The present research proposes a roadmap to the excellence of operations for sustainable reverse supply chain/logistics by the joint implementation of principles of Industry 4.0 (I4.0) and ReSOLVE model of circular economy (CE) approaches. The connection between I4.0 and CE is unveiled by addressing the case-based model affecting the economic and environmental performances imparting two important dimensions: (i) the information sharing with the reverse logistics system is in real-time mode, and (ii) diffusion of green product in the market. The effectiveness of the virtual world in I4.0 environment is explored using simulation of reverse logistics model involving operations such as inventory and production planning policy, family-based dispatching rules of remanufacturing, and additive manufacturing. The remanufacturing model examines the trade-off between set-up delays and the availability of green transportation. For managerial insights, Taguchi experimental design framework has been used for the analysis. Based on the trade-off analysis between environmental and economic performances, the findings of the paper suggest appropriate combinations of information-sharing and family-based dispatching rules. Further, the findings suggest that, given the I4.0 and circular capabilities, it is necessary to focus on the cost of the socially influenced operations involving factors such as collection investment and size of the end-user market that governs the product returns. Therefore, in the present paper, the integration of I4.0 and CE represents a real-time decision model for the sustainable reverse logistics system.
Newcastle University ePrints -eprint.ncl.ac.uk Dev NK, Shankar R, Gupta R, Dong JX. Multi-criteria evaluation of real-time key performance indicators of supply chain with consideration of big data architecture. Computers and Industrial Engineering 2018. AbstractOne of the major issues a designer of Big Data Architecture has to trade with is incorporating real-time predictive analytics capability using offline synergistic approaches like simulation, fuzzy analytic network process, and Technique for Order Preference. Further, under this setting, which involves re-engineering of operational units, the present study proposes a simple, yet practical heuristic to quickly handle the unstructured relational key-performance-indicators (KPIs) data of a supply chain that are obtained from the results of the simulation. Within the big data framework, the proposed model can be used as a decision support tool by the companies to evaluate their KPIs in a real-time dynamic system.
Purpose – The modern business community understands the importance of long-term satisfaction of consumer. Enabling the consumer to return products is a significant part of the equation. The purpose of this paper is to analyze the sustainable boundaries in terms of their relationship toward greening a supply chain. Design/methodology/approach – Using interpretive structural modeling the research presents a hierarchy-based model to realize the driving power and dependence of sustainable boundary enablers. Findings – The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions. Practical implications – This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus while making strategic, tactical or operational decisions as and when required while designing a green supply chain. Originality/value – This research assumes importance in context of greening a supply chain when globally enterprises are getting a lot of pressure from consumers as well as the regulatory measures from the government. Sustainability demands that the resources be used in lean manner through information coordination with all partners in a supply chain. The findings of this study would help delineate those variables that should to be necessarily considered to design a sustainable supply chain.
. Strategic design for inventory and production planning in closed-loop hybrid systems.International Journal of Production Economics, 183, Part B, Additional Information:• This paper was accepted for publication in the journal International Journal of Production Economics and the definitive published version is avail- HighlightsA closed-loop system with both manufacturing and remanufacturing is considered.Studied inventory and production planning models for continuous and periodic review.Total inventory costs and production order variance are performance indicators.Total inventory cost shows trade-off among demand, lead times, and review periods.Remanufacturing shows its contribution to low order variance in periodic review. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 1 Highlights (for review) Strategic design for inventory and production planning in closed-loop hybrid systems AbstractThis research studies inventory and production planning in a closed-loop system while considering both manufacturing and remanufacturing. We studied five inventory and production planning models under the continuous and periodic review systems using a discrete event simulation. Under the above review policies, different demand and return rates, as well as manufacturing and remanufacturing lead times, are considered. The total recoverable and serviceable inventory costs and production order variance are considered as the main performance indicators. From the total inventory cost viewpoint, our findings reveal the trade-off between stochastic demand, stochastic lead times, and review periods. It was found that the periodic review system outperforms the continuous review system for higher values of the review period and return to demand rate ratio. Furthermore, remanufacturing demonstrates an appreciable contribution to low order variance in periodic review systems for high values of return to demand ratio and lead times.
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