Browsing by Author "Yetkin Ekren, Banu"

Now showing 1 - 7 of 7
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    Additive manufacturing integration in E-commerce supply chain network to improve resilience and competitiveness
    (Elsevier, 2022-10-27) Yetkin Ekren, Banu; Stylos, Nikolaos; Zwiegelaar, Jeremy; Eroğlu Turhanlar, Ecem; Kumar, Vikas
    In light of recently increased e-commerce, also a result of the COVID-19 pandemic, this study examines how additive manufacturing (AM) can contribute to e-commerce supply chain network resilience, profitability and competitiveness. With the recent competitive supply chain challenges, companies aim to decrease cost performance metrics and increase responsiveness. In this work, we aim to establish utilisation policies for AM in a supply chain network so that companies can simultaneously improve their total network cost and response time performance metrics. We propose three different utilisation policies, i.e. reactive, proactive – both with 3D printing support – and a policy excluding AM usage in the system. A simulation optimisation process for 136 experiments under various input design factors for an (s, S) inventory control policy is carried out. We also completed a statistical analysis to identify significant factors (i.e. AM, holding cost, lead time, response time, demand amount, etc.) affecting the performance of the studied retailer supply chain. Results show that utilising AM in such a network can prove beneficial, and where the reactive policy contributes significantly to the network performance metrics. Practically, this work has important managerial implications in defining the most appropriate policies to achieve optimisation of supply network operations and resilience with the aid of AM, especially in times of turbulence and uncertainty.
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    Adopting Industry 4.0 by leveraging organisational factors
    (Elsevier, 2021-12-21) Kumar Srivastava, Deepak; Kumar, Vikas; Yetkin Ekren, Banu; Upadhyay, Arvind; Tyagi, Mrinal; Kumari, Archana
    The manufacturing sector needs to focus on social, environmental and technological factors to integrate Industry 4.0 in production planning, logistics and supply chains. Technical Education Institutes (TEIs) can play a key role in achieving this ambition as they are responsible for the workforce of the digital future. To this end, a learning factory is often referred to as a realistic manufacturing environment. However, the existing research regarding the successful adoption of a learning factory based on Industry 4.0 is scant in the literature. We, therefore, aim to address this research gap by examining key factors that affect the decision to adopt Industry 4.0 in technical education institutes. We have adopted the theoretical lens of the Technology-Organisation-Environment (T-O-E) framework to study industry 4.0 adoption in TEIs. The findings based on 134 valid responses from TEIs in India indicate that the organisational dimension is critical in determining whether or not to adopt Industry 4.0. Our study shows that top management support, internal resources, and the capabilities of the teaching staff are vital for the adoption of Industry 4.0. Additionally, our findings indicate that significant differences exist between public and private TEIs concerning the adoption of Industry 4.0.
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    Assessing the impact of COVID-19 on sustainable food supply chains
    (MDPI, 2021-12-23) Kazancoglu, Yigit; Ozbiltekin-Pala, Melisa; Deniz Sezer, Muruvvet; Yetkin Ekren, Banu; Kumar, Vikas
    Recently, it has become an important issue to ensure sustainability, especially in food supply chains, against the rapidly growing population, increasing demand, and sudden disruptions caused by uncertain times such as that caused by COVID-19. Since food supply chains has vulnerable products and processes, it is critical to understand the sustainability factors of food supply chains especially in uncertain times such during the COVID-19 pandemic. This study aims to determine sustainability factors of food supply chains. An Interpretive Structural Modelling method is used to state the relations between sustainability factors of food supply chains. As a result of the study, Information Sharing and Managerial Approaches are classified as driving factors; Food Safety and Security, Know-How Transfer, Logistics Networking, Risk Mitigation, Employee Commitment, Innovation, Traceability and Responsiveness are categorized as linkage factors. This article will be beneficial for managers in helping them develop sustainable food supply chains during uncertain times by focusing on traceability, information sharing, know-how transfer, food safety and security.
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    Autonomous mobile robot travel under deadlock and collision prevention algorithms by agent-based modelling in warehouses
    (Taylor and Francis, 2022-10-31) Eroglu Turhanlar, Ecem; Yetkin Ekren, Banu; Lerher, Tone
    Recent dramatic increase in e-commerce has also increased the adoption of automation technologies in warehouses. Autonomous mobile robots (AMRs) are from those technologies widely utilized in warehouse operations. It is important to design the operation of those robotic systems in such a way that, they meet the current and future system requirements correctly. In this paper, we study flexible travel of AMRs in warehouses by developing smart deadlock and collision prevention algorithms on agent-based modelling. By that, AMR agents can interact with each other and environment, so that they can make smart decisions maximizing their goals. We compare the performance of the developed flexible travel system with non-flexible designs where there is a single AMR dedicated to a specific zone so that no deadlock or collision possibility takes place. The results show that AMRs may provide up to 39% improvement in the flexible system compared to its non-flexible design.
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    Investigating the impact of COVID-19 on sustainable food supply chains
    (Emerald, 2022-10-20) Kumar, Vikas; Yetkin Ekren, Banu; Wang, Jiayan; Shah, Bhavin; Frederico, Guilherme Francisco
    Purpose- The ongoing pandemic has gravely affected different facets of society and economic trades worldwide. During the outbreak, most manufacturing and service sectors were closed across the globe except for essential commodities such as food and medicines. Consequently, recent literature has focused on studying supply chain resilience and sustainability in different pandemic contexts. This research adds to the existing literature by exploring the economic, environmental and societal aspects affecting the food supply chain and assessing the impact of COVID-19 on food sustainability. Design/methodology/approach- A survey method has been adopted with a questionnaire instrument investigating the role of technology, government policies, geopolitics and intermediaries on sustainable organisational management. A five-point Likert scale (i.e., 1: strongly disagree; 5: strongly agree) is used to evaluate the responses. The findings are based on 131 responses from entry-level workers and senior executives of different food supply chains across Asia and Europe. The data has been analysed to derive insights into the impacts of this pandemic. Findings- The survey concludes with the significant impact of COVID-19 on the three pillars of sustainability, i.e. economic, social, and environmental dimensions. The empirical analysis shows digitalization and its applications help mitigate the negative effect of COVID-19 on sustainability. In addition, the supportive government policies and intermediatory interventions were helpful in improving sustainability at each level. Social/Research/Practical Implications- The findings have implications for businesses and policymakers. Companies can learn from the advantages of digitalization to counter the challenges imposed by the pandemic or similar situations in the future in maintaining the sustainability of their supply chains. Managers can also learn the importance of effective organisational management in driving sustainability. Finally, policymakers can devise policies to support businesses in adopting sustainable practices in their supply chains. Originality/value- Our study adds to the limited literature exploring the impact of COVID-19 on food supply chain sustainability through the Triple Bottom Line (TBL) lens. This is also one of the first empirical studies to examine the effect of technology, government and organisational management practices on the sustainability of food supply chains.
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    Multi-objective inventory optimization problem for a sustainable food supply network under lateral inventory share policy
    (Elsevier, 2022-10-26) Yetkin Ekren, Banu; Chattopadhyay, Ritwika; Kumar, Vikas
    This study dives deep into a lateral supply chain network for perishable food products and aims to determine optimal re-order and order up to levels for multiple e-groceries within a common network using a simulation-based optimization technique. The algorithm aims to minimize the average inventory carried within the network while accounting for parameters like reduced wastage, improved customer satisfaction level, and a limited number of replenishments.
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    Transaction selection policy in tier-to-tier SBSRS by using deep q-learning
    (Taylor and Francis, 2022-11-30) Arslan, Bartu; Yetkin Ekren, Banu
    This paper studies a Deep Q-Learning (DQL) method for transaction sequencing problems in an automated warehousing system, Shuttle-based Storage and Retrieval System (SBSRS), in which shuttles can move between tiers flexibly. Here, the system is referred to as tier-to-tier SBSRS (t-SBSRS), developed as an alternative design to tier-captive SBSRS (c-SBSRS). By the flexible travel of shuttles between tiers in t-SBSRS, the number of shuttles in the system may be reduced compared to its simulant c-SBSRS design. The flexible travel of shuttles makes the operation decisions more complex in that system, motivating us to explore whether integration of a machine learning approach would help to improve the system performance. We apply the DQL method for the transaction selection of shuttles in the system to attain process time advantage. The outcomes of the DQN are confronted with the well-applied heuristic approaches: first-come-first-serve (FIFO) and shortest process time (SPT) rules under different racking and numbers of shuttles scenarios. The results show that DQL outperforms the FIFO and SPT rules promising for the future of smart industry applications. Especially, compared to the well-applied SPT rule in industries, DQL improves the average cycle time per transaction by roughly 43% on average.