451 research outputs found
A New Evaluation Model For The Readiness And Maturity Level Of Intelligent And Sustainable Supply Chain Management Based On Geometric Mean
No full textJournal of Transportation and Logistics[TR-EN] Journal of Transportation and LogisticsJournal of Transportation and LogisticsSon yıllarda küreselleşme ve küresel rekabetteki artış, artan teknolojik büyüme hızı, müşteri taleplerindeki çeşitlilik ve tedarik zinciri süreçlerinin giderek karmaşıklaşması firmaların tedarik zinciri stratejilerine akıllı ve sürdürülebilir paradigmalar eklemelerine neden olmuştur. Tedarik zinciri oyuncuları arasındaki gerçek zamanlı bilgi paylaşımı ve zincirin her bir basamağının etkin koordinasyonu, tedarik zincirinin verimli şekilde yönetimi için önemli rol oynamaktadır. Bu da geleneksel tedarik zincirinden dijital tedarik zincirine dönüşüm ile mümkündür. Endüstri 4.0 olarak adlandırılan ve 2011 yılında Almanya’da doğan Dördüncü Sanayi Devrimi bilgi teknolojileri, nesnelerin interneti, yapay zeka, bulut bilişim teknolojisi, otonom araçlar, robotik sistemler, sensor ve otomasyon ağları, sanal ve arttırılmış gerçeklik gibi teknolojilerin üretim süreçlerine yoğun biçimde entegrasyonunu hedef alan yenilikçi bir paradigmadır. Ne var ki, Endüstri 4.0’a uyum ve uyum sonrası olgunluk dönemi birçok firma için beklenmedik problemlere yol açabilmektedir. Akıllı fabrikaların kurulmasında ve dijital dönüşümün uygulanmasında en büyük sorunlardan biri, Endüstri 4.0 yetkinliklerinin tüm operasyonlara eş zamanlı olarak etkin şekilde uygulanamamasıdır. Bu bağlamda, firmaların Endüstri 4.0’a hazırlık ve uyum sonrası olgunluk düzeylerinin niceliksel ölçümü ve değerlendirilmesi, üst yönetim için büyük önem arz etmektedir. Bu çalışmanın amacı firmaların Endüstri 4.0’a hazırlık ve olgunluk düzeylerinin daha iyi anlaşılıp ölçülebilmesi için, dijital tedarik zincirlerinin akıllı ve sürdürülebilir boyutta olgunluk düzeylerinin eş zamanlı ölçülebilmesine olanak sağlayan bir model önermektir. Modelin uygulandığı nümerik örnekte, her bir Endüstri 4.0 aracının sürdürülebilirlik boyutlarına ne derece uyum sağladığı belirlenmiştir. Örneğin, eklemeli imalat ve arttırılmış gerçeklik sürdürülebilirliğin ekonomik boyutunda yüksek olgunluk skoru alırken, çevresel ve sosyal boyutlara göre daha düşük skor almıştır. Benzer şekilde, yapay ve dikey sistem entegrasyonu her üç boyut için yüksek olgunluk seviyesinde iken, yapay zeka çok düşük olgunluk seviyesinde kalmıştır.Recently, companies have added smart and sustainable paradigms to their supply chain strategies as a result of globalization and increased global competition, increasing technological growth rate, diversity in customer demands, and increasing complexity in supply chain processes. Real-time information sharing among supply chain players and the effective coordination of each step of the chain are critical for efficient supply chain management. This is made possible by the transition from the traditional supply chain to the digital supply chain. The Fourth Industrial Revolution, also known as Industry 4.0, was coined for the first time in Germany in 2011. It is an innovative paradigm with the goal of intensely integrating technologies, such as information technologies, the Internet of Things, artificial intelligence, cloud computing technology, autonomous vehicles, robotic systems, sensor and automation networks, and virtual and augmented reality into production processes. However, for many companies, the adaptation of Industry 4.0 and the subsequent maturity period may present unexpected challenges. One of the most difficult challenges in establishing smart factories and implementing digital transformation is that Industry 4.0 competencies cannot be effectively applied to all operations simultaneously. In this context, quantitative measurement and evaluation of firms’ maturity levels following Industry 4.0 preparation and adaptation is critical for senior management. The goal of this study is to propose a model for measuring the maturity level of digital supply chains while considering smart and sustainable dimensions. We determined the extent to which each Industry 4.0 tool was compatible with the sustainability dimensions in the numerical example where the model was applied. For example, although additive manufacturing and augmented reality receive high scores in the economic dimension of sustainability, they receive lower scores in the environmental and social dimensions. Similarly, although horizontal and vertical systems integration has high levels of maturity in all three sustainability dimensions, artificial intelligence has an exceptionally low level of maturity
Allied Closed-Loop Supply Chain Network Optimization with Interactive Fuzzy Programming Approach
No full textThe concept of closed-loop supply chain (CLSC) has started to attract growing attention due to the consumer pressures, environmental awareness, and legislations. Managers in many companies have realized that a well-designed supply chain (SC) can improve the companies' performance in the market. Thus, a lot of companies start to focus on CLSC issues including remanufacturing, refurbishing, recycling, and disposal of end-of-life products. The body of literature on CLSC management has been overwhelmingly dominated by noncooperative studies. In order to fill up this gap in the literature, we deal with an allied SC network in cooperative environment. With the implementation of allied SCs, companies not only maximize their profit but also minimize their various costs and become more flexible and efficient in the market. Following this motivation, we develop a decentralized multilevel CLSC model for allied SCs. At the first decision level, the plants in allied SCs are considered as the upper-level DMs of the Stackelberg game. At the second level, raw material suppliers, common suppliers, assembly centers, and common collection centers are considered as the lower-level DMs of the Stackelberg game. In order to tackle each decision-maker (DM)'s unique objectives, we propose a new fuzzy analytic hierarchy process (AHP)-based interactive fuzzy programming (IFP) approach. In the IFP approach, upper-level DMs determine the minimum satisfactory level for their own objectives, and by using this value, the lower DMs evaluate their own satisfactory level. A compromise solution can be derived until termination conditions are satisfied. The primary aim of this study is to design a decentralized CLSC network in cooperative environment and to propose a novel IFP approach. Finally, a numerical example is implemented and analyzed in order to demonstrate the efficiency of the proposed approach
Readiness and maturity of smart and sustainable supply chains: a model proposal
Get PDFMany companies embrace Industry 4.0 technologies to enable operational sustainability against increasing climate change effects, decreasing natural resources, and raising consumer awareness of environmental issues. Even though readiness and maturity assessment of smartness and sustainability concepts are nested, no study simultaneously focuses on these concepts. As pioneering research, we propose a novel model titled “Smart and Sustainable Supply chain Readiness and Maturity model (S3RM)” and validate it by conducting a case study in the automotive industry. We design our model upon the triple-bottom-line (TBL) approach consisting of smartness and sustainability dime5nsions. Our study introduces the TBL of smartness covering availability, integrity, and adaptability sub-dimension. TBL of sustainability includes social, environmental, and economic sub-dimensions. The proposed model calculates the Smart and Sustainable Readiness and Maturity Index by averaging sustainability scores’ summation and smartness scores’ multiplication. Each sub-dimension consists of items measured by a readiness and maturity scale. The findings suggest how smartness and sustainability items create strengths, weaknesses, opportunities, and threats for the supply chain operations. Our model provides managerial implications in assessing the readiness and maturity of Industry 4.0 tools and sustainability indicators. This study offers a road map to managers on smart and sustainable supply chains’ defined target areas
An empirical investigation of Advanced Manufacturing Technology investment patterns: evidence from a developing country
Get PDFAdvanced manufacturing technology (AMT) investment patterns in developing countries is in need of further investigation, particularly in the light of the conflicting evidence from the literature. This paper provides new evidence on AMT investment patterns from the Turkish automotive industry and develops a taxonomy by exploring the relationships between AMT investment patterns, ownership structure, firm size and performance. Analysis of industry survey data suggests the existence of three groups with different AMT investment strategies. Results suggest that AMT investment patterns are not only significantly correlated with firm performance or ownership, but also reveals significant differences in manufacturing performance across investment patterns. (C) 2013 Elsevier B.V. All rights reserved.Selcuk University Scientific Research Project Fund (BAP)Thanks are due to two reviewers for their valuable comments. In carrying out this research, the third author has been supported by the Selcuk University Scientific Research Project Fund (BAP)
Operational and environmental performance measures in a multi-product closed-loop supply chain
No full textThis paper investigates a number of operational and environmental performance measures, in particular those related to transportation operations, within a closed-loop supply chain. A mathematical model in the form of a linear programming formulation is used to model the problem, which captures the trade-offs between various costs, including those of emissions and of transporting commodities within the chain. Computational results are presented for a number of scenarios, using a realistic network instance.<br/
Multi-level optimization of an automotive closed-loop supply chain network with interactive fuzzy programming approaches
Get PDFClosed-Loop Supply Chain (CLSC) management has attained appreciable attention over the last few years. CLSC management allows companies to manage their recovery and recycling activities of end products. Due to the latest developments in the world, producers are responsible for the collection, refurbishing, repairing and disassembly of end products at the end of their lives. This paper develops a mixed-integer CLSC model that is inspired by the automotive industry. In this model, we consider three Decision Makers (DM): Plant, Dismantler Center and Customer. Each DM has individual objectives and is responsible for only its own objective function under same constraints. In order to tackle the trade-offs among the objectives, we used four different Interac-tive Fuzzy Programming (IFP) approaches. The applications of the model and solution techniques are investigated in conjectural data. The paper ends with a conclusion and a call for future studies
A Comparison of Islamic Vs Conventional Banks in Turkey
No full text##nofulltext##Semen Son Turan (MEF Author)..
Operations Strategy
No full textAmong the areas of operations management (OM) research, the results of work done to identify which themes are the most prevalent in this particular area point to operations strategy (OS) as the most prominent theme. Operations strategy is the collective tangible movements decided, ordered, or inspired utilizing the corporate approach. The operations department is responsible for overseeing both the strategic and daily production of goods and services. In the settings of production, manufacturing, or service supply, operations management is largely concerned with planning, coordinating, and overseeing. Despite the fact that strategy and structure in organizations are distinct, they are strongly connected, particularly in operations management. Indeed, operations strategy can be defined as the interaction between a firm’s strategic direction
Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing
No full textThis paper describes an integrated model that jointly optimizes the strategic and tactical decisions of a closed-loop supply chain (CLSC). The strategic level decisions relate to the amounts of goods flowing on the forward and reverse chains. The tactical level decisions concern balancing disassembly lines in the reverse chain. The objective is to minimize costs of transportation, purchasing, refurbishing, and operating the disassembly workstations. A nonlinear mixed integer programming formulation is described for the problem. Numerical examples are presented using the proposed model
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