Determining the number of kanbans in a multiproduct,multistage production system

Significant reductions in setup and lead times reported by the Japanese have led Western manufacturers to rethink the need for complex computer-based MRP systems. Consequently, many of these firms have adopted some form of kanban for shop floor control. In this paper, a planning model is developed to assist line managers in determining an optimal kanban policy at each workstation. The objective is to work within the capacity of the system to balance cost and service over the planning horizon. The model takes the form of a mixed integer linear program, and is solved with standard techniques. When no shortages are permitted, a number of alternative formulations are introduced that sharply reduce the computational burden. Results are presented for an example based on the assembly of printed wire boards at Texas Instruments' Austin plant.     

Application of hierarchical production planning in a multiproduct,multimachine environment

The paper proposes a model designed to deal with a hierarchical production planning/scheduling problem in a multiproduct, multimachine environment with sequence dependent set-ups. Problems of this type have been known to be difficult to solve owing to their heavy computational burden. The model proposed here incorporates the concept of expected set-up costs and the expertise of manager input at the aggregate planning level in order significantly to reduce the computational burden. When tested with the actual plant data, the model outperformed other models reported in the literature.     

Optimal and heuristic inspection schedules for multistage production systems

Consider a single inspection facility that can be quickly switched among multiple inspection tasks. It can be used (for example) for detecting malfunction (or down state) production stages in a multistage production system. We assume that a properly working (or up state) production stage moves to a down state in any period with fixed probability. The stage then stays down until it is inspected and immediately restored back to an up state. Our purpose is to schedule inspections among the different production stages so as to maximize the fraction of good items produced. An optimal inspection schedule for a two stage production system is provided. For the general case of more than two stages, four heuristics are compared. We conclude that the proposed dynamic schedule is easy to derive, always feasible, and outperforms the static schedules.     

An investigation of multiproduct,multimachine production scheduling and inventory control of a flow-shop system

Unlike most of the previous studies of the multiproduct, multimachine systems, hero an attempt is made to consider the man-machine overtime and idleness costs together with the usual inventory-related costs (the set-up costs, carrying costs, and back-logging costs). The major assumptions of the model include: (a) demand for each product is captive and constant; (b) single or multiple facility work centres may be employed: (c) the total manufacturing operations of any single product must be completed before another product can be started; (d) all the manufacturing facilities are set up simultaneously for each of the products and its production can be started only after all the machines are ready. The annual total variable cost function is found to be very complex. Therefore, a recursive algorithm is required to solve this function for the values of optimal produetion-cycle-thnes of the individual products, T_j ^*,s . As the facilities are assumed to produce only one product at a time, these cycle time values need to be fitted into a production schedule so that there is no conflict between any two products on any of the machines and so that any modification in the values of T_j ^*,s result in the least increase of the system's total annual variable costs. Such total annual variable costs, computed with the help of this model and its alogrithm for 15 different situations, are compared with those provided by two other known models. Each time this model performs significantly better than the other two.     

Optimal policies in multiproduct inventory models

Summary We consider a period review, dynamic multiproduct inventory model with stochastic demand, in which the cost of ordering consists of linear portions for each product as well as a nonlinear term. This nonlinear term depends for example, on the products we order. We prove the existence of an optimal policy and characterize such a policy. We show that an optimal policy reduces to the well-known (, S)-policy, if we spezialise the nonlinear ordering cost in a proper way. Finite horizon results are given.

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Zusammenfassung Wir betrachten ein periodisch kontrolliertes dynamisches Mehrprodukt-Lagerhaltungsmodell mit stochastischem Bedarf, bei dem sich die Bestellkosten aus einem linearen und einem nichtlinearen Anteil zusammensetzen. Der nichtlineare Anteil kann z. B. davon abhängen, welche Produkte bestellt werden. Es wird die Existenz einer optimalen Bestellpolitik gezeigt. Außerdem werden Eigenschaften einer solchen Politik nachgewiesen. Wir zeigen, daß bei Spezialisierung der nichtlinearen Bestellkosten eine optimale Politik eine (, S)-Politik ist. Die Ergebnisse beziehen sich auf den endlichen Planungshorizont.

     

Economic design of an attributes control system for a multistage serial production process

A model for the economic design of an np-control system integrated within a multiple stage serial production process is presented. The total expected quality control cost includes the costs of sampling, the costs of investigating an out-of-control alarm and possibly correcting an assignable cause(s), and the costs associated with the production of non-conforming items. The model is represented as a directed network with decision variables of sample size, rejection number and frequency of sampling occurring at each stage of the process. A combination of dynamic programming and direct search techniques is applied to determine the set of sampling policies which yield minimum total expected cost. Numerical examples and results of a sensitivity analysis are reported.     

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.     

Optimal hybrid push/pull control strategies for a parallel multistage system: Part II

The strategies developed in part I of this paper are extended to a more general case in part II. Based on the optimal policy structure of a Markov Decision Process model and by control and information structure analysis, we propose that the ‘best’ strategy for a general series/parallel multistage (assembly) production/inventory system is to use a push (MRP) strategy at all initial stages of the system and a pull (JIT) strategy at all the other downstream stages. As viewed from the information structure, this recommended strategy is a group of decentralized controllers with a centralized coordinator.     

Optimized production planning model for a multi-plant cultivation system under uncertainty

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.     

An integrated model for inventory and production planning in a two-stage hybrid production system

A two-stage hybrid flow-shop production system is considered. The first stage is a process production system and the second stage is a job-shop production system. The two stages are separated by an intermediate warehouse to introduce flexibility (some independence) in the planning of production at both stages. The inventory level at the warehouse should be optimized to provide a trade-off between the cost of carrying the inventory of the semi-finished products, the minimum batch size requirement in the first stage, and the required service level at the second stage. An integrated model for planning the production in these hybrid flow-shop production systems types is developed. The objectives of optimizing the production and inventory costs at the two stages of the system, including the warehouse, while satisfying customer demands, are considered. An algorithm to solve the suggested model is described in detail, and a solution is provided for a real world case, which has inspired the study. A computational study to measure the performance of the approach was also carried out and the results are reported.     

Stage due date planning for multistage assembly systems

Coordinating due dates of operations throughout all stages of manufacturing and assembly is a problem especially for complex product structures with uncertainties in process times. A recursive procedure is described to estimate distributions of completion times for each operation. Stage due dates are then calculated to meet specified service targets. Compared with plans from existing heuristic methods, there are considerable improvements in meeting service targets and reducing costs. Simulations demonstrate that the method is effective for complex assemblies produced in low volumes by capital goods companies.     

Experimental realization of a multiproduct photorefractive correlation system for temporal signals

The design and operation of a multidimensional photorefractive correlator is described. With a photorefractive medium as the integrator, this system effects the correlation of up to four time-evolving signals. The holographic correlation volume is viewed by projection onto a two-dimensional detector. The correlator is designed for use with binary-phase signals, especially pseudorandom noise sequences.     

Optimal preventive maintenance in a production inventory system

We consider a production inventory system that produces a single product type, and inventory is maintained according to an (S, s) policy. Exogenous demand for the product arrives according to a random process. Unsatisfied demands are not back ordered. Such a make-to-stock production inventory policy is found very commonly in discrete part manufacturing industry, e.g., automotive spare parts manufacturing. It is assumed that the demand arrival process is Poisson. Also, the unit production time, the time between failures, and the repair and maintenance times are assumed to have general probability distributions. We conjecture that, for any such system, the down time due to failures can be reduced through preventive maintenance resulting in possible increase in the system performance. We develop a mathematical model of the system, and derive expressions for several performance measures. One such measure (cost benefit) is used as the basis for optimal determination of the maintenance parameters. The model application is explained via detailed study of 21 variants of a numerical example problem. The optimal maintenance policies (obtained using a numerical search technique) vary widely depending on the problem parameters. Plots of the cost benefit versus the system characteristic parameters (such as, demand arrival rate, failure rate, production rate, etc.) reveal the parameter sensitivities. The results show that the actual values of the failure and maintenance costs, and their ratio are significant in determining the sensitivities of the system parameters.     

Optimal production plan for a multi-products manufacturing system with production rate dependent failure rate

This study deals with the problem of dependence between production and failure rates in the context of a multi-product manufacturing system. It provides an answer about how to produce (i.e. the production rates) and what to produce (i.e. which product) over a finite horizon of H periods of equal length. We consider a single randomly failing and repairable manufacturing system producing two products P_a and P_b . The product P_a is produced to supply the strategic demand d(k) of the principal customer via a buffer stock S over k periods (k?=?1,?2,?…?,?H). The second product P_b is produced to meet a secondary but very profitable demand. It is produced during a given interval at the end of each period k. We develop a genetic algorithm to determine simultaneously the optimal production rate of the first product during each period k and the optimal duration of the production interval of the second product, maximising the total expected profit.     

Inspection allocation for multistage deteriorating production systems

The paper deals with the layout and operation of an inspection system used for detecting malfunctioning processors in a multistage production system. This problem involves three inter-related decisions: (i) the overall inspection capacity; (ii) the assignment of inspection tasks to inspectors; and (iii) the scheduling of the inspector's tasks. These decisions require a trade-off between the cost of inspectors and the loss associated with non-conforming products. A hierarchical heuristic solution procedure is proposed to support these three related decisions. Numerical experiments demonstrate the performance of the heuristic, showing that solution criteria are very close to their lower bounds. Although we use production terminology, the results might be applicable to any organization, which inspects and maintains a variety of characteristics of its branches or activities.     

Inspection allocation for multistage deteriorating production systems

The paper deals with the layout and operation of an inspection system used for detecting malfunctioning processors in a multistage production system. This problem involves three inter-related decisions: (i) the overall inspection capacity; (ii) the assignment of inspection tasks to inspectors; and (iii) the scheduling of the inspector's tasks. These decisions require a trade-off between the cost of inspectors and the loss associated with non-conforming products. A hierarchical heuristic solution procedure is proposed to support these three related decisions. Numerical experiments demonstrate the performance of the heuristic, showing that solution criteria are very close to their lower bounds. Although we use production terminology, the results might be applicable to any organization, which inspects and maintains a variety of characteristics of its branches or activities.     

Formulation for a fixed-charge,separable nonlinear production planning problem

A production planning problem for which the objective function contains both separable and fixed-charge components is formulated under the assumptions of separable constraint functions and a- minimum production level. It is shown that for this problem, the well known application of the λ separation technique can be extended to allow the separation variables, λ, to represent the fixed charge component as well as the nonlinear components of the objective function. The result is the formulation of an approximating problem that has a degree of solution complexity comparable to that of usual separable programs. An application of such formulation to the electric utility generation scheduling problem is presented.     

Optimal preventive maintenance policies in a serial production system

There have been many publications dealing with preventive maintenance policies for stochastically deteriorating systems. However, most of them study systems having one device subject to failure. Much of the limited research dealing with multi-device production systems has been conducted through simulation experiments. In this paper, the preventive maintenance problem for serial production systems is formulated as a mathematical model. This formulation permits management to analyse the impact of a preventive maintenance policy on a serial production system without resorting to simulation. Numerical examples are used to provide managerial implications for maintaining a serial production system. The results show that the operating characteristics of the stations are interrelated; therefore, it is important to examine the joint effects of a maintenance policy on the various stations of the production system simultaneously rather than study each station separately.     

Optimal economic production quantity policy for a parallel system with repair,rework, free-repair warranty and maintenance

Hot standby redundancy maintains the working order of a system, repairs offer restoration in case of failure, and preventive maintenance (PM) prevents trouble. Warranties provide assurance to customers, and a superior warranty signifies higher product quality. The running costs of redundancy, maintenance and warranties influence decisions during product manufacture. Therefore, this paper presents an economic production quantity (EPQ) model for a parallel system with maintenance, production, and free-repair warranty (FRW) programmes. The production system begins with a basic unit and produces conforming items. PM is performed after the production run period and is classified as imperfect or perfect. If the basic unit fails, it is repaired and returned to operation after perfect PM; the spare unit is online only during the repair time of the basic unit. The spare will produce some number of defective goods, which are reworked in the same inventory cycle. The hot spare is minimally repaired if it fails in its standby or online mode. In this study, an inferior item is defined as one that satisfies specifications on inspection and is usable but is likely to incur postsale servicing costs when sold under an FRW. The total cost of this EPQ model includes setup, holding, PM, restoration, minimal repair, and warranty costs. The optimal production runtime is determined by minimising the total cost. Several cases are discussed in this paper, and the proposed model is illustrated using a numerical example and sensitivity.     

Differential evolution algorithm for static and multistage transmission expansion planning

A novel differential evolution algorithm (DEA) is applied directly to the DC power flow-based model in order to efficiently solve the problems of static and multistage transmission expansion planning (TEP). The purpose of TEP is to minimise the transmission investment cost associated with the technical operation and economical constraints. Mathematically, long-term TEP using the DC model is a mixed integer nonlinear programming problem that is difficult to solve for large-scale real-world transmission networks. In addition, the static TEP problem is considered both with and without the resizing of power generation in this research. The efficiency of the proposed method is initially demonstrated via the analysis of low, medium and high complexity transmission network test cases. The analysis is performed within the mathematical programming environment of MATLAB using both DEA and conventional genetic algorithm and a detailed comparative study is presented.