Effect of maintenance policies on the just-in-time production system

Using simulation, experimental design, and regression analysis, mathematical models are developed here to describe the effect that maintenance policy, machine unreliability, processing time variability, ratio of preventive maintenance time to processing time, ratio of minimal repair time to preventive maintenance time, and production line size have on various measures of performance, namely total production line output and production line variability of the just-in-time production system. The analysis of the data shows that under different situations, different maintenance policies do not have the same effect on the production line performance. The following conclusions were obtained; when the number of production machines is low (five machines or less), and/or when the ratio of minimal repair time to preventive maintenance time is high, maintenance policy III leads to a higher performance than maintenance policy II. Otherwise maintenance policy II, which is more sensitive to the change of the ratio of minimal repair time to preventive maintenance time, leads to a higher performance. The results of the study can be utilized in choosing a maintenance policy as a function of the production process parameters. Once a policy is chosen, the practitioner can select the most important factors to control under that policy in order to minimize the machine idle time, maximize the production process reliability, improve productivity, and therefore increase the production line performance.     

Increasing the production rate of a just-in-time production system with variable operation times

This paper examines a just-in-time (JIT) system with kanbans with three subassembly lines feeding a final assembly station. Variability in operation times exists and variability effects are reduced by increasing work in process levels or by unbalancing the subassembly lines through assignment of work content at each station. Of the several unbalancing methods that were analysed in this study, only the high-medium-low showed a consistent improvement in the output rate of the JIT production system. The output rates with unbalanced stations were always superior to the output rate of the perfectly balanced configurations used as controls. The extent of improvement over the output rate of balanced systems increased directly with the variability in operation times in final assembly and subassembly stations and inversely with the interstage buffer capacity allowed in the system.     

A comparative analysis of an MRP lot-for-lot system and a Kanban system for a multistage production operation

Japanese production methods and operational control techniques have been the subject of much recent attention from American production managers and the media. In this paper the Kanban aspect of the 'just-in-time' concept is analysed in order to ascertain the potential for scheduling in an ill-structured production operation and to compare its effectiveness with the traditional MRP lot-for-lot scheduling and control procedure. The analysis will be conducted using a hypothetical production operation that includes multiple workcentres, machines and product structures, and serial and assembly operations. Simulation model results are discussed and principles for selecting the more cost-effective system are outlined for the general MRP lot-for-lot versus Kanban scenarios.     

Evaluating artificial intelligence heuristics for a flexible Kanban system: simultaneous Kanban controlling and scheduling

This paper evaluates several artificial intelligence heuristics for a simultaneous Kanban controlling and scheduling on a flexible Kanban system. The objective of the problem is to minimise a total production cost that includes due date penalty, inventory, and machining costs. We show that the simultaneous Kanban controlling and scheduling is critical in minimising the total production cost (approximately 30% cost reduction over scheduling without a Kanban controlling). To identify the most effective search method for the simultaneous Kanban controlling and scheduling, we evaluated widely known artificial intelligence heuristics: genetic algorithm, simulated annealing, tabu search, and neighbourhood search. Computational results show that the tabu search performs the best in terms of solution quality. The tabu search also requires a much less computational time than the genetic algorithm and the simulated annealing. To further improve the solution quality and computational time for a simultaneous Kanban controlling and scheduling on a flexible Kanban system, we developed a two-stage tabu search. At the beginning of the tabu search process, an initial solution is constructed by utilising the customer due date information given by a decision support system. The two-stage tabu search performs better than the tabu search with a randomly generated initial solution in both the solution quality and computational time across all problem sizes. The difference in the solution quality is more pronounced at the early stages of the search.     

Sequencing problem for a mixed-model assembly line in the Toyota production system

The paper discusses a sequencing problem of a mixed-model assembly line in the Toyota Motor Corporation production system, which is well known as the Just-in-Time production system. Whenever a worker in the assembly line finds that he might fail to complete his operations within the work zone, he pushes a button to call an auxiliary worker who assists him in the operations. If he can complete the operations within his work zone with the help of the auxiliary worker, the line does not stop. Otherwise, the line stops. In the Toyota production system, it is very important to keep a constant rate of usage of every part used by the assembly line. Hence, there are two goals for the sequencing problem in the Toyota production system. The paper provides a new formulation for the sequencing problem with two goals. It considers the goal of keeping the constant rate of part usage as a constraint of the sequencing problem, and it formulates a sequencing problem of minimizing the total line stoppage time with auxiliary workers and the constraints for keeping the constant rate of part usage. Since this problem is NP-hard and the size of the practical problems at Toyota are huge, a two-phase approximation algorithm is proposed. Numerical examples show that the proposed algorithm is efficient and can find a good suboptimal solution.     

国有企业丰田生产方式本土化标准研究

以“准时生产JIT”和“自动化”作为两大支柱的丰田生产方式(TPS)凭借其完整、超常规、最具革命性的全新生产方式被称为“改变世界的机器”.精益生产、持续改善等专门用语出现在全球制造业并成为争相学习、效仿的对象.国有企业在TPS本土化的道路上由于缺乏对其本质的理解和研究,照搬全抄、形式主义的学习方式只能步履维艰.文章以史为鉴,在吸取丰田经验教训的基础上,提出国有企业学习TPS的标准与方法,为TPS本土化提供依据和方向.     

Line balancing in a just-in-time production environment: balancing multiple U-lines

The introduction of multiple, independent production lines has helped many firms to increase their production flexibility, provide for redundancy when equipment breaks down, reduce idle time and labor costs, and achieve many other benefits. This paper introduces and formalizes the multiple U-line balancing problem. Optimal solution methodologies are provided for Type I (minimize the number of stations for a given cycle time), Type II (minimize the cycle time for a given number of stations), and cost-minimization line-balancing problems. A branch-and-bound algorithm is also developed for the situation in which equipment requirements are dependent on the line configuration and the task assignment to stations. Computational results indicate that the greatest benefit of exploiting multiple lines occurs for smaller cycle-time problems that require higher output.     

Configuring a Kanban system using a discrete optimization of multiple stochastic responses

This paper investigates the development of a production control strategy for a custom door manufacturer. A Kanban system is developed for the production environment. Simulation and discrete optimization techniques are applied to configure the system. The paper demonstrates that a Kanban approach can be applied to a production environment which neither represents a pure flow shop nor contains balanced production processes. It also highlights the difficulties that can arise in performing a discrete optimization upon conflicting multiple stochastic responses.     

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.     

Modelling and simulation of just-in-time flexible systems

The increasing worldwide competition requires economical manufacture, high quality and short delivery time. The Just-In-time (JIT) philosophy of manufacturing is increasingly being considered by manufacturing organizations, as a response to the increased pressure to supply high quality products with short delivery times and at low cost. A very simple shop floor control system that was developed by Toyota in the 1970s specifically for their Just-In-Time assembly plant, has received considerable attention in the Western World, and is known as the ‘kanban’ system (literally translated as ‘card’ system). Japan’s success has prompted many scholars and practitioners, to turn their attention to Japanese management practices. This article is to address the modelling, simulation and implementation issues of Just-In-Time in flexible manufacturing environments. Priority nets are used for modelling and analysis of the kanban system. A large number of simulation runs are conducted/presented to probe the behaviour of the system, with respect to different parameter changes.     

Optimizing production smoothing decisions via batch selection for mixed-model just-in-time manufacturing systems with arbitrary setup and processing times

This paper is concerned with the production smoothing problem that arises in the context of just-in-time manufacturing systems. The production smoothing problem can be solved by employing a two-phase solution methodology, where optimal batch sizes for the products and a sequence for these batches are specified in the first and second phases, respectively. In this paper, we focus on the problem of selecting optimal batch sizes for the products. We propose a dynamic programming (DP) algorithm for the exact solution of the problem. Our computational experiments demonstrate that the DP approach requires significant computational effort, rendering its use in a real environment impractical. We develop three meta-heuristics for the near-optimal solution of the problem, namely strategic oscillation, scatter search and path relinking. The efficiency and efficacy of the methods are tested via a computational study. The computational results show that the meta-heuristic methods considered in this paper provide near-optimal solutions for the problem within several minutes. In particular, the path relinking method can be used for the planning of mixed-model manufacturing systems in real time with its negligible computational requirement and high solution quality.     

丰田生产方式和工业工程

简要分析了工业工程的特性和丰田生产方式的本质，并以图表的形式给出了两者的关系，最扣提出，当前应着重宣传和推广基础工业工程。     

A note on ‘Economic manufacturing quantity in a just-in-time delivery system’

This comment is made on a paper by Golhar and Sarker who showed that it is economically advantageous for a supplier to participate in the just-in-time delivery system. Although the general conclusions are correct, one of the conditions under which the results are obtained is not necessary. Also, the optimal production quantity is not independent of delivery quantity though their interdependency is in a rather indirect manner.     

看板管理在轮胎行业的应用

将价值流图析技术运用到轮胎制造行业,找出现场半制品库存过高的实际问题。再通过调整下游工序的加工设备,均衡化地组织上游设备的生产。同时采用看板管理的方式,在现场设置合理的半制品库存,以后道工序拉动前道工序生产的方式,最终实现半制品库存的降低。     

看板管理在企业中的应用研究

借鉴看板管理思想,结合企业的实际情况,论述了使用看板的8个条件、6个规则和4个作用,详细介绍了各种看板的形式、内容、计算公式和使用规则,同时引入了看板箱和物料超市的配套概念,从整体上阐述了看板管理的操作模式.     

看板控制系统零部件厂内搬运路线的优化

从看板控制系统厂内各零部件运输路线没有进行优化而导致了人力、物力的浪费问题着手，以降低厂内总搬运成本为出发点，提出并论述了设立临时中转站的优化方法及这样的临时中转站的存在的理论证明，并指出了如何寻找站点的方法。该优化方法是可以对到相应的资源进行调配，以达到减少厂内总搬运成本这一目的。     

基于WITNESS的看板生产系统建模仿真与优化研究

基于WITNESS对看板生产系统进行了PetriNet建模,对wITNESS看板生产系统的基本假设、系统绩效指标选取、模型参数优化与仿真结果进行了分析,应用WITNESS建立了一个单产品、多阶段、混联的JIT生产系统仿真模型,通过仿真实验,研究分析了在安全系数和变异系数两方面的随机变量在不同的组合下对系统绩效指标的影响．