Optimal method for changing the number of kanbans in the e -Kanban system and its applications

The Toyota Motor Corporation has recently developed a new kanban system called ‘e-Kanban’, which is a parts ordering information system that operates within the communications network established between Toyota and its suppliers. One of the goals for developing the e-Kanban system was to introduce an efficient means for properly changing the number of kanbans once the required number has been calculated, as changing the number of kanbans in the kanban system directly affects the order quantity. Consequently, it is very important to monitor carefully and control changes in the number of kanbans. The paper investigates and proposes an effective method for changing the number of kanbans using the e-Kanban system. Applying this method to three problems, it is shown that the e-Kanban system can be implemented more efficiently and effectively than the original kanban system.     

Toyota production system and Kanban system Materialization of just-in-time and respect-for-human system

The Toyota Production System and Kanban System introduced in this paper was developed by the Vice-President of Toyota Motor Company, Mr. Taiiohi Ohno, and it was under his guidance that these unique production systems have become deeply rooted in Toyota Motor Company in the past 20 years. There are two major distinctive features in these systems. One of these is the ‘just-in-time production ’, a specially important factor in an assembly industry such as automotive manufacturing. In this type of production, “ only the necessary products, at the necessary time, in necessary quantity ” are manufactured, and in addition, the stock on hand is held down to a minimum. Second, the System is the ‘respect-for-human’ system where the workers are allowed to display in full their capabilities through active participation in running and improving their own workshops.     

The effect of sudden material handling system breakdown on the performance of a JIT system

In this paper we explore the impact of sudden breakdown of the material handling system on the performance of a traditional kanban system (TKS). TKS, which is an element of the just-in-time system, is designed to operate in an ideal environment such as constant processing times and uninterrupted processing. However, in a real life environment, the TKS could be subjected to various unpredictable factors including stochastic processing times and process interruption due to equipment failure. These factors would seriously strain the performance of TKS. We consider a TKS in which some stations are dependent on a material handling system to move parts between them. We study the effect of a sudden breakdown of such a material handling system on the performance of the TKS. In addition, we also study a newly developed kanban system (which dynamically and systematically manipulates the number of kanbans in order to offset the blocking and starvation caused by these factors during a production cycle) under the same conditions. We refer to the new system as the 'flexible kanban system' (FKS). We compare the overall performances of the TKS and FKS by considering a variety of cases. We present the solution procedure, results and discussion for these cases.     

Flexible kanbans to enhance volume flexibility in a JIT environment: a simulation based comparison via ANNs

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.     

Kanban number optimisation in a supermarket warehouse feeding a mixed-model assembly system

Following just-in-time principles, a growing number of manufacturers are adopting the so-called supermarket concept. Supermarkets are decentralised storage areas scattered throughout the shopfloor that serve as an intermediate store for parts required by nearby assembly lines. From these stores, a certain number of handling operators deliver parts from the supermarket to, and collect empty bins from, assembly stations. Finally, they return to the supermarket and are refilled for their next tours. The assembly stations are typically refilled from the supermarket through the constant replacement of the consumed parts pulled by the kanban system. Considering a mixed model assembly system composed of different assembly lines, feeding problems can occur as an effect of the replenishment lead time, of the production mix variation, of the commonality between the different models assembled. The aims of this paper are (i) to highlight how the supermarket/multi-mixed assembly-line system presents specific attributes that prohibit the simple application of well-known kanban dimensioning formulations and (ii) to provide an innovative procedure to optimally set all decision variables related to such a feeding system.     

An overview of design and operational issues of kanban systems

We present a literature review and classification of techniques to determine both the design parameters and kanban sequences for just-in-time manufacturing systems. We summarize the model structures, decision variables, performance measures and assumptions in a tabular format. It is important to state that there is a significant relationship between the design parameters, such as the number of kanbans and kanban sizes, and the scheduling decisions in a multiitem, multi-stage, multi-horizon kanban system. An experimental design is developed to evaluate the impact of operational issues, such as sequencing rules and actual lead times on the design parameters.     

The extended kanban control system for production coordination of assembly manufacturing systems

In assembly manufacturing systems there are points in the production process where several component parts are put together in areas called assembly cells so as to form more complex parts called subassemblies. In this paper, we present and compare two variants of the Extended Kanban Control System (EKCS) - a recently developed pull production control mechanism that combines base stock and kanban control - for the production coordination of assembly manufacturing systems. In both variants, the production of a new subassembly is authorized only when an assembly kanban is available. Assembly kanbans become available when finished subassemblies are consumed. If an assembly kanban is available, in the first variant, each component part of a subassembly is released into the assembly cell as soon as itis available (independent release). In the second variant, however, it is released only when allother component parts also become available (simultaneous release). In both variants, when a component part is released into the assembly cell, it releases its kanban, thus authorizing the production of a new component part.     

一种实现小批量准时化生产的可视化电子看板系统

针对传统看板方式不适用于多品种、小批量订单生产的诸多问题,提出了一种新的、基于可视化电子看板技术的解决方案,使得准时化生产方式能成功运用于多品种、小批量订单的市场环境。以电子产品的生产场景为例,采用过程分析的方法,进行了新看板运行流程的设计,提出了可视化电子看板系统的结构、关键技术和适用环境条件。     

A stochastic model of an unreliable kanban production system

We analyze a stochastic model of a production line withk stations (machines) in series. There are finitecapacity buffers between the machines and at the end of the line. The movement of the workpieces through the line is demand-driven, i.e. we deal with a pull (kanban) production system. Processing times are assumed to be deterministic and constant. There are two sources of randomness in the model: Demand for workpieces from outside is stochastic, and the machines may break down (and then be repaired) with a given probability. A demand from outside is lost if the final buffer is empty. This system is described by a discrete-time Markov chain. The steadystate distribution is given for k=1. This is the basis of a decomposition algorithm which approximates the throughput of the line and the percentage of satisfied demand for arbitraryk. A comparison with simulation results shows that this algorithm is very accurate.     

Stochastic coloured Petri net (SCPN) models of traditional and flexible kanban systems

Modelling and analysis of kanban-controlled (just-in-time) production systems under realistic assumptions presents a number of challenges, including the ability to conduct both qualitative and quantitative analysis, and the ability to model control policies. These challenges are due, in part, to station interdependence, blocking and starvation due to limited buffer spaces, and the necessity of modelling both material and kanban flows. Petri nets (PNs) have recently emerged as a promising approach for modelling manufacturing systems. PNs are a graphical and mathematical technique useful for modelling concurrent, asynchronous, distributed, parallel, non-deterministic and stochastic systems. PN models can be analysed to determine both their qualitative and quantitative properties. In this paper, we develop stochastic, coloured PN (SCPN) models of a JIT system utilizing two different kanban control policies: a traditional kanban system (TKS) policy and a flexible kanban system (FKS) policy. The resulting models can be used to represent JIT systems of arbitrary size, producing single or multiple types of products, with fixed order points 1. The models are shown to be live and bounded, and can be simulated to produce quantitative results. Sample simulation results are presented to illustrate the models' capabilities.     

Algorithms for the design of a multi-stage adaptive kanban system

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.     

A simulation study of container size in two-card kanban systems

Setting container sizes is one of the first decisions that users of kanban systems must address. Yet researchers have largely assumed container sizes to be given. This paper investigates the effect of container size on average inventory and customer service levels in a two-card kanban system processing multiple part types. Container size and the number of kanbans are varied in tandem so that total in-process inventory capacity remains constant. Simulation results show that smaller containers lead to smaller average total inventories. The surprise is that smaller containers do not always lead to poorer average customer service. Smaller container sizes can lead to better average customer service when the costs of greater total setup time are offset by the benefits of more frequent material handling, that is less frequent station material starvation, and improved finished goods part mix. This occurs primarily when container size is larger than average finished-goods order size and when setup times are relatively short.     

Analysis of production control systems kanban and CONWIP

In this paper we describe and classify different pull production systems. The production control systems kanban and CONWIP are then analysed with respect to production rate and average W1P. We examine single product flow lines with exponential service time distributions and unlimited demand at the final buffer (saturated lines). We show that the distribution of cards (kanbans) has a significant effect on the performance of kanban systems. Different types of kanban control mechanisms show equivalent performance data, if the distribution pattern is adapted accordingly. Our research shows that the kanban system is more flexible with respect to a given objective than the CONWIP system, because in addition to the total card number the card distribution is a control parameter. Moreover for a given production rate the average WIP is lower in a kanban system than in a CONWIP system. We identify the average WIP in the interstage buffers as important parameter and describe the ‘WIP bowl phenomenon’ as result of optimum card distributions. Concluding remarks and directions for future research conclude the paper.     

THE KANBAN ASSIGNMENT PROBLEM IN SERIAL JUST-IN-TIME PRODUCTION SYSTEMS

This paper examines multi-stage serial just-in-time production systems that use kanbans as a means of communicating the production needs of each stage of operation. The kanban-controlled system is a linked-demand system. A recursive function is presented which computes the number of kanbans required for all stages of a serial production system. This function is used to compute a lower bound on the expected fill rate for an arbitrary kanban assignment.     

Investigating the factors influencing the shop performance in a job shop environment with kanban-based production control

In this paper, we intended to explore three research questions related to applying just-in-time (JIT) manufacturing techniques in a job shop environment with the kanban-based production control. Simulation experiments were performed and the results were analysed using a statistical method, planned comparison. We found that the adoption of cellular layout in a job shop with the kanban system should only be considered if the amount of setup time reduction achievable through cellular manufacturing is medium to large; otherwise, functional layout should be adopted. In addition, moving parts in batches within cells was found to be more advantageous than moving parts one piece at a time. Only minor effects of material handling speed on the shop performance were identified.     

In-plant material buffer sizes for pull system and level-material-shipping environments in the automotive industry

Traditionally automotive assembly plants operate with at least two weeks of frozen vehicle orders enabling them to calculate the amount of material needed for the next two weeks. Implementing a pull system between the plant and its customers, and level-material-shipping between the plant and its suppliers, changes the amount of material buffer needed within the assembly plant. The pull system eliminates the frozen vehicle-order schedule, without which plants cannot calculate the material needed, but must use inventory to buffer the line from random demand. Level-material-shipping, a just-in-time principle that provides suppliers with a constant shipping schedule, forces plants to use material inventory to buffer the line from un-level demand for parts resulting from un-level production or an un-level model mix. We model these effects to derive formulas for the buffer needed to provide a given service level in the face of demand variability, un-level production, and un-level model-mix.     

Preventive maintenance and optimal buffer inventory for products sold with warranty in an imperfect production system

This paper deals with an imperfect production system with allowable shortages due to regular preventive maintenance for products sold with free minimal repair warranty. Preventive maintenance is an essential factor of the just-in-time structure that results in a shutdown of the production process for a certain period of time. During such an interruption, a buffer stock is needed to adjust the market demand. The study includes the possibility of imperfect production and determines the optimum buffer level and production run time by trading off the holding cost, shortage cost, rework cost, repair cost for warranty, labour/energy costs, material cost and cost for maintenance so that the cost per unit product is minimised.     

Generic kanban systems for dynamic environments

Kanbans have shown successful results in lowering inventory and shortening lead time in repetitive production systems. Unfortunately, such systems are not applicable to production environments with dynamic characteristics. Here a modified kanban system, the generic kanban system, is proposed for such dynamic environments. The generic kanban system behaves similarly to the push system except that it is more flexible with respect to system performance and more robust as to the location of the bottleneck. The simulation results that the generic kanban system is dominant over the dedicated kanban system and the CONWIP system. The adaptability of such a system to dynamic environments is justified.     

A neural network procedure for kanban allocation in JIT production control systems

In this paper, we develop a Generalized Systematic Procedure (GSP) for determining the optimum kanban allocation in just-in-time (JIT) controlled production lines. This procedure is based on a meta-model that incorporates (1) a factorial design approach to select the appropriate kanban combinations, (2) a simulation model to simulate the JIT production line, and (3) a trained neural network model to evaluate the line performance over the entire domain of possible kanban combinations. The GSP is then applied to a case problem and the results are presented.     

Prioritization of kanbans in the case of a single station serving multiple downstream stations

When implementing the kanban method in non-serial production lines, an interesting prioritization problem arises. Often a single server station will be linked with M different downstream stations via M separate kanban loops. Then the K-priority problem may be described as determining which kanban card should be processed next, given that empty cards are waiting in more than one loop. The objective in prioritizing the kanbans is to reduce back order or shortage costs and inventory costs at the downstream stations. Utilizing the theory of Markovian decision process and dynamic programming concepts, a solution to the K-priority problem is developed. This solution is labelled the K-rule, and was found to outperform the first-come-first-served and longest queue rules, plus a cost inclusive heuristic rule, in experimental tests,