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Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty.

In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios.

From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible.

In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size.

This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

Determining the number of circulating kanban cards is important in order effectively to operate a just‐in‐time with kanban production system. While a number of techniques exist for setting the number of kanbans, artificial neural networks (ANNs) and classification and regression trees (CARTs) represent two practical approaches with special capabilities for operationalizing the kanban setting problem. This paper provides a comparison of ANNs with CART for setting the number of kanbans in a dynamically varying production environment. Our results show that both methods are comparable in terms of accuracy and response speed, but that CARTs have advantages in terms of explainability and development speed. The paper concludes with a discussion of the implications of using these techniques in an operational setting.

Examines Just‐in‐Time (JIT) from its evolution as a Japanese concept through to a review of its philosophy and implementation. Cites several techniques of implementation. Includes a review of the early work of various researchers and practitioners. Concludes that JIT is a very effective manufacturing philosophy which is universal in nature encompassing all aspects of manufacturing. Suggests a few deficiencies in current literature.

The aim of this paper is to develop an efficient analytical procedure to evaluate performance of the most general pull production systems particularly when multiple‐part‐types are involved. The authors consider a kanban controlled production system that can be modelled as a closed queuing network with different product classes. The production line is decomposed into stages which consist of one or several stations and an output buffer. Each stage is associated with a given number of kanbans. The main idea of this analytical algorithm is to analyze each subnetwork individually using a product form approximation technique. The iterative procedure is used to find the unknown parameters.

The authors design a multiclass queuing network that can be used to represent kanban controlled production systems. To solve this model, three procedures are used: decompose the original network into M subnetworks, convergence of unknown parameters in each subnetwork, and convergence of unknown parameters in the original network. The authors now describe these procedures separately.

The main contribution of this paper is the formulation of the problem of kanban controlled production systems with several part‐types. The methodology is based on approximate formula with decomposition and is applicable to more general manufacturing environments. The authors' method can be applied to both limited and unlimited demands. The analytical algorithm designed in this work has demonstrated excellent performance in analyzing kanban controlled production systems.

The methodology of this algorithm is based on approximate formula and is applicable to more general manufacturing environments.

This paper presents a new generic Petri net (PN) model for design and performance evaluation of a flexible assembly system (FAS) and disassembly system (DAS) with dual kanban. The architectural design of the model is derived from a generic bill of materials (BOMs) in the FAS, a reverse BOM in the DAS and the process plan in the case of flexible manufacturing system (FMS). Integration of FMS, FAS and DAS by developing a new generic PN model with the pull system is introduced. Analysis and performance evaluation of the new model based on invariant analysis and linear programming are also introduced. The method will be illustrated by a small case study.

This paper aims to introduce, apply and validate, through a realistic case study, an analytical cost model to support the design of the tow-train feeding system for mixed-model assembly lines managed according to the just-in-time concept. The fleet size and inventory level, minimizing the total annual cost, are the key model goals, while the tow-train shipping capacity and the service level are the decisional variables to set.

The model computes the material handling, inventory and stockout rising costs of the tow-train feeding system and looks for their minimization. It further computes the expected lead time between consecutive round-trips and the Kanban card number, distinguishing among parts and assembly lines, overcoming the simplifying hypothesis assuming a constant lead time for all parts. The model is validated against a dedicated case study stressing its strengths in terms of cost and inventory-level reduction.

The proposed approach is found to be effective if compared to the standard literature in the field of Kanban system design. The 10.76 per cent cost saving is experienced for the considered case study, and the inventory level is closer to the field-experienced profile.

The model adopts a practical perspective, making it easy and applicable to common operative industries.

The literature neglects to consider the differences in the part consumption when estimating the lead time between tow-train round-trips. The proposed model overcomes such limitations and strengthens the model applicability and performances.

The aims of this paper is to investigate simulation‐based optimisation and stochastic dominance testing while employing kanban‐like production control strategies (PCS) operating dedicated and, where applicable, shared kanban card allocation policies in a multi‐product system with negligible set‐up times and with consideration for robustness to uncertainty.

Discrete event simulation and a genetic algorithm were utilised to optimise the control parameters for dedicated kanban control strategy (KCS), CONWIP and base stock control strategy (BSCS), extended kanban control strategy (EKCS) and generalised kanban control strategy (GKCS) as well as the shared versions of EKCS and GKCS. All‐pairwise comparisons and a ranking and selection technique were employed to compare the performances of the strategies and select the best strategy without consideration of robustness to uncertainty. A latin hypercube sampling experimental design and stochastic dominance testing were utilised to determine the preferred strategy when robustness to uncertainty is considered.

The findings of this work show that shared GKCS outperforms other strategies when robustness is not considered. However, when robustness of the strategies to uncertainty in the production environment is considered, the results of our research show that the dedicated EKCS is preferred. The effect of system bottleneck location on the inventory accumulation behaviour of different strategies is reported and this was also observed to have a relationship to the nature of a PCS's kanban information transmission.

The findings of this study are directly relevant to industry where increasing market pressures for product diversity require operating multi‐product production lines with negligible set‐up times. The optimization and robustness test approaches employed in this work can be extended to the analysis of more complicated system configurations and higher number of product types.

This work involves further investigation into the performance of multi‐product kanban‐like PCS by examining their robustness to common sources of uncertainties after they have been initially optimized for base scenarios. The results of the robustness tests also provide new insights into how dedicated kanban card allocation policies might offer higher flexibility and robustness over shared policies under conditions of uncertainty.

With support from the dynamic capabilities theory, this paper examines the role of Cloud Computing technology use in logistics (Cloud-Supported Logistics) and its effect on business results in Lean manufacturing management (Lean Production implementation) and Supply Chain Integration contexts.

Using the survey method, a random sample of 260 companies in intermediate positions in their supply chains was gathered from a population of 1,717 Spanish companies and used to test five hypotheses. The data were collected by telephone survey using a computerised system with a response rate of 15.6% (260 valid questionnaires). Structural equation modelling was used to test the five proposed hypotheses.

The findings indicate that Cloud-Supported Logistics use plays an important role in achieving better business results in Lean Production environments. Lean Production has been found to have both a direct effect and an even more powerful indirect effect on performance through the Cloud-Supported Logistics and Supply Chain Integration that these technologies produce. Supply Chain Integration is also found to have a mediating effect in the Cloud-Supported Logistics–performance relationship.

This study is valuable for academics and practitioners as it provides evidence of the relevant role played by Cloud-Supported Logistics in Lean Production implementation contexts. Cloud-Supported Logistics and Lean Production are strategically and operationally linked and their joint use results in Supply Chain Integration and better business performance.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

The aim of this article is to propose a methodology for the design and operation of a just‐in‐time coordination mechanism to control the flow of materials in the supply chain.

A literature review of the problem is presented and a new supply chain coordination mechanism is then proposed.

The paper reveals that the one aspect not deeply studied yet in the supply chain management is their short‐term control. A simple kanban coordination mechanism demonstrates that is practical in the flow coordination of materials among the different nodes (companies) in a supply chain.

This paper shows recent approaches in the supply chain context, useful to companies looking forward new opportunities in coordination systems for the supply chain.

The paper begins with a review of previous research in the material flow control in the supply chain. The authors then propose a new mechanism and an optimization methodology to deal with the coordination mechanism.