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Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice. [ABSTRACT FROM AUTHOR]

This work is a supplement to earlier literature reviews of research on the production control scheme known as CONWIP. In this paper, we chronicle the origins of CONWIP and address many of the issues and misunderstandings that have appeared over the past 30+ years. [ABSTRACT FROM AUTHOR]

Kanban systems are simple yet effective means of controlling production. Production control is decentralised or exercised locally on the shop floor, i.e. a downstream station signals to an upstream station that an item is needed. If items are always the same and known, then demands can be satisfied instantaneously from stock; but if items differ and are unknown, demands must first be propagated backwards from station to station before being satisfied. The former is defined as an inventory control problem and the latter as an order control problem. Handling the order control problem via kanban involves a decentralised card acquisition process (during which information is propagated from station to station) that is separated from the actual production process. COBACABANA (control of balance by card-based navigation), an alternative card-based solution, shares kanban's control structure but centralises the card acquisition process. Evaluating the two systems therefore provides a unique opportunity to compare decentralised and centralised control. Using simulation, we demonstrate that it is specifically the centralised card acquisition process that allows COBACABANA to balance the workload across resources and thus to outperform kanban in an order control problem. This has major implications for research and practice. [ABSTRACT FROM AUTHOR]

Demand driven material requirements planning or DDMRP is a recent and promising material management method that has been developed and implemented in the practitioner world. Essentially, DDMRP represents a rethinking of the basic MRP logic. By incorporating elements drawn from Lean Systems and the Theory of Constraints and by introducing new features such as dynamic buffers, DDMRP modifies the basic MRP logic so that it is better able to satisfy customer demands in an increasingly demanding, turbulent and dynamic environment. Claims have been made by firms that DDMRP represents a superior planning approach. In this paper, we introduce and explore DDMRP. In addition, we evaluate its effectiveness relative to two other widely accepted approaches - MRP II and Kanban/Lean production - through a series of structured computer simulation experiments. The results strongly indicate that DDMRP does represent a superior approach - one that warrants further academic study. [ABSTRACT FROM AUTHOR]

The construction industry has long been suffering from high rates of noncontributory time. Construction processes are likely to include time, which is sometimes lost for non-value-adding operations resulting in time waste. Considering the large percentage of lost time in all operations, this study aims to reduce the high rate of non-contributory time (NCT) in construction services. To test the management model, a Peruvian company was selected as a study case. In this respect, a management model based on mostly implemented Lean tools such as Kanban, 5S, and TPM was utilized. It is of utmost importance to emphasize that this proposal aims to reduce the NCT by up to 25%, as well as reduce the number of orders generated with delay, and eventually reduce the loss or damage of materials and equipment stoppages. [ABSTRACT FROM AUTHOR]

In the past decade, a growing body of literature has investigated the CONstant Work In Progress (ConWip) production control system (PCS). In view of the current industrial challenges entailing adaptability, product customisation, decreasing leadtimes and customer satisfaction, ConWip seems to be an effective and adaptive PCS for manufacturers. This paper aims to update the last ConWip systematic review that dates back to 2003 and to provide a guide for understanding through an original classification method. This method enables the differentiation of papers that concentrate on ConWip sizing, performance and context as well as a comparison with other PCSs. In addition to providing a key to interpreting the research approaches, the criteria considered answers questions on how to implement, how to optimise and why and when to use ConWip. Finally, the most relevant research avenues are highlighted to provide future lines of research. [ABSTRACT FROM AUTHOR]

We explore the use of an agile methodology for improving the recovery of complex systems under catastrophic scenarios. Our adaptation of Kanban presents a novel, agile approach to overcoming the unique challenges that organizations face during disaster recovery. An action research study approach is employed to test the implementation of Kanban during a complex scenario at a large enterprise. The findings suggest that an adaptive and flexible methodology is required for an efficient disaster recovery in confronting unintended and cascading consequences. This research offers several contributions. First, to our knowledge, this is the first study to detail an approach for disaster recovery using an agile methodology. Second, this study uses a new combination of classic, canonical, and dialogical action research approaches to conduct the first empirical test of the effectiveness of an agile approach during an actual disaster recovery event. Third, in response to this Special Issue, the aforementioned research approach discusses the relationships between information systems researchers and research clients, demonstrating how action research can lead to improved organizational situations. [ABSTRACT FROM PUBLISHER]

In accordance with the lean production philosophy, an assembly line may be supplied by means of a kanban system, which regulates and simplifies the flow of materials between the lines and the warehouses. This paper focuses on evaluation of feeding policies that differ from each other in term of the number of kanbans managed per feeding tour. A pure cost-based approach is thus proposed, which considers both inline inventories along with handling costs proportionate to the number of operators involved in the parts-feeding process. A multi-scenario simulative approach is applied in order to establish the number of operators required to avoid inline shortages. The scenario minimising total cost is then selected. The innovation introduced is a model for describing kanban arrivals and their requests for feeding, improving the potential of the simulation to describe real-life environments. Lastly, a case study from the automotive industry is presented in order to highlight the applicability of the proposed approach as well and the effects of alternative feeding policies on the total cost incurred. [ABSTRACT FROM AUTHOR]

This paper explores the Agile methodologies, Scrum and Kanban, to define their advantages and limitations of use. The methods are compared for their use in software development, specifying which would be a suitable option for a game development process focusing on maximizing productivity and quality of the software. Exploration of use cases and methodology guides are discussed, defining the benefits of choosing Kanban or Scrum for a software development team. Findings show Scrum to be a method that focuses on the verbal communication through sprint meetings and reviews. Kanban is described as a visually driven framework that utilizes a Kanban board and cards for communication. Scrum is a strict method can only implement change after a sprint, while Kanban is more flexible and can make changes at any point in the development process. A hybrid of the two methods, Scrumban, is also investigated and found to be an alternative for users who find aspects of both methodologies to be appropriate for their team. There is a great deal of consideration required for independent game developers as they need to reflect on their team dynamics and situation before determining which methodology is best suited for them. [ABSTRACT FROM AUTHOR]

In this paper, we conduct an analytical comparison of three pull production control systems: Kanban, CONWIP and Base-stock in multi-stage production processes. First, we compare the three control systems in a multi-stage serial production process. Then, we compare them in multi-stage assembly production processes, and present guidelines that allow us to select the best system. As a result, we show which structural parameters decide the superiority of one control scheme to the others, and how they are related. A key for superiority is a configuration of parameters, such as processing times and number of cards employed in the system. We show that there is no general superiority amongst the analysed concepts. Finally, we verify the effect of variability on the system performance, and generalise the analytical results of deterministic cases by conducting numerical experiments. [ABSTRACT FROM AUTHOR]

One-piece flow and kanban/pull methods have been used to reduce work-in-process (WIP) and flowtime in manufacturing flow processes; however, these methods have limitations. For example, one-piece flow does not work well when there are relatively large set-up times required between different components. One-piece flow also requires operations to be well balanced with a minimum of variability in processing times at each operation. Unfortunately, these conditions often do not exist. The theory of constraints drum-buffer-rope (DBR) method is designed for unbalanced processes, and it has been shown to be effective for products with large operation time variation. However, DBR does not generally optimise flowtime and cannot handle a process with moving constraints (bottlenecks). We have developed a method called Takt Time Grouping (TTG) for implementing kanban-flow manufacturing, when one-piece flow or DBR do not provide good results. TTG combines one-piece flow manufacturing, transfer-batch sizing and DBR concepts through the use of a constraints-based transfer-batch sizing formula. Using a discrete event simulation model, it is shown that TTG increases throughput rate as compared to one-piece flow, CONWIP and DBR approaches, with much lower WIP inventory and faster flowtime than CONWIP and DBR. [ABSTRACT FROM AUTHOR]

A common simplifying assumption used in the literature is to minimise average Work In Process (WIP), while achieving maximum production rate, which does not consider the fact that the value of WIP increases down the stream of a production process as labour, time, energy and resources are added to it. This paper aims at minimising queues of parts waiting downstream of production process and in turn minimising value-added WIP by constraining more and more inventory of unfinished products at the earlier stages of production. For this reason, generic black token closed loop Petri Net (PN) model of Flexible Flow Shop (FFS) with Paired-cell Overlapping Loops with Card Authorisation (POLCA) is developed. Tokens in the control loops represent Polca cards to control the flow of material from order release till finished products. Marking of PN is done through Mix Integer Linear Programming after the computation of semi-positive P invariants. Simulation is being done to obtain queues of parts, waiting at each station during demand variation. Results were compared with PN model of FFS without Polca. Results showed the constriction of unnecessary WIP towards the initial stage of production instead of at bottlenecks, with proposed model, and in turn minimisation of value-added WIP. [ABSTRACT FROM AUTHOR]

Preventive maintenance is widely implemented in manufacturing industries for reducing random machine failures. High availability of a machine may be ensured by avoiding excessive or insufficient maintenance. Although analytical models of single or two-machine systems with preventive maintenance have been proposed in the literature, similar study on multi-machine systems remains limited. In this paper, the authors investigate preventive maintenance in Kanban controlled assembly lines and develop an analytical model for such systems. This model decomposes an assembly line into a series of primitive line segments. Each segment is characterised by a continuous-time-discrete-state Markov process. This model provides the estimates of production rate and work-in-process, which can be used to evaluate the effect of preventive maintenance on an assembly line. Additionally, based on the proposed model, we also present an algorithm to determine the maintenance rates for all machines in a Kanban controlled assembly line. As demonstrated in the numerical experiments, the analytical model is useful to manufacturers in preventing excessive or insufficient maintenance and thus improving the production rate of Kanban controlled assembly lines. [ABSTRACT FROM AUTHOR]

Many pull policies can be found in the literature for controlling multi-stage production/inventory systems. In this paper we present a framework that enables us to describe the dynamics of a large class of pull control policies, using the same set of canonical functions. The class of policies we consider includes well-known pull policies such as kanban, CONWIP, basestock, generalised kanban, and extended kanban, and also many other hybrid policies, and their extensions to systems producing batches. Each of these policies is characterised by certain parameter values. These parameter values are calculated using a computational algorithm that relies on the use of path algebra tools, especially (min, +) algebra tools. This canonical formulation allows us to identify under which values of the control parameters, two different policies will exhibit the same dynamic behaviour. It also enables us to derive methods for evaluating and comparing the performance of various pull control policies. [ABSTRACT FROM AUTHOR]

Lean production is proved to be an effective tool for companies to improve continuously and is widely studied from both practical and theoretical perspectives. However, most previous studies of lean production are limited to internal operations of a company. The research in this paper aims to explain the relationship between electronic-enabled supply chain integration and the adoption of lean production. A theoretical model with six hypotheses was proposed based on the innovation diffusion theory (IDT). The model was empirically tested with data from 558 manufacturers. The results show that: (1) IDT can explain lean production adoption; and (2) electronic-enabled supply chain integration positively influences the perceived relative advantage of lean production and consequently leads to its long-term adoption. This study uses IDT to explain lean production adoption with the influence of electronic-enabled manufacturing supply chain (EMSC). The study also has a practical implication that may change the supply policy in future practices, as companies may require their suppliers to implement EMSC as part of the lean production requirements. [ABSTRACT FROM AUTHOR]

This paper presents a new method to describe, analyse and estimate production system performances. Work-in-process (units), lead time (number of time units spent in the production system for each unit) and throughput (number of produced units per time unit) are basic performance measures, also used in this article. It is essential for industry to know about relations between system parameters and system performances in existing systems, and in not yet implemented system alternatives. Different performances are achieved by adjusting system parameters. Trade-offs between system parameters and its different performances are necessary to stay efficient and competitive in today's market. Queuing theory and simulation can help the decision makers to estimate system performances of existing and not yet implemented systems. When the complexity increases queuing theory becomes cumbersome, very difficult and eventually impossible to use. A single simulation presents limited information. Multiple simulations are necessary to ensure that the best alternative is chosen. A high number of simulations demand a lot of computer time and resources. Reduction of runs is desirable even with cheaper computer equipment. Currently, traditional two-dimensional charts are the only tools to present and analyse system performances. This article presents a new surrogate model for easier estimation and presentation of system performances, their internal relations, and relations to the system parameters. With the new surrogate model, system performances based on simulations are presented as positions in a three-dimensional environment. Parametric curves and surfaces of Bezier type are generated and adapted to these positions. System performances of other system alternatives can then be estimated without explicit simulation. The number of simulation calculations can thereby be moderated. The method is illustrated with a small production line system. [ABSTRACT FROM AUTHOR]

While the effect of protective inventory on the performance of simple lines has received considerable attention, the same cannot be said for re-entrant lines. This paper attempts to meet that deficiency. This paper examines two different but related issues. First, the theory of constraints (TOC) evaporating cloud method is employed to show the traditional dilemma of increasing work-in-process (WIP) to fully utilise resources versus decreasing WIP inventory to reduce cycle time. The assumptions and implications of three different management philosophies (traditional, JIT/lean, and TOC) are explored in addressing this dilemma with respect to the use of both protective inventory and protective capacity. Second, given an unbalanced re-entrant line with fixed capacity, simulation is used to explore the effectiveness of using protective inventory by changing the level of WIP on two dependent variables: cycle time and throughput. Two sources of variation are simulated: processing time and breakdowns (machine failures). At a given WIP level, it was found that the amount of protective capacity at non-bottlenecks changed with increases in variability. Therefore the level of WIP inventory (with its protective inventory) and the level of protective capacity needed to protect against variability play a critical role in determining cycle time and throughput of the re-entrant line. While this is an exploratory study, comments on protective inventory and protective capacity are provided based on the three different management philosophies. [ABSTRACT FROM AUTHOR]

Kanbans play an important role in the information and material flows in a JIT production system. The traditional kanban system with a fixed number of cards does not work satisfactorily in an unstable environment. In the flexible kanban-type pull control mechanism the number of kanbans is allowed to change with respect to the inventory and backorder level. Based on the need for the flexible kanban, a method was proposed by (Husseini, S.M.M., O'Brien, C., and Hosseini, S.T., 2006. A method to enhance volume flexibility in JIT production control. International Journal of Production Economics, 104 (2), 653-665), using an integer linear programming technique, to flexibly determine the number of kanbans for each stage of a JIT production system, minimising total inventory cost for a given planning horizon. Here, the effectiveness of the method proposed by Husseini et al. is examined by a case study and compared with the results for the conventional method of fixed kanban determination. This is also confirmed by a simulation study using artificial neural networks (ANNs). The main aim of this paper is to show the cost advantage for Husseini et al.'s method over the conventional method in fluctuating demand situations, and especially to prove that simulation via ANNs ensures a simplified representation for this method and is time saving. [ABSTRACT FROM AUTHOR]

The traditional kanban system with a fixed number of cards does not work satisfactorily in an unstable environment. With the adaptive kanban-type pull control mechanism, the number of kanbans is allowed to change with respect to the inventory and backorder level. It is required to set the threshold values at which cards are added or deleted, which is part of the design. Previous studies used local search and meta-heuristic methods to design an adaptive kanban system for a single stage. In a multi-stage system the cards are circulated within the stage and their presence at designated positions signals to the neighbouring stages details concerning the inventory. In this work, a model of a multi-stage system adapted from a traditional and adaptive kanban system is developed. A genetic and simulated annealing algorithm based search is employed to set the parameters of the system. The results are compared with a traditional kanban system and signs of improvement are found. The numerical results also indicate that the use of a simulated annealing algorithm produces a better solution. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of integrating advance demand information (ADI) with Kanban-based pull production and inventory control systems (PICS). Predicting the impact of several PICS design parameters such as Kanban card limits, base stock levels, demand information lead times, and the quality of ADI on performance measures such as throughput, inventory holding costs and customer service levels, presents a complex yet important problem. Since efficient analytical models for performance evaluation studies of these systems are unavailable, simulation experiments are used for the study. The study shows that in many situations, integrating ADI with Kanban-based pull systems provides opportunities for efficiencies that might be significantly greater than that available using pull systems alone. Further, the study also investigates the performance sensitivity of these systems to the quality of information shared and information asymmetry. [ABSTRACT FROM AUTHOR]

Adaptive card control strategy-based heuristics are used to change the number of cards dynamically in response to stochastic and fluctuated customers’ demands. However, when the decisions are taken in real-time and without the use of forecasts, existing heuristics may yield to change too often the number of cards. This over-correction, related to system nervousness, can induce undesirable effects for the workshop. Our literature analysis underlines that, despite nervousness has been discussed in other industrial areas, it seems not to have been studied in the context of adaptive pull control systems. We first introduce and discuss nervousness in the context of adaptive pull control systems. We identify the main factor that induces nervousness and its consequences. To reduce nervousness, we propose a new approach, which relies both on an adaptive freezing interval and a multi-objective simulation optimisation technique. We first show the relevance of the proposed approach through a comparison with an adaptive Kanban system taken from the literature. This comparison shows that our approach yields better results. In addition, the resulting Pareto front offers flexibility to the decision-maker. The suggested approach can be useful: for managers to better implement their adaptive pull systems, and for decision-makers to define operational procedures taking nervousness into account. [ABSTRACT FROM AUTHOR]

An assembly-type just-in-time (JIT) supply chain system is composed of a main serial supply chain and several branching serial supply chains merging to the main supply chain. Under the assumption of constant demand rate, the replenishment problem in the assembly-type JIT supply chain systems can be formulated as a mixed-integer non-linear programming problem. We conduct thorough theoretical analysis on the properties of the objective function value curve in this study. Following our theoretical analysis, we propose a search algorithm that effectively solves an optimal solution. Our numerical experiments show that the average run time of the proposed algorithm grows in a linear order of the problem size, and the proposed algorithm may serve as an efficient solution approach for the decision-maker. [ABSTRACT FROM PUBLISHER]

This segment of the Sharpest Tool in the Shed column explores three tools to aid libraries in the management of electronic resources. Electronic resources management is often multistep, time-consuming work riddled with almost identical workflows, and the tools discussed in this column provide ways to save time as well as handle work more efficiently. Drawing on research and conference presentations, this column will examine the workflow management tools Trello, Asana, and Planner. [ABSTRACT FROM AUTHOR]

Problem-based learning (PBL) has proven to be highly effective for educating students in an active and self-motivated manner in various disciplines. Student projects carried out following PBL principles are very dynamic and carry a high level of uncertainty, both conditions under which agile project management approaches are assumed to be highly supportive. The paper describes an empirical case study carried out at Aalborg University Copenhagen involving students from two different semesters of a Bachelor of Science programme. While executing the study, compelling examples of how PBL and the agile project management method Kanban blend could be identified. A final survey reveals that applying Kanban produces noticeable improvements with respect to creating, assigning and coordinating project tasks. Other improvements were found in group communication, knowledge about the work progress with regards to both the individual and the collective and the students’ way of continuously improving their own teamwork. [ABSTRACT FROM PUBLISHER]

Although a lean focus is widely popular in general manufacturing environments, there are limited studies that empirically investigate how lean improvement programmes can be integrated with a material requirement planning (MRP) system. The aim of this research is to examine if the integration of lean improvement programmes with a MRP system has a positive effect on operational effectiveness when manufacturers are experiencing high levels of customer demand variability. Based on the contingency theory perspective and using data collected from the international manufacturing strategy survey (IMSS-V), a sample of 382 international manufacturing companies are first divided into two groups based on the degree of their customer demand fluctuation. Moderated hierarchical regression is then applied to each group to empirically test the research hypotheses. Statistical results suggest that operational effectiveness significantly improves when lean improvement programmes support MRP systems as manufacturers are experiencing high levels of fluctuations in demand. [ABSTRACT FROM AUTHOR]

Within immunization programs supported by the World Health Organization, current practice is to use a vial as the basic unit for managing vaccine inventories at the clinic level. In addition to being inconvenient, this has the potential to induce errors in the ordering process. We propose alternative ordering policies based on using inner pack quantities corresponding to secondary vaccine packaging and draw upon visual management, simplified inventory tracking, better housekeeping, and other lean related concepts that have been used in the manufacturing sector to simplify and improve the vaccine inventory management system. We present analyses that show that the proposed polices only require very modest increases in fixed storage and transport requirements. [ABSTRACT FROM PUBLISHER]

Since the emergence of Kanban, there has been much research into card-based control systems. This has included attempts to improve Kanban and/or develop alternative systems, particularly ConWIP (i.e. Constant Work-In-Process), POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorisation) and COBACABANA (i.e. Control of Balance by Card-Based Navigation). Yet, to date, no unifying review of the mechanisms underpinning these systems has been presented. As a consequence, managers are not provided with sufficient support for choosing an appropriate system for their shop; and researchers lack a clear picture of how the mechanisms compare, leading to several misconceptions. This paper reviews the control mechanisms underpinning the Kanban, ConWIP, POLCA and COBACABANA systems. By comparing the 'control mechanism' (i.e. the loop structure and card properties) and 'contextual factors' (i.e. routing variability, processing time variability, and whether stations are decoupled by inventory or the flow of jobs is controlled), we provide managers with guidance on which system to choose. For research, we show for example that most criticisms put forward against Kanban systems, e.g. to justify the development of ConWIP, POLCA or COBACABANA, only apply to work-in-process Kanban systems and not to production Kanban systems. Future research directions for each control system are outlined. [ABSTRACT FROM AUTHOR]

This study explores the implementation of the kanban system, which is a Lean technique, within the pharmaceutical supply chain (PSC). The case study provides insights on the benefits and challenges arising from the application of this technique, within a group of cooperative pharmacists, in Greece. The research questions developed from the review of the literature were tested using evidence from field-based, action research within a pharmaceutical organisation. The reported case study contributes to the longer term debate on assessing the Lean maturity level within the health-care sector. There are two primary findings: (i) that the adoption of kanban system provides a strategic benefit and improves the quality of services. (ii) It also provides a basis for a strategy of operational change; it gives the opportunity to the organisation to move away from the current push delivery and logistics systems towards improved logistics strategy models. [ABSTRACT FROM AUTHOR]

The problems with the poor use of project data include: i. lack of visibility and transparency of what is being worked on; ii. differing understanding of purpose across the project team;iii. silo’d and individual work patterns; and iv. ‘watermeloning’, described as the reporting of project status and progress as green or to plan when the project is red, behind plan. Through the successful development and implementation of a Visual Project Status Wall, it was shown how the problems could be addressed by increasing transparency and collaboration in the project team. The Visual Project Status Wall is a low fidelity, flexible, interactive, visual and data rich artefact that can be quickly adapted to the changing needs of a project team. A set of critical success factors were identified that can be applied by practitioners to the use of Visual Project Status Walls on other transformation programmes. [ABSTRACT FROM PUBLISHER]

Supply replenishment in many healthcare settings is a very laborious and wasteful process. The objective of this article is to describe a pilot implementation of a fixed order quantity kanban system for supply replenishment within an outpatient clinic at a cancer center. The pilot resulted in decreased labor for materials management staff and increased supply availability for clinicians. The concepts discussed and implemented build on the engineering management body of knowledge. The article provides an in-depth look at a successful implementation. In particular, the article describes the baseline process analysis used, the application of inventory modeling principles, as well as the application of a decision support tool. The results of the described inventory replenishment process redesign using the kanban system and stock card approach provide other engineering managers a roadmap for their own implementations. [ABSTRACT FROM AUTHOR]

Centralised planned campaign production is the predominant production system in process industries. In this study, we investigate whether a decentralised Kanban control system, which has proven to offer advantages in other industries, can be successfully integrated in a campaign production environment. The used research methodology combines model-based and case-study-based elements. Using the example of a pharmaceutical internal five-stage supply chain, we conceive a Kanban concept that integrates campaign formation, develop a discrete-event simulation model and conduct a range of explorative simulation experiments. We find that a Kanban campaign production system is not merely feasible but would also be favourable: throughput times can be reduced without increasing customer lead times. Sensitivity analysis shows that the system’s performance is relatively robust to changes in Kanban key configuration parameters such as number of Kanban cards or campaign size. We conclude by discussing our findings and formulating three propositions that might stimulate future research. [ABSTRACT FROM PUBLISHER]

Job-shop production in an individual and small-batch manufacturing environment demands producing simultaneously different products in many customised versions and in small numbers. The associated variability of the time-phased work content leads to a high degree of complexity and turbulence in the manufacturing process of such a production type. Therefore, production control becomes significantly more complicated, and many theories on how to cope fail in the real world. Despite the many technological and conceptual advances in the field of job-shop control over the past few decades, there is still a remarkable lack of practical control approaches for job-shop production. For this reason the Push-Kanban production control concept will be introduced in this article. It combines robust push scheduling along with a kanban-driven, decentralised inventory control mechanism to create a holistic control approach, integrating all production control tasks. Thus, it offers a feasible option for controlling job-shop production in industrial practice. This article examines the effectiveness of the concept by means of a simulation study based on real data. [ABSTRACT FROM AUTHOR]

The dynamic control of cards in pull systems can improve the performance of a manufacturing system in a turbulent demand condition. The traditional fixed card approach can reduce the performance of a system in some cases. This article presents a dynamic card control methodology in order to keep a high level of performance measures. The proposed methodology is based on the observation of customer demand in order to detect the fluctuations and adjust the number of cards. The demand fluctuations is evaluated based on two moving average: the first on a medium horizon and the second on a short horizon. The comparison between the two moving averages is the signal of the controller developed. A simulation environment has been developed to test the proposed methodology in both kanban and Constant Work In Process (CONWIP) systems. The simulations conducted in several scenarios highlight the better performance obtained using the controller. The main performance measures investigated are: the throughput, the queue of orders waiting to be processed, the throughput time of the orders, the number of cards used and the orders delayed. The benefits are more relevant in the case reliability reduction of the manufacturing system. [ABSTRACT FROM PUBLISHER]

The article presents a study which examines the validity of the notion that effective manual systems (EMS) or systems supporting human choices in the course of work should be regarded as decision support systems (DSS). The study analyzes the nature of the choices by humans during routine work by reviewing literature on EMS, routine work activity and human choice. The researchers also offer a case study of a manual whiteboard-based bed allocation system in hospital's intensive care unit (ICU).

Adaptation of constant work-in-process (CONWIP) in make-to-order (MTO) environments essentially depends on the support of three key just-in-time (JIT) practices, i.e. unidirectional flow (UF), one-piece flow (OPF), and set-up time reduction (STR) induced by cellular manufacturing. Their impacts on the performance difference between CONWIP and Kanban were investigated by simulation experiments. CONWIP was found to be more adaptable to the dynamic shop environment since it outperforms Kanban regardless of the scenarios of the key JIT practices. The importance of UF in support of CONWIP was highlighted for a smaller STR. While a larger STR extends the effectiveness of UF, the advantage of UF in favor of CONWIP lessens at the same time. To justify the practice of OPF, an 80% or larger STR is required and CONWIP along with UF should be adopted. This study complements the current literature by establishing essential guidelines for coordinating the key JIT practices to enhance the functioning of CONWIP in MTO environments. [ABSTRACT FROM AUTHOR]

Kanban, a key element of just-in-time system, is a re-order card or signboard giving instruction or triggering the pull system to manufacture or supply a component based on actual usage of material. There are two types of Kanban: production Kanban and withdrawal Kanban. This study uses optimal and meta-heuristic methods to determine the Kanban quantity and withdrawal lot sizes in a supply chain system. Although the mix integer programming method gives an optimal solution, it is not time efficient. For this reason, the meta-heuristic methods are suggested. In this study, a genetic algorithm (GA) and a hybrid of genetic algorithm and simulated annealing (GASA) are used. The study compares the performance of GA and GASA with that of the optimal method using MIP. The given problems show that both GA and GASA result in a near optimal solution, and they outdo the optimal method in term of run time. In addition, the GASA heuristic method gives a better performance than the GA heuristic method. [ABSTRACT FROM AUTHOR]

This work formalises a new approach for material flow control, i.e. the so-called customised token-based systems (CTBS). This approach represents a natural evolution from classical pull systems, such as Kanban. The article first describes the flow of materials (orders or tasks) from a management point of view, and discusses exact and approximate approaches to tackle the problem. The origin of Customised Production Control systems is explained, as well as the main advantages: high degree of generalisation, enhancement of the space of solutions and adaptation to the manufacturing environment. Next, we propose a method based on cross-entropy for the optimisation of CTBS. The computational experience carried out in a number of scenarios shows the CTBS to be profitable. Furthermore, the resulting control mechanisms seem to be relatively easy to implement in real-manufacturing environments. [ABSTRACT FROM AUTHOR]

The JIT system and its operational techniques have shown noticeable advantages when applied in an ideal factory. The steadiness of demand and production times and the reduction of set-up times represent the key factor necessary in order to correctly execute JIT. Ideal environments are designed to work with smooth and stable demand patterns, constant and balanced processing times, small lot sizes and without scraps and reworks. However, these conditions are difficult to realise in real productive systems. In these contexts, the increase of operational costs, owing to the growth of inventories, necessary to match demand, often causes the failure of many JIT implementations. For these reasons, during the past years researchers have been investigating the issues related to JIT implementation in unsteady productive organisations. In this area, the kanban system, responsible for the exact propagation of information and for inventory control, is the most widely researched control mechanism. Literature proposes various kanban systems; in all cases the determination of the number of kanbans depends both on the management method chosen at each stage of the process as well as on the fluctuation of operative variables. This study deals with the problem of choosing the optimal number of kanbans in a multi-stage productive environment organised in an assembly-tree layout. In particular, this paper proposes a heuristic procedure to determine the number of kanbans and compares it with the traditional methods applied in manufacturing contexts. [ABSTRACT FROM AUTHOR]

In an environment of mass customisation where demand information can be placed in advance with sequencing orders, the question of the best use of this information arises in a supply chain. This situation led the authors to analyse the efficiency of current mechanisms of scheduling coordination when suppliers' processes are not completely reliable. Policies such as periodic replenishment or the kanban system, characterised by a replacement of the items to consume, cannot be exploited effectively with the current rules. This article presents and justifies new scheduling coordination rules allowing synchronous production in an unreliable environment. This new approach has been benchmarked in the automotive industry as an appropriate method to avoid stockouts and decrease the safety stock. [ABSTRACT FROM AUTHOR]

Several studies have shown that when both statistical fluctuations and dependent events exist, unbalanced production lines out-perform balanced lines. By definition, unbalanced lines have some amount of protective capacity built into them; however, little research exists to address the question of quantity and position of protective capacity necessary to counteract the impact of variation on system performance. This research seeks to improve our understanding concerning the shape of protective capacity in unbalanced lines when faced with variation in the form of unplanned machine downtime. Both Kanban and drum-buffer-rope (DBR) controlled lines are investigated. Results show that balancing the protective capacity yields superior results over both increasing and decreasing protective capacity shapes (holding average protective capacity equal). Results also show that Kanban lines behave differently than DBR lines. [ABSTRACT FROM AUTHOR]

This paper deals with the implementation of the Kanban system in a continuous product line of a tyre manufacturing plant. The paper also describes a practical approach to the design of Kanban card, board, container sizing, the number of Kanban, operating rules and day-to-day scheduling of machines using Kanban, and the necessary changes in a wage system to support its acceptability by workers on the shop floor. [ABSTRACT FROM AUTHOR]

The production system using kanban was pioneered by Toyota Motor Company in Japan and subsequently it was adopted by numerous other Japanese and US companies for applying the just-in-time manufacturing principles. This research studies a single-stage supply chain system that is controlled by kanban mechanism. The supply chain system is modelled as a mixed-integer nonlinear programming (MINLP) problem. It is solved optimally by branch-and-bound method to determine the number of kanbans, batch size, number of batches, and the total quantity over one period. Meanwhile, the kanban operation between two adjacent plants is worked out considering the factors of loading and unloading time, and transport time. Coupled with plant-wide efforts for cost control and management commitment to enhance other measures of performance, a logistics system for controlling the production as well as the supply chain system is developed, which results in minimizing the total cost of the supply chain system. The results show that the improvements in reduction of inventory, wasted labour, and customer service in a supply chain are accomplished through the kanban mechanism. [ABSTRACT FROM AUTHOR]

In a JIT manufacturing environment it may be desirable to learn from an archived history of data that contains information that reflects less than optimal factory performance. The purpose of this paper is to use rule induction to predict JIT factory performance from past data that reflects both poor (saturated or starved) and good (efficient) factory performance. Inductive learning techniques have previously been applied to JIT production systems (Markham et al., Computers and Industrial Engineering, 34, 717-726, 1998; Markham et al., International Journal of Manufacturing Technology Management, 11(4), 239-246, 2000), but these techniques were only applied to data sets that reflected a well-performing factory. This paper presents an approach based on inductive learning in a JIT manufacturing environment that (1) accurately classifies and predicts factory performance based on shop factors, and (2) identifies the important relationships between the shop factors that determine factory performance. An example application is presented in which the classification and regression tree (CART) technique is used to predict saturated, starved or efficient factory performance based on dynamic shop floor data. This means that the relationship between the variables that cause poor factory performance can be discovered and measures to assure efficient performance can then be taken. [ABSTRACT FROM AUTHOR]

Methods for planning and control of the flow of material in the manufacturing enterprise are more or less appropriate to use in a specific situation, mainly depending on the existing planning environment. How well they contribute to an effective material flow is also depending on how they are applied. This paper examines which material planning methods companies are using, to what extent these methods are perceived as efficiently supporting the operation, how the various methods are applied, and how the satisfied users apply the methods. The findings are based on a survey study carried out in 84 manufacturing companies in Sweden in 2000. From the results some conclusions concerning state-of-the-art application of material planning methods in the manufacturing industry are presented. A comparison with a similar study on the same population from 1993 is also conducted. The findings show that material requirements planning is generally the most used method. The most common ways to determine planning parameters are based on judgement and experiences. The majority of companies review the parameters less frequently than once a year. The satisfied users, however, use more analytical approaches and review parameters more frequently than others. [ABSTRACT FROM AUTHOR]

A simulation-based study is presented to compare the performance of a set of kanban allocation rules in a flexible manufacturing system (FMS) operating in a pull mode. This paper also presents a simulation-based direct search approach to determine the optimal number of kanbans and their simultaneous allocation to different part types. This paper presents a realistic cost function that includes a penalty for failing to meet the demand on time, and a penalty for rescheduling delivery of materials from vendors. The model captures limited flexibility in the form of operational flexibility in a FMS. Future extensions to this study are discussed. [ABSTRACT FROM AUTHOR]

Materials Requirement Planning (MRP) and JustIn-Time (JIT)/kanban are two widely used production scheduling and control (PS& C) methodologies in the manufacturing industry. MRP has better planning capabilities, while JIT has superior shop floor control capabilities. MRP is applicable to a wide range of manufacturing companies, while successful JIT/ kanban implementation is generally restricted to repetitive and serial manufacturing. Several hybrid MRP/JIT systems have been proposed by researchers and practitioners to combine the benefits from both methods, while eliminating some of their drawbacks. A few companies have successfully implemented customized hybrid systems. However, there are no 'generic' methods by which JIT/kanban can be combined with MRP. This paper introduces a generic and widely applicable JIT/ kanban-type shop floor extension to MRP. Further, it incorporates specific techniques that eliminate the drawbacks of JIT/kanban and enable it to be used with MRP in a broad range of manufacturing plants. The techniques include: (i) the Kanban Card Controller, which links the MRP output to the JIT/kanban input; (ii) the Kanban Prioritizer, an optimal scheduling methodology, which enables JIT to be used effectively in non-serial production facilities; and (iii) a dynamic lead time estimator which calculates lead time based on the most current shop floor parameters. [ABSTRACT FROM AUTHOR]