Search Results for « Supply Chain Management »

While consolidation strategies form the backbone of many supply chain optimisation problems, exploitation of multi-tier material relationships through consolidation remains an understudied area, despite being a prominent feature of industries that produce complex made-to-order products. In this paper, we propose an optimisation framework for exploiting multi-to-multi relationship between tiers of a supply chain. The resulting formulation is flexible such that quantity discounts, inventory holding, and transport costs can be included. The framework introduces a new trade-off between tiers, leading to cost reductions in one tier but increased costs in the other, which helps to reduce the overall procurement cost in the supply chain. A mixed integer linear programming model is developed and tested with a range of small to large-scale test problems from aerospace manufacturing. Our comparison to benchmark results shows that there is indeed a cost trade-off between two tiers, and that its reduction can be achieved using a holistic approach to reconfiguration. Costs are decreased when second tier fixed ordering costs and the number of machining options increase. Consolidation results in reduced inventory holding costs in all scenarios. Several secondary effects such as simplified supplier selection may also be observed.

Most of the theories that have dominated supply chain management (SCM) take a reductionist and static view on the supply chain and its management, promoting a global hunt for cheap labor and resources. As a result, supply chains tend to be operated without much concern for their broader contextual environment. This perspective overlooks that supply chains have become both vulnerable and harmful systems. Recent and ongoing crises have emphasized that the structures and processes of supply chains are fluid and interwoven with political‐economic and planetary phenomena. Building on panarchy theory, this article reinterprets the supply chain as a social–ecological system and leaves behind a modernist view of SCM, replacing it with a more contemporary vision of “dancing the supply chain.” A panarchy is a structure of adaptive cycles that are linked across different levels on scales of time, space, and meaning. It represents the world’s complexities more effectively than reductionist and static theories ever could, providing the basis for transformative SCM.

This study set out to determine what motivated SMEs in Semarang City to undertake green supply chain management during the COVID-19 and New Normal pandemics. The purposive sampling approach was used as the sampling methodology in this investigation. There are 100 respondents in the research samples. The AMOS 24.0 program's structural equation modelling (SEM) is used in this research method. According to the study's findings, the Strategic Orientation variable significantly and favourably affects the Green Supply Chain Management variable expected to have a value of 0.945, and the Government Regulation variable has a positive and strong influence on the variable Green Supply Chain Management with an estimated value of 0.070, the Green Supply Chain Management variable with an estimated value of has a positive and significant impact on the environmental performance variable. 0.504, the Strategic Orientation variable with an estimated value of has a positive and significant impact on the environmental performance variable. 0.442, The Environmental Performance variable is directly impacted positively and significantly by the Government Regulation variable, with an estimated value of 0.041. This significant positive influence is because SMEs in Semarang City have government regulations, along with government support for facilities regarding efforts to implement the concept of environmental concern, causing high environmental performance caused by the optimal implementation of Green supply chain management is built on a collaboration between the government and the supply chain's participants.

Supply Chain Management requires addressing a variety of complex decision-making challenges, from sourcing strategies to planning and execution. Over the last few decades, advances in computation and information technologies have enabled the transition from manual, intuition and experience-based decision-making, into more automated and data-driven decisions using a variety of tools that apply optimization techniques. These techniques use mathematical methods to improve decision-making. Unfortunately, business planners and executives still need to spend considerable time and effort to (i) understand and explain the recommendations coming out of these technologies; (ii) analyze various scenarios and answer what-if questions; and (iii) update the mathematical models used in these tools to reflect current business environments. Addressing these challenges requires involving data science teams and/or the technology providers to explain results or make the necessary changes in the technology and hence significantly slows down decision making. Motivated by the recent advances in Large Language Models (LLMs), we report how this disruptive technology can democratize supply chain technology - namely, facilitate the understanding of tools' outcomes, as well as the interaction with supply chain tools without human-in-the-loop. Specifically, we report how we apply LLMs to address the three challenges described above, thus substantially reducing the time to decision from days and weeks to minutes and hours as well as dramatically increasing planners' and executives' productivity and impact.

In this paper, a blood supply chain network, where the occurrence of disruption might interrupt the flow of Red Blood Cells, is dealt with. In principle, the probability of disruption is not the only property confiding the network, but unprecedented fluctuations in supplies and demands also contribute to the network shortages and outdated blood units. Although the consideration of parameter uncertainties is of paramount importance in the real-world circumstances for a decision-maker, she or he would be willing to monitor the network in a properly broader perspective. Therefore, one of the eminent key performance indicators known as service level turned our attention. To tackle uncertainties in the mentioned network - comprising of the four conventional levels containing donors, blood collection facilities, blood banks, and hospitals - we present a two-stage stochastic programming model. Consequently, a toy-example is randomly generated to validate the proposed model. Furthermore, numerical analysis led us to a comprehensive service level analysis. Finally, potential pathways for future research are suggested.

This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties crucial for a secured supply chain: transparency, validity, and separation. The paper describes current security approaches and maps them to the proposed security properties, including research ideas and case studies of supply chains in practice. It discusses the strengths and weaknesses of current approaches relative to known attacks and details the various security frameworks put out to ensure the security of the software supply chain. Finally, the paper highlights potential gaps in actor and operation-centered supply chain security techniques