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This study integrates the Lean Six Sigma (LSS) DMAIC (design, measure, analyze, improve, control) methodology with the Life Cycle and Value Stream Level of RAMI 4.0 by proposing a systematic structure that includes LSS 4.0 tools and techniques for each level. The fuzzy Entropy Weighting method is used to evaluate LSS 4.0 tools and techniques for each level, and a sample implementation of the proposed structure is conducted in a high-technology electronics firm. The results indicated that the proposed structure effectively integrates the LSS and DMAIC methodology with the Life Cycle and Value Stream Level of RAMI 4.0. The results suggest that although the DMAIC methodology is applicable for each life cycle stage, the most important approaches vary for each life cycle level. Therefore, DMAIC implementation for each level should be conducted separately for each life cycle and LSS 4.0 tools and techniques should be chosen according to the specific needs. This article proposes a novel systematic structure that includes LSS 4.0 tools and techniques for each DMAIC stage and that can be used for LSS implementation in RAMI 4.0. The proposed structure will contribute to systemizing the complex structure of Industry 4.0 in the implementation phase of smart factories. [ABSTRACT FROM AUTHOR]

Operating with fixed schedules requires coordinating and cooperating with many actors in liner shipping. Therefore, liner operators announce predetermined cut-off dates for each voyage for Sippers to perform cargo-related transactions and send their documents. The shippers complain that the cut-off times are primarily for the operator's benefit and create a very tight time. However, the operators have trouble that the shippers cannot fulfill the necessary instructions and documents on time. From this point of view, this study aims to offer optimized cut-off determination for liner services and employs a mixed-method approach to evaluate the cut-off process of liner operators. Firstly, a qualitative study was conducted to obtain factors affecting cut-off date determination. Second, the factors affecting cut-off dates were analyzed with the fuzzy Total Interpretive Structural Modelling (TISM) method. Third, a step-by-step shipping process from booking to the vessel's departure was developed. Moreover, the simulation method was applied with actual data to offer alternative schedules for a liner operator for its two liner services. The results show that even using only the two strongest driving factors determined in the TISM process (TEU capacity of the vessel and number of port calls) improves the cut-off determination simulation performance results by 20%. [ABSTRACT FROM AUTHOR]

Transition from a linear to a circular economy (CE) is a challenging process for a sustainable supply chain, and innovative process approaches and technologies are needed to deal with the risks involved. Industry 4.0 principles have great potential to achieve optimal sustainable supply chain solutions and are expected to add value to sustainable supply chain operations by increasing efficiency and resource utilisation. Therefore, Industry 4.0 supports companies transitioning to a CE through improving the efficiency and sustainability of their supply chain management. Thus, the purpose of this paper is to investigate the potential risks of the transition from a linear to a CE, with proposed Industry 4.0-based responses from an operations management perspective within the sustainable supply chain. Implementation of the study was conducted in a logistics company in Turkey. An integrated MCDM (Multi-criteria Decision Making) approach was based on Fuzzy AHP, and TODIM was used to analyse the association between risks and responses. According to the findings, the most important Industry 4.0-based responses are the integrated business processes for cross-functional collaboration, modular processes for simplification and standardisation, and continuous monitoring of the cost and performance throughout the supply chain by big data and analytics. This study may assist managers in managing risks in supply chain operations during the transition from a linear to a CE through Industry 4.0 based responses. The main contribution of this study is a greater understanding of the risks related to the transition from a linear to a circular economy, and proposals for Industry 4.0-based responses as a means of overcoming these risks in a sustainable supply chain context. [ABSTRACT FROM AUTHOR]

Purpose: Research and Development (R&D) and innovation activities critically impact an organization's development and competitive advantage. Although all industries have R&D and innovation activities, sectoral applications vary depending on readiness, investment opportunities, and organizational strategies. This study focuses on the automotive, textile, and main metal industries, with the highest export rates in Türkiye. This study aims to analyze R&D and innovation activities for the selected industries and provide practitioners with future insights. Methodology: Six different R&D and innovation indicators, i.e., current expenditure, personnel expenditures, trade investments, number of patent applications and number of R&D personnel, are considered for this study, and the GM (1,1) forecasting model is used to predict 2022-2030. Findings: As a result, although an increase in R&D and innovation activities in the automotive industry is expected, especially for each indicator, these values are limited for textile and main metal. It is realized that especially these two industries need more support. Originality: Within the scope of this study, future insights and suggestions are given under digitalization and technology adoption, encouraging postgraduate studies of employees and higher education - industry collaborations, adopting R&D and innovation as a part of corporate culture, extending R&D and innovation incentives, supporting SMEs in R&D and innovation activities according to sectoral comparisons.