Towards Industry 5.0

In the year 2021, a virtual reality training application has been developed, specifically for the Oculus Quest 2 headset, in order to allow the users to view and analyse 3D models for a wide variety of geometrical tolerances, tolerance zones and even the conformity condition and the datum features. This application allows the students to better understand the geometrical tolerances in accordance with the latest ISO GPS standards by using different 3D interactive models in order to highlight different types of geometrical tolerances and tolerance zones. In order to try to make the virtual reality training application more mobile and accessible for students, a mobile application, designed for the android operating system smartphones, has been developed. This application can facilitate better learning outcomes within the teaching-learning process by enabling the students to visualize a wide variety of 3D models representing different types of geometrical tolerances. Due to the dramatic evolution of technology in the past 20 years and the need to constantly keep up with it, the learning and teaching process suffered a massive change. The Covid pandemic has closed Universities all over the world and so, for the teaching process to continue, a sudden shift from traditional teaching to a more modern one involving the digital world was needed. Thanks for the fact that, nowadays, students are more inclined to use different types of mobile devices, the shift to the new learning paradigm has not left a great “scar” on student and teachers.

It is very important for companies with high inventory turnover to be able to efficiently carry out sales and raw material purchases in their trade processes. For this reason, it is very important to be able to predict their short-term sales to execute their own plans in the most effective way. In this study, LSTM, SVR and LR models are proposed to predict short-term sales of companies. For this purpose, 6-month data of a retail company operating in B2B was used. First, to get a more effective result in hourly forecasts, the data, which is a 2-dimensional array, was used in such a way that it would be effective in the last 24 h by including the rolling mechanism in the model. Then, LSTM, SVR and LR models were applied using the dataset developed with the rolling mechanism. The results of the analysis show that, although close to each other, the LSTM model captures the patterns better and that the use of this model can be used as a different option in the management of companies’ short-term sales.

Due to its high cost, loss of productivity, and most importantly, loss of time in training a new employee, employee retention has become a strategy that has made even more attractive for many researchers and professionals in the field. The purpose of this study is to present a case study that addresses the problem of employee churn and develop a model which predicts employee retention best. In the present study, the most well-known machine learning techniques such as Logistic Regression, K-Nearest Neighbor (KNN), Naive Bayes, Decision Tree, Support Vector Machine (SVM), XGBoost, Artificial Neural Network (ANN) and Random Forest were used. Finally, the performance of the proposed approaches was evaluated. The numerical results showed that the proposed Naïve Bayes clearly outperformed all other classifiers according to all evaluation criteria except Accuracy. However, Random Forest gave the best results according to the accuracy criterion.

Industry 4.0 has produced a new concept for companies with changing production processes and business models. Technical advances increase productivity, flexibility, production speed, mass customization, resulting in higher quality and productivity for businesses. An important factor in the implementation of Industry 4.0 is data collection and analysis for real-time decision making, so that the company becomes more flexible and improves its processes based on the evaluation of snapshot data, thereby optimizing production. Competitiveness in the market has created new challenges, prompting companies to seek fundamental solutions in quality, performance and agility in their processes and products, so the manufacturing execution system (MES) has become indispensable to assist them in this process. The system brings together the company's planning and production, providing access to information displayed in graphs, allowing monitoring and analysis of production, product and equipment status, enabling monitoring of usage, minimizing idle time. The MES function is to manage resources, improve equipment utilization through data trending and historical analysis. Industry 4.0 has brought advanced information and communication systems to companies, but to implement them also requires efficient processing of processes. This study focuses on the development and implementation of a production execution system using the Python programming language, open source hardware and software, enabling industry 4.0. The data to be obtained will be processed in a compiler environment, and the efficiency and efficiency of the existing equipment will be calculated and these values will be reflected on the screen with an interface.

Brand is one of the most important parts of businesses and many elements are brought together to create a brand. In order for customers to prefer brands, businesses need to consider both customer general and specific expectations, focus on the right points and offer the most appropriate solution to customers because customers consider many factors when making their brand choices. The purpose of this study is to determine which areas the companies operating in the telecommunications sector should focus on according to customer expectations and criteria for brand preference by using the Fuzzy Cognitive Mapping (FCM) method. Customer expectations and criteria are obtained as a result of literature research. After the data are prepared, the most effective criteria are determined with the FCM method. In this study, it is determined that which areas the companies operating in the telecommunications sector should focus on according to customer expectations and criteria. FCM is very useful to decide in complex situations like this. The greatest limitation of this study is determining the customer criteria for brand preference. This study shows that FCM can be very useful to determine the most crucial customer expectations for telecommunications sector. In addition, FCM can be used in other sectors where customer expectations are very important and decisive, to prioritize customer brand preference criteria and to guide businesses.

In an era of digitalization many companies face the challenge of making prompt and viable management decisions. Decision Automation aided with Business Intelligence provides dramatical improvements to the quality and efficiency of management decisions, as well as business processes modelling and analysis. The aim of this paper is to develop methods and tools for automation of the decision-making procedure with Agile BI tools at different stages of management process.

The competition conditions, which are getting more and more difficult in our age, made it inevitable to constantly monitor the performance of banks, which is one of the most important elements of the financial system. The ruthless competition environment forces bank to use the resources they have in the most efficient way. Therefore, it is very important for banks to evaluate their own performance and take measures to increase their performance in line with the evaluation results. The aim of this study is to comparatively analyse the financial performances of the top five banks operating in Turkey in 2020, which have the highest profit ratio in terms of asset size, for four quarters. Performance evaluation of banks was made using 9 criteria and the success of the management strategies followed by the banks throughout the year was evaluated by monitoring the performance rankings in four periods.According to the results obtained from the study; Ranking first in the financial performance ranking of the five banks analysed, Ziraat Bank raised its score from 0.62 in the first quarter to 0.75 points in the second quarter, and managed to maintain its first place performance until the end of the year, despite falling to 0.60 points in the third quarter. The performance increase of this bank in the first place in the second quarter, which is the crisis period, was interpreted as turning the crisis into an opportunity. While the performance score of the other bank, which ranked second in the first quarter, was 0.56, it decreased to 0.37 points in the second quarter and increased again to 0.50 points in the third quarter. The continuation of this bank's second place performance throughout the year was interpreted as demonstrating a stable performance management, but not being able to take advantage of the opportunities in the second quarter and its performance declined, but showed a rapid recovery in the third quarter.

This study was carried out to evaluate the journals chosen by academicians working in industrial engineering and operations research fields to publish their scientific publications. In the study, in which a total of 133 journals were evaluated, the publication times of the journals and their publication quality were considered under various criteria. The primary purpose of this article is to provide a ranking for all covered academic journals in the relevant field. While similar studies evaluate publications according to a single criterion, this study provides a ranking by considering multiple main criteria and their sub-criteria. It is also suggested to consider some new factors that were not considered before but are valuable to the authors, such as the acceptance rate of the journals, review and publication times, citation score, and quartile information. The data of this study were obtained from reliable, open-source institutional sources such as the web pages of journals, Google Scholar, Scopus, and Web of Science. Results indicate that considering different criteria directly affects the ranking of journals. Also, sharing different metrics such as acceptance rate and review time by journals affects the rank of journals. This study will help academics, students, and all academic scientists understand how journals perform according to the determined criteria and choose journals when submitting their publications.

In recent years, football clubs, mostly due to financial reasons, need to evaluate the football players more accurately in line with the demands of their technical teams and to make the right choice (the need to transfer the right player) among the players they have evaluated. Football clubs are customers throughout the player selection process, hence the “voice” of the customer; must be taken into account in such a way as to meet the expectations of the technical teams from a football player for any position. The purpose of this paper is to evaluate the football players according to the needs of a football club technical team and to choose the best among them. In this study, the goalkeeper position will be examined. In future studies, studies will be expanded for each position. The requirements of the technical team for the goalkeeper position will be evaluated with 38 different criteria under the main headings which are technical, mental, physical and goalkeeping. In this paper, potential goalkeeper candidates will be evaluated with the help of the Analytical Hierarchy Process (AHP) method and compared with each other to choose the best among them. In addition, the weights and evaluation criteria related to Quality Function Deployment (QFD) and Quality House (HOQ), which the technical team of X (the club that is the subject of the study) Football Club needs for the goalkeeper position, will be developed and some improvement areas will be determined. A case study will be conducted among the five goalkeepers (Goalkeeper I, Goalkeeper II, Goalkeeper III, Goalkeeper IV, Goalkeeper V) regarding the goalkeeper needs of X Football Club. Data will be obtained from Football Manager 2022 game. In addition, HOQ rates will be made by the technical team of X Football Club. The findings will point to the best goalkeeper out of the five that meets the needs of Football Club X. In addition, according to HOQ, it is aimed to determine the most important factors for the improvement of goalkeepers’ performance in line with the criteria of the technical team of X Football Club.

Sustainability gains importance parallel to the fact that natural resources sharply decrease. One of these resources is water and effectively usage of water resources becomes more crucial as not only water is an essential component that faces to run out but also recycling and reusing concepts are becoming important. Wastewater can be efficiently reused under effective policies and for these policies, wastewater amount forecasting is very important. Considering the fact that Turkey has been experiencing to improve its waste management strategies, wastewater management is also very crucial for Turkey to develop its policies. Thus, Turkey’s wastewater amount needs to be accurately forecasted in order to effectively manage wastewater discharged to lake, sea, soil and other resources. This study focuses on the forecasting for wastewater discharged to different resources. Box-Jenkins time series analysis has been used to forecast them under different categories. After analyzing and modelling, the real data and the estimated data fits well for the indicted time series model.

New types of needs, rebellious threats, or out-of-control situations emerge along with the development of human society and the introduction of new technologies. Many options—whether to serve the needs of law enforcement, the film industry, or the military—have been and are still being considered to address these issues of the new generation. Rural hospitals in some nations of central Africa are tough to access and supply. Road infrastructure issues, too dangerous commutes, or a lack of convenient flight options. UAVs are the quickest, easiest, most affordable, and most effective way to keep helping the needy population in those areas. During the American military’s conflict with Viet Nam, the enormous losses of American soldiers killed in enemy ambushes, helicopters shot down, and ground antipersonnel mines prompted scientists to look into and create a new strategy for defeating foes worldwide with few casualties. Thus, there has been a lot of interest in unmanned aerial vehicles (UAVs) over the past few decades, which is probably because UAVs have a lot of advantages because they can fly. Including necessary onboard electronics like GPS and cameras make it easier to realize the intended objectives. Instead of using conventional methods, a VTOL (Vertical Take Off and Landing) RPV (Remotely Piloted Vehicle) is created to track a chosen ground target during assigned surveillance missions.

The influence of technological parameters of centrifugal induction sintering on the adhesion of the coating to the base of the cylinder liner was studied. The process of restoration of cylinder liners of ship engines by centrifugal induction sintering of hard alloy powder ПГ-CP2 has been studied. The magnitude and nature of the linear shrinkage of the coating metal was determined. The shrinkage properties of cast iron are highly dependent on the formation of the casting structure, which, other things being equal, is determined by the cooling rate.

In order to get more efficiency from the soil, the soil needs to be processed and made ready for planting. Disc harrow facilitates soil preparation, since they are heat treated and become highly strong. Vibration causes break down and failure of disc harrows and mounting parts to the chassis. Therefore, it is important to investigate the frequency and amplitude of vibrations occurring during operations with disc harrows. In this experimental study, the disc harrow was connected to a tractor and operated together in order to get vibration measurements. The measurements were conducted with the help of a unit consisting of a three dimensional (3D) accelerometer vibration sensor, an interface and a special computer. The 3D accelerometer vibration sensor is placed on the chassis, where discs attached. The signals obtained from the sensors in volts were transferred to the computer after being converted to millivolts/volt in an interface. The acceleration values of the tractor were calculated, the graphics were drawn and the minimum, maximum and average values were obtained.

Nowadays, porosity evaluation is a very important part of the production process in the automotive industry and engineering production. The methods used for internal structure evaluation are destructive and non – destructive. One of the most useful non – destructive methods is industrial computed tomography which is based on the application of the X – ray beam in the process of getting data. This method allows evaluation of the external and internal structure from the same data. However, the accuracy of the scan used for porosity evaluation is still in the process of researching. There are not many possibilities for verification of the results because all the analyses are virtual. One of the methods used for results comparison is destructive metallographic cut but it is possible to compare defects only in 2D. Therefore, the idea of creation of the reference sample for porosity evaluation for CT scanning became the aim of this paper.The milled aluminium alloy sample was created from 4 identical parts with hemispherical artificially created defects. Individual parts, that is parts in disassembled state, were measured using focus variation microscopy. The assembly of 4 pieces in one part was followed by a CT scanning process. Comparison shown that the highest relative differences up to 26% were achieved in evaluation of the smallest pore volumes. The smallest relative differences, approximately 2%, were achieved in evaluation of the biggest defects.

Additive manufacturing technologies present several advantages over the conventional technologies, like the high flexibility, an easy and fast path to manufacture parts from the CAD file and it is appropriate for manufacturing parts with complex shapes, which are hard or impossible to manufacture with conventional technology. Selective Laser Melting is an Additive Manufacturing technology, suitable for manufacturing metal parts, using a powder that is melted in the desired areas. However, the technology is mostly used for prototyping and one of a kind parts manufacturing, due to relatively high cost and limitations in the dimensions of the parts. This paper aims to study if the properties of the Selective Laser Melted 316L, stainless steel are feasible for manufacturing a part for the automotive industry, specifically brake discs with complex internal structures. Tensile and compressing specimens are manufactured using the Selective Laser Melting technology, to determine the ultimate tensile strength, elongation, and porosity, using computer tomography. The results show that a 99.99% density is achieved, which indicates that the characteristics of the material are not influenced by the porosity and using this technology is suitable for manufacturing brake discs for the automotive industry.

In global competitive conditions, correctly designed strategic demand forecasting studies aid to gain an advantage over competitors by accurately predicting production systems based on previous sales data in order to plan future demands in a consistent manner. Demand forecasting has a significant impact on the determining the production volumes of companies and preventing serious losses such as prestige and high costs. In this study, it is aimed to create demand models of a dyeing company for the next five years using recently developed machine learning tools such as random forests (RF), support vector regression (SVR) and artificial neural networks (ANN). The success of the models has been shown according to the error rates (MAPE, MSE, RMSE etc.) obtained as a result of the utilized methods. The proposed forecasting models will contribute to the strategic decision-making mechanisms of the company adequately for future projections. The effectiveness and applicability of the developed models are discussed in detail through a real case study.

The design of a new generation 3D printer has been proposed to improve the performance of 3D printers, based on the analysis of their parameters and setup. The working principle of the proposed 3D printer was studied, and according to the working principle of each element, the control scheme of the printer and its operating algorithm were developed. Based on the control and operation scheme of the 3D printer, taking into account the nonlinearities, its Markov graph was compiled and its reliability was determined. During the print period, the reliability curves of the 3D printer elements in the Matlab environment were constructed based on the time-dependent change indicators of the printer’s monotonic deviation.

In today’s industrial standards having a zero-defect policy is very common among companies. However, many companies have a hard time reaching this goal. This work is aiming to reach a zero-defect level in one of the most important pieces of furniture assembly through a quality control automation system which uses a vision system for inspection. This is required since having even one faulty piece of fittings can make the assembly of Do It Yourself (DIY) furniture impossible. This system is using a state of the art camera to check every single piece with the help of an Artificial Intelligence (AI) based software and then separate the faulty products to ensure maximum service quality to furniture manufacturers.

The paper deals with the design of a robotic workplace with CNC machines and the subsequent simulation of the work cycle of the workplace. The task of the solution was the design of the components necessary for the automated operation of the workplace. Individual components were created in the SolidWorks program and then converted to the RobotStudio program. After creating the workplace scheme, a simulation of the workplace was carried out in order to present the functionality and better understand the function of the individual components. The process of implementing robotic workplaces into the real environment is significantly shortened by suitable variants of the created solutions.

Education 5.0 focuses on the use of new technologies, such as artificial intelligence and internet of things, to provide a more humanized teaching, mainly focusing on a students’ emotional and social development. The importance of gamification in education is based on enriching learning with the fun factor. The objective of this paper is to create a framework that can be used by educators to observe students in their acquisition of competencies. An instructional design, observation items, a framework for an observation schedule, templates for observation protocols, instructions for data collection and for the analysis of the results are provided.

To unify communication across partners in production systems, the German Plattform Industrie 4.0 network specified the Asset Administration Shell (AAS) both as a general concept and a specific data exchange format for assets in Internet of Things contexts. This contribution presents an approach to apply this concept to quality inspection (QI) processes supported by Augmented Reality (AR) assistant systems. It defines the submodels that contain all data required to provide shop floor personnel with necessary information during the process. Furthermore, the approach contains the representation of necessary system and positioning information for correct AR overlay of the QI information on top of the real-world object. Finally, a prototype AAS system implementation for Microsoft HoloLens 2 based on Eclipse Basyx is presented for evaluation and validation purposes.

Industry is an important driver for prosperity in Europe. Industrial and technological developments have influenced European society more than any other developments. The challenge has always been for policy makers to protect citizens from the negative aspects and embrace the positive elements. Innovation is one of the key elements for novel technological developments. The European Commission state that future technological evolutions must respect all key priorities including the environmental, social, human-centric ones. This means complex and challenging problems that need to be solved will require new ways of thinking and working. One of the most important assets we have is a well-educated workforce. Futureproofing this workforce with diverse and inclusive work practices will be critical ensure that top talent will be attracted, and remain, in these companies going forward. “Managing for diversity” as described by Chavez et al. in 2008 means bringing that competitive advantage through the attraction, retention, and leveraging of the unique skills and capacities of a diverse workforce [1].

Traditional methods that have been going on for a long time have begun to change with the spread and widespread use of the internet. A new transformation has been experienced with digital media. This transformation has brought about changes and developments in various sectors. In the healthcare sector, great steps have been taken at the point of transformation, and the Industry 4.0 revolution has also affected hospitals. In the study, research has been conducted on what changes that Industry 4.0 has created on hospitals, how it affects and contributes the sector. Within the scope of the research, a digital roadmap was proposed for three hospitals that tend to digitalize and focus on development and innovation. Thus, a tool will be created for hospitals to see their faults and evaluate themselves. In the model proposed within the scope of the study, a total of 25 criteria, including six main and nineteen sub-criteria, were determined. With the determined criteria, it is aimed to measure the digital maturity level of three hospitals. In the study, the BWM method was preferred in determining the criteria priorities. In the ranking of the identified alternatives, the CODAS and MABAC methods were compared and the ranking results in both methods supported each other. Since the topic of digital transformation has been attracting attention and demand recently, it is thought that the study will contribute to both the literature and the healthcare sector. However, the methodology has new and limited applications. In addition, to the best of our knowledge, there is no study comparing the digital maturity performance of hospitals in the healthcare sector with the proposed methodology.

The digitization of the working world is changing almost everything – the way we work, plan, and control processes. This article is about the application of digital humans and describes the change in times and paradigms toward digital human models and virtual ergonomics for the apparel industry and ergonomics. The digital body is now using with everywhere in course of industry 4.0. Representation of man could now be three-dimensional, but that one with it also has properties that go beyond the purely geometric production in the so could program the resulting digital human models. These digital human models were wholly integrated directly into CAD programs so that now the desired human scale could be available to the designer. The anthropometric properties of the digital human body are started to be used more widely. The development of digital human models should be parallel to the anthropometrically oriented models, also developed biomechanical models, which initially represented the physical inertia properties of the human body elements, but increasingly with the forces and muscles have been equipped so that complex movement sequences can also be represented with them. When it comes to personal attention to the vehicle, the design appeals to the “emotion” and the ergonomics to the “ratio”. Although ergonomics, usability, and related disciplines have existed for a long time, but have developed into decisive competitive factors in many companies, especially in recent years. The automobile is probably the most fascinating industrial product of all.

In this paper considers the occurrence of quantization and overload (restriction) noises at the analog-to-digital conversion of TV luminance signal. The ratios of the powers of restriction noise and quantization noise have been determined for inversely proportional and inverse exponential model of brightness distribution on TV broadcast images. The effect of restriction noise on the quality of image reproduction and the possibility of reducing this noise by compressing the dynamic range of the brightness signal of TV broadcasting are experimentally determined.

The quality indicators functioning multiservice communication network, built in accordance with the architectural concept NGN (Next Generation Network) and FN (Future Network) based on the technology building distributed communication networks, are analyzed. The performance multiservice communication networks using SDN (Software Defined Networking), LTE (Long Term Evolution), 5G New Radio, IMS (Internet Protocol Multimedia Subsystem) and NFV (Network Functions Virtualization) technologies was chosen as a system criterion. Based on the study, a new approach to constructing a method for calculating the performance network is proposed, taking into account the self-similarity property of the transmitted traffic. On the basis calculation method, analytical expression is obtained to evaluate the indicators channel resources, bandwidth and probabilistic-temporal characteristics of the communication network in the provision multimedia service.

In this study, the open vehicle routing problem with heterogeneous vehicle fleet (HFOVRP) is addressed. Unlike the standard vehicle routing problems, vehicles do not return to the depot after their customer visits in the open vehicle routing problems. In the HFOVRP, demands of customers must be served by a heterogeneous vehicle fleet, where the tour length of each vehicle is limited by a maximum allowed tour length. The aim of the studied HFOVRP is to minimize the total fixed cost of used vehicles. In this study, a constraint programming (CP) model is developed for the HFOVRP. A mixed-integer linear programming (MILP) formulation of the HFOVRP is also provided to make a comparison with the CP model. Then, the performances of the CP and MILP models are assessed on a set of small-sized instances with varying number of customers. The computational results show that the CP model is effective for providing good-quality solutions for small-sized instances of the HFOVRP in short computational times.

The Industry 4.0 revolution paves the way for a radical transformation in production systems. This transformation also necessitates acquiring the required skills to accomplish new tasks and job descriptions. On the other hand, individuals have different skills, learning preferences, and requirements. In this sense, designing training programmes for Industry 4.0 requires considering the gap between job requirements and learners, individually. This study presents a customized web-based training platform developed as a part of CEPI 4.0 Project. The platform incorporates training modules developed as a result of need analyses conducted in Turkey, Austria, Slovakia, and Romania. The competency gap of an individual is determined through an initial assessment. Then, each individual is presented a customized set of contents from the Industry 4.0 training modules, which have been prepared through our project. Finally, the individual or group-level progress achieved through customized training is demonstrated using an Industry 4.0 Education Scale developed for the project.

Data envelopment analysis is a method that enables performance evaluation and comparison in institutions, organizations and companies operating in both the service and production sectors. Thanks to this method, besides measuring and comparing the activities of different units, it is possible to find ways to make inefficient units efficient. The ability to use multiple inputs and outputs is one of the biggest advantages of this method. Within the scope of this study, a performance evaluation was made in order for the underwear company, which reached 62 stores in 5 years, to realize its mission and vision. The stores of the company in 3 different regions were evaluated on the basis of 3 inputs and 3 outputs. Afterwards, an efficiency calculation and comparison was made on a regional basis. In this way, the differences between the regions and the aspects that are open to development were also revealed. At the end of the method, evaluations were made on the basis of stores and regions, and the necessary conditions for inefficient units to be efficient were examined.

Efficiency shows how much value and surplus value can be produced with a unit of expenditure. The efficiency of the production process is influenced by many parameters, the energy consumption can be found among them. Maximizing energy efficiency can therefore help in the fight against climate change and the depletion of resources. The concept of energy efficiency serves recognizing the problems of non-sustainable development and moving in the direction of a sustainable economy. After studying the issue of energy efficiency, the paper deals with the cooling-lubricating fluids. The Kraljic matrices for grinding and diamond burnishing were created and analysed. In terms of energy-efficiency, we determine the oils and emulsions that prove to be the best. The factorial experimental design was used in the best zone of Kraljic matrix for creation empirical formulas where the best surface parameters could be get when using the least energy.

Many researchers in the field of the quality evaluated that management of organization has a significant impact on successful implementation of quality management. The leadership approaches of the managers in the organization affect the quality management (QM) process directly. Leadership approaches have been grouped by researchers as transformational, transactional and non-transactional. According to the researchers’ study the approach of transformational leadership (TL) has a positive impact on successful QM practices. The purpose of this paper is to examine which of the behavioral component of the TL approach detailed in the Bass and Avolio’s Full Range Model of Leadership is important in the development of the quality management system (QMS). In the research, an Analytic Hierarchy Process (AHP) method was implemented based on the opinions a number of quality managers and quality experts from the production and service sectors in Turkey. As a result, the “idealized influence” behavioral component has higher importance in QMS.

In order to ensure the uninterrupted continuity of their activities, businesses have to keep certain levels of inventory in market conditions that cannot be precisely measured and easily predicted, such as uncertainty in demands and lead times, fluctuations in prices. Inventory for health businesses that produce health service output as a result of business activities; means materials that must be kept for examination, treatment and diagnosis and that directly affect human health. For this reason, the management of medical inventory is very important both for human health and for the financial continuity of hospitals. In this study, which explains the inadequacy of the current medical consumable inventory control method used in the operating room unit of the hospital, which is the subject of the study, by using simulation and optimization techniques, and saving inventory costs by designing alternative inventory control models to the current situation; first of all, the current medical consumable inventory of the operating room were examined by ABC-VED analysis. Then, the new inventory control model, which was created using the (s,S) inventory control policy, in order to be an alternative to the existing inventory control management and current inventory control management of the operating room, was modeled using the stochastic modeling approach in the Arena Simulation package program, using real life data from the hospital. The simulation model is run for both inventory control models and the inventory costs of the materials are calculated for both inventory control models. In the last part of the application, the (s,S) inventory control model, which was designed as an alternative to the current situation, was optimized for the selected materials using the OptQuest optimization tool in the Arena Simulation program. As a result of the optimization, the minimum, maximum and reorder point parameters of the materials used in the study were re-determined to optimize the inventory cost of the materials. By using the optimized inventory parameters (s,S), the inventory control model was run again and the inventory costs of the selected materials were calculated for the third and final time. Finally, the outputs of the three inventory control models were analyzed and it was concluded that the lowest inventory cost value with a confidence level of 95% was achieved by using the optimized (s,S) inventory control model and the current inventory control method of the operating room was insufficient in terms of cost.

These days, sustainability has become a fundamental concern for defining strategic directions in companies. Accordingly, companies not only focus on economic aspects but consider environmental and social issues to make managerial decisions. Asset-intensive organizations need to handle the sustainability dimensions through their asset management process as it hugely affects their profitability and sustains success. Therefore, a proper risk analysis procedure is required in the physical asset management framework, which focuses on sustainability. This study proposes a fuzzy risk analysis process that considers sustainability aspects in physical asset management. To that end, all risk factors are identified based on sustainability issues and the life-cycle of physical assets. Then the critical ones are ranked based on structured criteria and sub-criteria for risk analysis. In this regard, several criteria and sub- criteria influencing risk criticality are first determined, and their weights are determined using the fuzzy best-worst method. Then, the identified risks are ranked based on these measures and their associated weights using the fuzzy TOPSIS method. A case study in a gas plant is also provided to show the model’s applicability.

This paper focuses on issues of processing production plans data using Open-Source Big Data technologies, including issues of data collection, preparation, storing, transforming and analysing and technology benchmarking. The digital framework for production plan files processing is described, prototyped and tested using different parameters of data volume and memory for production planning. Functional and component architecture of the framework consists of digital services starting from loading data from hundreds of production plan files, through processing and transforming these files into json objects and inserting SQL into in-memory database, to analysing them using KPI-based methods. Proposed system allows near real-time production planning which gives opportunity for decision makers to monitor production plans in real time and take appropriate actions. Proposed digital production planning framework is tested using production plans data from real automotive industry company.

Spiritual values and the dialectic of their development are closely connected with social relations, as well as the nature of the social structure, and have a special place in the structure of human development. In the general system of spiritual values, the characteristics of each social structure, and people's ways of thinking and behaving are reflected as a whole. Therefore, when analyzing their content, it is necessary to approach the issue in an inseparable link with public relations. We must not forget the point of inheritance, because national and spiritual values, passing the tests of time, play an important role in the formation of the people and the nation, revealing the identity of each people, nation, and individual. The national and spiritual values of each nation are historically formed and form the basis of the national, existence of that nation. The people who protect, improve and adhere to their spiritual values are always met with great sympathy. Therefore, the presented article examines the evolution of spiritual values and their way in the life of society.

This study proposes a novel constraint programming model for the mixed-blocking permutation flow shop scheduling problem with batch delivery to minimize the total tardiness and batch cost. A mixture of various blocking type restrictions was considered in the mixed-blocking permutation flowshop part of the studied problem. The mixed-blocking permutation flowshop is integrated with the logistics process via batch delivery decisions. Therefore, the studied problem considers both production and logistics decisions simultaneously. In other words, the logistics decision directly affects the production schedule because customers expect their demands for individual products to be produced and delivered to them in a short time. Information exchange in the logistics and production phases helps companies establish a more flexible production system. The effectiveness of the proposed constraint programming model is verified in an illustrative example. According to the result, the model can be competitive in solving the problem.

The medical field is one of the many areas which constantly benefits from the advantages of additive manufacturing (AM), due to the possibility of fabricating custom implants with complex shapes. The purpose of this paper was to investigate the effect of drag finishing on the surface roughness of mandibular reconstruction plate made from pure titanium (Ti) and fabricated by the selective laser melting (SLM) process. The surface roughness parameters considered were Ra, Rq, Rt, Rz, Sa, Sq, and Sp. The measurements were done on side surfaces and top ones. Using computed tomography (CT) scan, we also analysed the micro-porosity and the factors leading to differential porosity. In general, the Ra surface roughness suitable for maxillofacial implants is between 0.2 μm to 2 μm. The present work shows that the as-build part has the Ra roughness on the outer boundary around 9.1 μm (10.7 μm Sa) and 24.4 μm on the top surface (32.4 Sa). After we adopted the drag finishing parameters, we reduced the Ra surface roughness to 1.6 μm on the outer boundary (3.1 μm Sa) and 11.4 μm on the top surface (26.8 Sa). Due to printing conditions, the CT investigation indicates that the extremities of the reconstruction plate and the middle segment have different micro-porosity levels. This aspect can influence the mechanical properties and a physical test was required. To determine the mechanical resistance of the actual implant, we used the Inova testing system. Under continuous tensile load, the fracture appears nearby the screw hole at 402N and 3.3 mm displacement. The voids identified by CT have a limited influence on the fracture area. To limit the micro-voids volume and distribution, future studies are needed to analyse the impact of SLM technological conditions on micro-porosity.

Gears are one of the most commonly used parts in different manufacturing industries because of their functionality, and so the question of how to improve the geometry of these parts was always in the open. The research paper brings up the idea of reducing the material volume used in the manufacturing process by using a generative design method, meaning a free-flowing design using generative design software. The CAD model is subjective to parameters that are targeted in the program (volume, mass, safety factor) that are a frame of reference to develop different iterations from which we chose 5 of them. A finite element analysis is made to compare the generative version with the non-modified CAD to see the differences in behavior. These results are used to choose the best iteration of the gear. The parts modified as well as the non-modified ones are manufactured using different additive manufacturing technologies. An analysis is made to see the differences in terms of mechanical characteristics by making tests for surface durability, tensile strength, and bending. The results of the analysis show a 50% decrease in material volume without compromising the structural functionality.

In view of the rapid increase in the volume of air traffic, optimization of airport management has recently gained a great deal of attention to be able to increase the airport capacity and efficiently use scarce resources, namely gates. Improper assignment of gates causes flight delays, inefficient usage of scarce resources, customers’ dissatisfaction and other domino effects. Generally, a typical hub-and-spoke handles hundreds of flights every day. Considering this, the gate assignment problem (GAP) addresses the issue of maximizing the usage of gates equipped with aerobridges, namely bridge-equipped gates. Due to the numerous flights and gates involved in the problem, it is often impractical to solve GAP with optimality in a reasonable amount of computational time. Consequently, novel nature-inspired heuristics have been proposed to generate good solutions to AGAP. In this study, we employ Whale Optimization Algorithm (WOA) which is one of the recently developed swarm-based metaheuristics to find good solutions to complex GAP. The proposed method assigns scheduled flights to bridge-equipped gates based on both total flight-to-gate assignment utility and use of apron gates. In order to demonstrate the efficiency of the algorithm, some instances with different sizes are generated and the results obtained by using CPLEX Studio IDE optimizer and WOA are compared with respect to solution quality and computational time. To ameliorate the solution quality, we proposed two local search procedures embedded in WOA. To the best of our knowledge, WOA has never been applied to GAP so far. Thus, the chief contribution of this study is to apply such novel swarm-based metaheuristic, namely WOA to GAP. Comparison of the results with the optimal schedules has allowed us to demonstrate the power of the proposed algorithm.

Meta-heuristics are widely used methods in OR literature. Whale Optimization Algorithm (WOA) is one of these meta-heuristic methods which is recently developed. The objective of this study is to find the best possible job schedule while minimizing the make-span (i.e., the length of time elapsed from the beginning of first job to the end of the last job.) of the system. This problem is initially solved by using Optimization Programming Language namely CPLEX Studio IDE 20.1.0. Then, WOA which is a current meta-heuristic, used to solve the same problem. Some toy instances of different sizes are created and the results obtained by using CPLEX and WOA are compared. Although, in some studies in the literature, WOA is used to solve job shop scheduling problems, there is not a study which uses WOA as a solution methodology for parallel machine job scheduling problem with machine eligibility consideration to the best of our knowledge. Thus, the main contribution of this study is to include machine eligibility to the conventional job scheduling problem and to use WOA while solving the corresponding problem.

Given the importance of the concept of sustainability, this article explores the issue of companies developing new products. Therefore, this paper presents the author's proposed model based on product life cycle stages and environmental methodologies such as IDOV (Identify, Design, Optimize, Verify), SIPOC (Supplier, Input, Process, Output, Customer), and 4Rs (Reduce, Repair, Reuse, Recycle), which has been used to formulate a set of principles for developing products in a sustainable manner, in which the reduction of carbon footprint is desired. The presented model has 30 low-carbon principles developed by now and for each step from life cycle or the methods presented there is at least one principle described. Therefore, the model can guide developers to adopt those principles in a chronological order, according to each evolution step in the life cycle product and add more appropriate low-carbon principles if they still consider it is necessary.

Lithium ion battery technology is the most promising energy storage system thanks to many advantages such as high capacity, cycle life, rate performance and modularity. Many transportation applications including marine, aerospace and railway have been utilizing lithium ion batteries. Likewise, there is a dramatic transition from conventional vehicles having internal combustion engines to electric vehicles (EVs). In this review, current lithium ion technology and electric vehicles are introduced. Furthermore, expected future technological advancements are discussed from the active materials to scalability. It can be summarized that consumers have three main concerns towards electric vehicles: range, charging time and life time. Possible solutions to overcome the range anxiety, charging time, and lifetime are exhibited from mostly material and cell design perspectives. Although it is possible to enlarge the volume of this review, the key subjects are presented by introducing the most current advancements which can be adapted to current production infrastructures. Those achievements in the battery level will transform the global transportation sector.

University course timetabling problem is a problem that tries to optimally assign days, hours, and classrooms for courses in the curriculum, taking into account constraints such as availability of the lecturers, capacities of the lecture halls/classrooms and possible other special rules. In this study, the course timetabling problem of Izmir Bakırçay University Industrial Engineering Department is considered. Although it is a relatively new university in Turkey, it has become increasingly difficult to prepare course timetables due to the increasing number of departments, courses, and students, as well as the very limited current number of classrooms, lecture halls and laboratories within the campus. Currently, the course schedules are prepared with heuristic methods manually. This process is extremely challenging due to the mentioned scarce resources, the most critical being the number of amphitheaters dedicated to the department, as well as the limited number of computer labs. Even coming up with a feasible timetable for a semester can take weeks and several hundred valuable man-hours in the current situation. In order to solve the real-life problem on hand, an integer programming model was developed with an objective of minimizing the used number of classrooms. The model takes into account the unavailable hours of the lecturers. It also considers many constraints such as not overlapping the classes of consecutive years’ lectures, as well as other traditional timetabling constraints. The model was solved using IBM ILOG CPLEX Optimization Studio, an optimization software package. In addition, an interactive and simple user interface was developed in MS Excel VBA programming language, which communicates with the optimization software automatically, thus allowing the decision makers to use the interface without the need for any technical knowledge. Optimal course timetables meeting the university rules and lecturer preferences can be created automatically and efficiently as a result.

In today's complex manufacturing industry, no-wait permutation flowshop scheduling problems are one of the most encountered types of scheduling problems. The floor configuration of this type is the one with the restriction over the jobs that cannot wait between successive machines. The problem can be modeled from different points of view on the floor configuration. Hence, in this study, three mixed-integer programming models and two constraint programming models are studied on the no-wait permutation flowshop scheduling problems for the three objective functions: makespan, total flow time, and total tardiness. Among five mathematical models, two are newly proposed to the literature on no-wait flowshop scheduling problems, and three are previously studied for the variants of the no-wait flowshop scheduling problems. Complete experimentation is accomplished on the well-known benchmark set of Taillard. Regarding the computational experiments, Model 4 performs best regarding the objective function value and the gap percentage reported in makespan and total flow time minimization. However, for total tardiness, although Model 3 performs best in terms of the gap percentage reported, Model 4 still performs best in terms of the objective value reported.

The problems that occur with the ineffective use of resources in an enterprise and the bottlenecks in the warehouse lines reduce quality and productivity, and negatively affect customer satisfaction. The aim of this study is to identify these problems existing in the system using ARENA simulation and to examine the bottlenecks, the factors that reduce efficiency with the obtained data. In this context, a time study is carried out for each department in the warehouse in order to see the whole process and to determine the source of the problem by making necessary visits to the enterprise. By using data obtained, scenario analyzes are carried out with the help of statistical distributions by using the process map ARENA simulation program, which is applied during the implementation phase. Furthermore, the second aim of the study is to examine each scenario and identify the scenario with possible output and the bottleneck experienced by the business. Based on these outputs, a new system proposal is presented at the final stage of the study.

The results of the simulation based on a software algorithm designed to quantify the input matching at the input of a multichannel frequency-scanning antenna array power divider are presented. It was found that when performing wide-angle scanning in a relative frequency band of more than a few percent, the disadvantage of the known method for eliminating the normal effect is a sharp deterioration in matching in the lower and upper frequencies of the operating range. A new method is proposed based on an automated iterative process of optimizing the divider geometry, which makes it possible to obtain an acceptable match over the entire operating frequency band. The feasibility of switching from a serial power divider construction scheme to a series-parallel scheme is analyzed for wide-angle scanning in a relative frequency band of about 5%.

Steel materials are inevitable in many products used in various industry fields. Steel has positive properties in all life cycle stages, starting from good availability of iron, well known production process, affordable price, high plasticity, toughness and mechanical strength in use phase and excellent recycling possibilities at the end of life stage. The steel products production and manufacturing processes are common activities in production engineering where the impacts on the environment can be transparently shown with life cycle assessment. The analysis in this paper deals with life cycle inventory datasets regarding the steel production that can be used for life cycle assessment. First, general analysis of dataset providers and their life cycle inventory database features has been conducted. Secondly, analysis of specific dataset regarding the steel production has been investigated according to life cycle phase and geographical scope. The aim of this analysis is to investigate the life cycle inventory datasets that contain “steel” keyword in their name, and to reveal the differences between the similar ones. The results showed differences between the databases in general and specific differences regarding the steel production datasets and their global warming potential. Some databases provide information on various steel products and steel production and end of life operations, while others provide information on steel product mainly.

The Green Lean method seeks to avoid environmental waste, preserve ecological balance and sustainability, and accomplish these goals in a productive and cost-efficient manner. An eco-friendly approach to economic sustainability fosters synergy and offers the environment and society more tangible advantages. Supplier selection is a challenge that has been approached from several angles. As a result of the numerous competing criteria, it is recognized that multicriteria decision making methods (MCDM) are mostly used to address it. This research addresses the issue of an organization using a lean management strategy with supplier selection. To identify the lean factors included in the literature on supplier selection, a thorough literature study was undertaken. The fuzzy “SWARA (Stepwise Weight Assessment Ratio Analysis)” Method, which is often employed in the research domains and offers effective answers, was utilized in the first section of this research to analyze and weight the criteria that were collected from the existing literature. The method's use led to the determination of each assessment criterion's weight, which was then employed as a factor in choosing the suppliers. To determine the final ranking and choose the best supplier for the success of the business, the fuzzy “COPRAS (COmplex Proportional ASsesment)” method was used in the second part of the research. Following that, the managers are given the results in order to help them make better choices.

Additive manufacturing (AM) technology, which has developed recently, is used in a wide range of application areas such as from the medical sector to aerospace and automotive industries. Laser powder bed fusion (LPBF) is one of the metal AM techniques which provide an opportunity to generate complex geometries. Although LPBF has been started to be used for final geometries of the functional products, surface quality is still a great concern. Undesired surface features may cause the unexpected end of life of the functional parts by friction, wear, corrosion and fatigue fractures, as a result, high energy and material consumption and poor sustainability. Therefore, to achieve desired surface features of metal AM parts it is important to define suitable surface post-process. In this study, it was aimed to define the effect of vibratory polishing surface post process on the surface quality of the LPBF manufactured AlSi10Mg parts. Ceramic and polymer abrasive media were used during the process. Surface roughness values were measured at ten-minute intervals by stopping the process. The polishing process was applied for 60 min in total. At the end of this period arithmetic mean surface roughness of the sample polished by ceramic media was decreased by 62.14% while this ratio was 47.92% with polymer media. This study revealed that vibratory polishing was a very effective method for ensuring the surface integrity of metal AM parts and increasing the surface quality. By reducing the roughness and increasing the surface quality, it will reduce the energy loss due to friction in tribological systems and support sustainability. The studies are going on with different metal AM parts and different geometries.

The parcel locker is a new last-mile delivery concept that provides outdoor delivery of commercial goods. In recent years, determining the parcel locker locations has become critical in the literature to provide an effective locker service to the customer. Accordingly, this study aims to optimize the parcel locker locations with effective pricing decisions for the locker service. We use a price-response function to determine the price of the locker service in the customer layers. We generate new benchmark problems to evaluate the performance of the mathematical modeling approach. The computational results indicate that the price-response function is effective in determining the price of the locker service, and the proposed mathematical model, having introduced customer layers, gives promising results for future studies on combining the optimization of parcel locker location decisions and pricing widely applied in revenue management practices.

The success of supply chain management (SCM) depends on timely and accurate information sharing. Understanding the factors contributing to the quality and timeliness of information sharing would help supply chain professionals and practitioners. This study investigated whether top management support and information technology (IT) enablers positively influence information sharing and information quality in the supply chain activities of small and medium-sized enterprises (SMEs) in Karachi, Pakistan. Based on the data collected from 534 respondents, multivariate regression analysis was performed using SPSS software. The results showed that top management support and IT enablers considered inter-organizational facilitators positively impact the information sharing and information quality in the supply chain of SMEs in Karachi, Pakistan.

Several research works have been conducted in the framework of Lean and Green, yet, there is a lack of approaches that explicit, at a conceptual level, how to implement both paradigms in a relevant and integrated way. Alongside, nowadays’ supply chain environment is characterized by its volatility and unexpected and recurring changes which implies empowering organizations to maintain their sustainability. Supply chain resilience is distinguished by its ability to increase readiness with risks. In this optic, the present research work aims at providing managers and decision-makers with a formal and generalizable approach that provides appropriate guidelines for a Resilient Lean Green supply chain regardless of the level of adoption of both Lean and Green philosophies. The approach we propose is based on risk management since risk occurrence is generally behind performance failure. A case study was introduced to demonstrate the applicability of this approach at a corporate level.

Today, effective workforce scheduling is crucial for companies. This paper presents a workforce scheduling problem for multiple production lines. This study aims to develop an efficient and methodological shift scheduling algorithm for a heating device plant to reduce unnecessary overtime and improve quality and performance. The workers are assigned to the stations based on their qualification rates, and a line balancing option is provided if required. After linearizing the non-linear objective function using an innovative approach, the mathematical model is developed and solved by OPL CPLEX STUDIO IDE 12.10.0. With toy and original data. The mathematical model is verified and validated, and the results provide the optimal assignment of the workers to maximize the quality of lines. Since the company cannot use CPLEX due to license restrictions, the mathematical model is integrated into the Python program using the Pulp library to provide a solver option to the company. Moreover, the Hungarian method is coded in Python to create an instant solution. Since the company prefers to assign the workers manually, a greedy method is developed to improve the manual solution. Finally, a user-friendly Decision Support System is designed to support the decision-making processes.

In this study, the facility layout of a packaging machine production factory is planned according to the costs of the material handling equipment and distances between the departments. The branch and bound algorithm are implemented to optimally find the cells to be assigned for the projects. Costs are calculated in Excel and an optimal layout is developed in the facility according to the distances and the material handling costs information provided by the company. Moreover, a decision support system is developed to display a flexible facility layout design for a project-based production system which provides insight for the managers to decide the locations of packaging machine production cells. The locations of the projects to the manufacturing cells are determined by using the algorithms and models using the Python and OPL CPLEX 12.10 Optimization Studio software.

In this paper, a real-life flexible job shop scheduling problem (FJSSP) for valve production having sequence-dependent setup times and machine unavailability constraints is studied. The aim is to minimize the weighted sum of earliness and tardiness of the scheduled jobs. Since this problem is known to be in the NP-Hard class, we develop a Genetic Algorithm (GA) enriched with Iterated Local Search (ILS) to obtain near-optimal solutions for both the company’s problem and also for much larger instances in a reasonable run time. For the real-life implementation, we develop a user-friendly Decision Support System (DSS) consisting of databases for the inputs, a GA algorithm embedded as Python code, and a Gantt Chart representation of solutions as the output.

One of the frequently encountered problems in the labour-intensive apparel industry is the deviation from the target deadlines. The biggest observed reason for this problem is that the standard operation times and therefore production targets are being defined as deterministic values in the stochastic environment. The statistical studies carried out in this project show that the standard deviation of the operation times is too significant to be ignored. The natural randomness in the performance of the workers and additional factors such as fatigue and learning effect are some of the most important reasons that increase the variability in the system. The project is carried out in conjunction with one of Turkey’s top companies within the apparel sector, TYH Tekstil A.Ş. Different policies are applied by the company to dynamically solve the problems encountered during production. In the literature review, different simulation-based policy methods for a sample order were examined. However, since the company’s sewing line has its unique characteristics, the reviewed policies alone were determined not to be suitable for use. This project aims to determine the mentioned randomness parameters by analyzing the day-hour variability of the operation times statistically and provide the company with a tool that will simulate the sewing lines ahead of production using the order-specific inputs and data analysis, dynamically analyze and improve the performance of the sewing lines by Tabu search algorithm and visually/verbally report any problematic operations/occasions that may arise and performance improvements made by the decision policies for minimizing deviations from target deadlines. To increase the flexibility of the system and make it dynamic, the Python programming language was used.

The agrochemical sector has always been in the industry’s spotlight, resulting in its unique characteristic that has impressive-expressive roles in the market and conflict-affected areas from the strict regulations. Especially, sales patterns and distribution channels are the areas where most barriers emerge in this sector. Hence, this study mainly aims to reveal the barriers confronting sales & distribution processes of the agrochemical industry and analyze them to display the causal relationship amidst barriers and prioritize them to focus on them to overcome them in further stages. In this context, with the help of specialists, a focus group discussion was held to determine the most important and pertinent barriers to the sales and distribution operations. Found barriers were analyzed through The Decision-Making and Evaluation Laboratory (DEMATEL) method, which divides the interacting parts of a system into cause-and-effect groups as a structural modeling approach.

The apparel industry is challenging for production management due to rapid changes in fashion. Accordingly, customer needs and expectations increase constantly. As a result, apparel factories must be able to increase production rate, efficiency, and quality in order to survive in this dynamic world. To this end, assembly line balancing, which affects the overall cost and efficiency in apparel industry, plays a critical role. In this study, real-life assembly line balancing and competency-based worker assignment problems in apparel industry sewing workshop are examined simultaneously and implementation at a big apparel company is presented. A novel mathematical model is proposed to solve this integrated problem. Operation-worker and operation-workstation assignments are made for a given number of workstations, operations, and workers. The competency score of the worker on each machine type is a key factor in determining worker-operation assignment. Assignments are made in such a way that the total competency score of the line must exceed a pre-specified limit. The objective is to minimize the workload difference between workers on the assembly line for a given cycle time limit. The proposed model is solved using Google OR-Tools and is verified using real-life data from the company. Since the competency of the workers is crucial in operations based on manual labor, the proposed model can also be adapted to many industries in addition to the apparel industry.

Course scheduling and classroom assignment problem is a common problem for all educational fields. It is an NP Hard problem. Especially, universities should handle this problem while preparing course timetabling for each level due to elective courses and students taking upper/lower-level courses. There is a vast literature on this problem both for modelling and solution approaches. Although the essence of the problems is similar for the most, each problem has some unique restriction and/or parameters. We study the timetabling of the courses of Industrial Engineering program at Yaşar University. We develop a mathematical model to maximize the minimum lecturer satisfaction. Due to the computational complexity of the problem, we proposed a heuristic solution method, namely the Genetic Algorithm. Gene structure we use ensures the feasibility of many constraints of the mathematical model. Computational results of optimal and heuristic method are compared. As a real-life implementation, a university in Turkey Industrial Engineering Department data is used and results were reported.

This study aims to optimize the cut-off dates in liner shipping to speed up the shipping process and allow customers to send their goods on time. This study contributes to the literature by assisting in determining the cut-off optimization in the liner shipping problem. Many explanatory variables have a positive effect, resulting in the uncertainty of cut-off optimization in shipping. However, there are apparent differences in cut-off dates across the shipping regions studied worldwide. The Arena Simulation Software was used to conduct this research. A flowchart was generated in line with the information provided by a liner operator to minimize all process times, including the waiting time of the ship in port, to estimate the best cut-off date for all processes. Then, OptQuest, an extension of the Arena software, was used to optimize the simulation scenarios.

This study solves a one-dimensional cutting stock problem with multiple stock lengths. It is applied in a manufacturing setting where rolls of steel rods of different lengths are cut according to customer requirements. The one-dimensional cutting stock problem (CSP) is an NP-hard problem, including discrete demands and capacitated planning objectives. It is solved using column generation techniques. This study aims to develop a production plan that minimizes the waste of cutting steel rods of different lengths and diameters in required lengths. The approach to solving the problem has two steps. The first step is a heuristic algorithm that produces a cutting pattern at every iteration, which is then fed into a novel mathematical model to determine an optimal solution. An initial solution is obtained using randomly generated cutting patterns for the mathematical model. The algorithm terminates after a given number of iterations. The paper also proposes a Decision Support System, addresses application issues, and concludes with further studies.

Forecasting customer demand for preliminary products in an accurate way plays a vital role in increasing efficiency of inventory control systems, reducing total costs and meeting the requirements of customers on time. Considering this fact, the chief objective of the study is to develop a user-friendly decision support system (DSS) to be able to forecast demand for products and minimize the cost of total inventory control costs including ordering and holding costs. Due to the complexity of the problem of this study, the project is handled in two parts, namely, demand forecasting and inventory management. In the demand forecasting part, unlike the traditional methods which mostly ignore the statistical behaviour of demand distribution of products, we employed Holt-Winters and SARIMA techniques which minimize the error of forecasting by harnessing demand behaviour. In the second part, the forecasted demand values are used as inputs for the inventory control system. In this part, we developed a Mixed Integer Programming Model (MIP) where the total inventory cost, involving ordering and holding costs, is to be minimized. To solve the proposed mathematical model, IBM CPLEX OPTIMIZER coupled with Branch & Bound Algorithm (B&B) is employed. In addition to this exact solution technique, we also used the Benders Decomposition method which is suitable to solve MIP models in a more reasonable computational time with optimality, by decomposing the model into master and sub-problem. Besides these two exact-solution techniques, to determine the number of products to be ordered from a supplier in a shorter computational time when the problem size is larger, a heuristic solution was developed, adapted from the Silver Meal algorithm. The results obtained using the aforementioned techniques are compared concerning their solution quality and computational time.

The retail industry is a large service platform where national and international manufacturers bring their products to consumers. Today, the retail sector, both bricks-and-mortar and online, is developing and adapting to the changing needs of the customers. Depending on the changing demand patterns of the customers, one can notice that key success criteria of the sector transform as well. Rapid adaptation to changing requirements of the retail sector is necessary in order to survive in the increased competition and to increase the market share among the other companies. In order to analyze the sector in Turkey, retail brands that are selected from the largest 500 companies of Turkey (Capital 500 list) were examined using the relevant success criteria. Key success factors have been chosen from the existing literature about the retail sector. Firstly, retailing was examined in a theoretical framework to better undersand the elements that define the sector alongside technological capabilities of the sector. Additionally the effects of Covid-19 on e-retailing were also evaluated with the purpose of determining the changes forced upon the sector by the pandemic.. In the light of the findings, the emerging companies, observed changes and directional shifts, and the size of the competition in Turkish retailing sector are discussed. Success criteria were chosen from the existing literature, and were weighted in accordance with importance ranks obtained through content analysis. Considering success criteria, DEA analysis has been carried out and the efficiency level of the companies has been evaluated.

Technological innovations and the variety of customers’ requirements have increased competitiveness lately. Facility layout design also became critical for gaining a competitive advantage in terms of service time and operational efficiencies. A facility layout design is a term used to describe the process of arranging sections and distributing them in a facility. Inappropriate facility layout design causes cost and time waste in organizations. As a result,; this research created an implementation for a container cleaning firm with facility layout design issues. This research aims to identify factors influencing facility layout planning through decision-making methodologies, redesign the company's warehouse plan, and select the optimum warehouse placement. In-warehouse layout design methodologies will be employed to achieve an optimal in-warehouse settlement. SWARA (Step-wise Weight Assessment Ratio Analysis), a method for formulating multi-criteria decisions, was used first and foremost. Then, using BLOCPLAN, one of the heuristic improvement methodologies, a new layout was given based on the information received from the firm. The improvement obtained as a result of the suggested new settlement was detected aafter the investigation, and it was observed that it delivered better results.

In this paper, a real-life parallel machine scheduling problem with sequence-dependent setup times of an industrial-type electrical equipment manufacturing company is addressed. The objective of this study is to find a solution method to achieve an effective and systematic schedule that minimizes the total weighted tardiness in the system by considering some properties related to the jobs and machines. These properties are the priority rank of jobs, sequence-dependent setup times between jobs, machine eligibility, and machine availability. Initially, a mathematical model is proposed for the problem. The solving performance of the proposed model by LINGO is tested with randomly generated toy problems. Since the problem has NP-hard characteristics, heuristic algorithms based on the EDD rule and GTW algorithm are developed to obtain optimal or near-optimal schedules in an acceptable period of time. The success of the algorithms is tested through generated toy problems. It is observed that the combination of Modified EDD and HENOBA algorithms gives optimal or near-optimal solutions. Lastly, an efficient and user-friendly decision support system (DSS) is created.

Effective inventory management enables us to meet customer demand by ensuring the delivery of the right products that customers need on time. Likewise, the correct design of the supply chain contributes to the effectiveness of stock management. Companies increase customer satisfaction by making effective stock planning. A petroleum company which located in Izmir also aims at accurate and effective stock management. The company decides to determine the product variety and product quantity that should be in the stocks of the micro warehouses to be established in 5 different regions. In this study our objectives are (i) to identify which product should be stored at each micro depot based on the demand forecasting model we develop, (ii) to allocate storage capacities to the products, (iii) to determine ordering instances, and (iv) to conduct an optimal aggregate transportation plan with the given fleet size of different vehicles. The most demanded products for each region were determined by performing ABC analysis with 2 criteria. Since the products selected according to the ABC analysis will be transported to the micro warehouses by 3 different types of vehicles, a transportation planning model has been constructed. In order to decide on the ordering policy of the specified products in the micro warehouses, 2 different dynamic simulation models were created on a unit basis and on a pallet basis by using the Arena Simulation program with the objective of satisfying a certain service level.

Nowadays, sustainability has become a critical issue aiming to achieve social, environmental, and economic goals simultaneously. Sustainability should be adopted for all production processes, especially the product design phase. Since product design provides a significant difference between firms which has led to gaining strategic advantage. Therefore, this study investigates the customer requirements and technical properties of designing sustainable beverage packaging. The Quality Function Deployment tool evaluates the importance of proposed customer requirements and technical properties. The Quality Function Deployment technique is crucial to make sustainable improvements in the design stage. This paper is provided various suggestions to industry for creating sustainable beverage packaging design.

Although women's cooperatives have been taken attention in recent years, they are not managed efficiently. Recently, women's cooperatives mostly encountered problems while delivering their products to the end consumer. For this reason, collection center planning should be done for women's cooperatives. The study seeks to determine the essential criteria for choosing a collection center location for women's cooperatives in Turkey and to highlight which criterion is more important. In line with this study, it is aimed to find a solution to the problems of women cooperatives in the distribution stage by exchanging information with Tabit company, which is a social initiative company and the company's goals are to meet the demands of rural residents and those based on agricultural production. In this study, AHP is used to determine the most important and least important criteria for location selection of collection centers. 11 criteria are determined based on literature review and six experts are completed to AHP implementation. As a result, based on the data values of the experts in the AHP method, it was determined that the least important criterion was infrastructure and the most important criterion was proximity.