The effect of supply chain noise on the financial performance of Kanban and Drum-Buffer-Rope: An agent-based perspective

Managing efficiently the flow of products throughout the supply chain is essential for succeeding in today's marketplace. We consider the Kanban (from Lean Management) and Drum-Buffer-Rope (DBR, from the Theory of Constraints) scheduling mechanisms and evaluate their performance in a four-echelon supply chain operating within a large noise scenario. Through an agent-based system, which is presented as a powerful model-driven decision support system for managers, we show the less sensitivity against variability and the higher financial performance of the DBR mechanism, which occurs as this mechanism improves the supply chain robustness due to its bottleneck orientation. Nonetheless, we prove the existence of regions in the decision space where Kanban offers similar performance. This is especially relevant taking into account that Kanban can be implemented at a lower cost, as TOC requires a higher degree of information transparency and a solid contract between partners to align incentives. In this sense, we offer decision makers an approach to reach an agreement when the partners decide to move from Kanban to DBR in a bid to increase the overall net profit in supply chains operating in a challenging noise scenario

Theory of constraints case study in the make to order environment

Purpose: The theory of constraints (TOC) drum-buffer-rope methodology is appropriate when managing a production plant in complex environments, such as make-to-order (MTO) scenarios. However, some difficulties have been detected in implementing this methodology in such changing environments. This case study analyses a MTO company to identify the key factors that influence the execution of the third step of TOC. It also aims to evaluate in more depth the research started by Lizarralde et al. (2020) and compare the results with the existing literature. Design/methodology/approach: The case study approach is selected as a research methodology because of the need to investigate a current phenomenon in a real environment. Findings: In the case study analysed, the protective capacity of non-bottleneck resources is found to the key factor when subordinating the MTO system to a bottleneck (BN). Furthermore, it coincides with one of the two key factors defined by the literature, namely protective capacity and protective inventory. Originality/value: The three key contributions of this study focus on the MTO environment as follows.The first is about identifying the key factors in subordinating the system to the BN (step 3, TOC) according to the existing literature which have been identified through a systematic literature review. The second focuses on identifying the key factors in subordinating the system to the BN through a case study. Finally, the last contribution compares the results obtained in the case study with those obtained in the literature review

A Flexible Simulation Support for Production Planning and Control in Small and Medium Enterprises

For efficient, effective and economical production operation management in a manufacturing unit of an organization, it is essential to integrate the production planning and control system into an enterprise resource planning. Today\u27s planning systems suffer from a low range in planning data which results in unrealistic delivery times. One of the root causes is that production is influenced by uncertainties such as machine breakdowns, quality issues and the scheduling principle. Hence, it is necessary to model and simulate production planning and controls (PPC) with information dynamics in order to analyze the risks that are caused by multiple uncertainties. In this context, a new approach to simulate PPC systems is exposed in this paper, which aims at visualizing the production process and comparing key performance indicators (KPIs) as well as optimizing PPC parameters under different uncertainties in order to deal with potential risk consuming time and effort. Firstly, a production system simulation is created to quickly obtain different KPIs (e.g. on time delivery rate, quality, cost, machine utilization, WIP) under different uncertainties, which can be flexibly set by users. Secondly, an optimization experiment is conducted to optimize the parameters of PPC with regard to the different KPIs. An industrial case study is used to demonstrate the applicability and the validity of the proposed approach

Constraint-Based Supply Chain Inventory Deployment Strategies

The development of Supply Chain Management has occurred gradually over the latter half of the last century, and in this century will continue to evolve in response to the continual changes in the business environment. As organizations exhaust opportunities for internal breakthrough improvements, they will increasingly turn toward the supply chain for an additional source of untapped improvements. Manufacturers in particular can benefit from this increased focus on the chain, but the gains realized will vary by the type of supply chain. By applying basic production control principles to the chain, and effectively using tools already common at the production line level, organizations address important supply chain considerations. Both the Theory of Constraints and the factory physics principles behind the Constant WIP concepts focus on the system constraint with the aim of controlling inventory. Each can be extrapolated to focus on a system whose boundaries span the entire supply chain