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This paper provides procedures for setting optimal, or near-optimal, basestock levels in a multi-product system with setups and random yield. The procedures are derived using a novel polling system model of the system that contains both queues for production order and queues for temporary storage of rework orders with routing occurring between these two types of queues. Both systems with backlogging and lost sales are analyzed using existing work on polling models with routing and possibly finite buffers. For a system with backlogging, we provide a cost function that is minimized by solving a set of single-item newsvendor problems. In systems with lost sales, each queue is given a finite buffer equal to the basestock level and excess demand is lost. We provide a cost function and show that finding optimal solutions for large problems is not tractable; thus, we provide a heuristic for finding the basestock levels and demonstrate the effectiveness of the heuristic and accuracy of the cost approximation through numerical tests. Keywords: Basestock, random yield, multi-product, setups, 1. Introduction Most production systems are characterized by multiple uncertainties, which cause output to be highly variable. When yield is random, not only is the usable quantity uncertain, but the [...]

Deadlock prevention is a crucial step in the modeling of flexible manufacturing systems. In the Petri net framework, deadlock prevention policies based on siphon control are often employed, since it is easy to specify generalized mutual exclusion constraints that avoid the emptying of siphons. However, such policies may require an excessive computational load and result in impractical oversized control subnets. This is often a consequence of the redundancy in the control conditions derived from siphons. In this paper, a novel method is proposed that provides small size controllers, based on a set covering approach that conveniently relates siphons and markings. Some examples are provided to demonstrate the feasibility of the approach and to compare it with other methods proposed in the literature. Index Terms--Deadlock prevention, flexible manufacturing systems, Petri nets, siphons.

One key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line's performance. Keywords: bottleneck analysis, bottleneck inertia, real-time production control, throughput simulation [DOI: 10.1115/1.2673666]

A study on assessment of facility performance during multi-item production is presented.

This note considers a failure-prone manufacturing system producing one part-type in discrete mode. The problem is to find the optimal integrated production and backordering policy, in which control decisions include how much the production rate should take when the machine is up and whether an unmet demand should be backorder or rejected. The optimal policy is proved to be a threshold control and can be characterized by three threshold parameters for both discounted cost and long-run average cost cases. The structural relationships between three threshold parameters are established. It is found that the completely backordering policy may be optimal for the discounted cost but will never be optimal for the average cost. In addition, the explicit form of the stationary distribution under such threshold policy is derived, which is then be used to calculate interesting steady-state performance measures and seek the optimal threshold values. A numerical example illustrates the results. Index Terms--Backordering, failure-prone manufacturing system, production control, stationary distribution, threshold control.

Byline: Lars Monch (1), Marcel Stehli (1) Keywords: Agent-based analysis and design; Frameworks; Production control; Complex manufacturing systems; Software development Abstract: In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study. Author Affiliation: (1) Institute of Information Systems, Technical University of Ilmenau, Helmholtzplatz 3, 98684, Ilmenau, Germany Article History: Registration Date: 14/11/2005 Online Date: 07/12/2005

In this paper, we consider the joint management of finished goods inventory and demand for a product in a make-to-stock production system. The production process is random with controllable mean rate, and the demand process is stochastic with changeable mean rate dependent on the sale price being high or low. The management issue is how to dynamically adjust the production rate and the sale price to maximize the long run total discounted profit. We show that: 1) the optimal management of the finished goods inventory follows a base stock policy: when the inventory is above certain base stock level, the production is halted; otherwise the maximum production rate is deployed to raise the inventory to the base stock level; and 2) the optimal management of the demand process follows a price switch threshold policy: when the inventory is above the threshold, the low sale price is chosen to sell the product; and below it the high price is chosen to reduce the demand. We provide an algorithm to compute the base stock level and price switch threshold. Extension to multiple price choices is given with proofs highlighted. Index Terms--Demand process management, dynamic pricing, finished goods inventory management, make-to-stock production, Poisson demand, production control.

Study of scenario-based robustness of production management systems in four business enterprises is discussed. Risk and sensitivity analyses are also presented for the production management systems of these companies.

Byline: Chih-Chou Chiu (1), Yuehjen E. Shao (2), Tian-Shyug Lee (3), Ker-Ming Lee (4) Keywords: Statistical process control; engineering process control; minimum mean squared error control; neural networks; identification of process disturbance Abstract: Since solely using statistical process control (SPC) and engineering process control (EPC) cannot optimally control the manufacturing process, lots of studies have been devoted to the integrated use of SPC and EPC. The majority of these studies have reported that the integrated approach has better performance than that by using only SPC or EPC. Almost all these studies have assumed that the assignable causes of process disturbance can be identified and removed by SPC techniques. However, these techniques are typically time-consuming and thus make the search hard to implement in practice. In this paper, the EPC and neural network scheme were integrated in identifying the assignable causes of the underlying disturbance. For finding the appropriate setup of the networks' parameters, such as the number of hidden nodes and the suitable input variables, the all-possible-regression selection procedure is applied. For comparison, two SPC charts, Shewhart and cumulative sum (Cusum) charts were also developed for the same data sets. As the results reveal, the proposed approaches outperform the other methods and the shift of disturbance can be identified successfully. Author Affiliation: (1) Institute of Commerce Automation and Management, National Taipei University of Technology, Taipei, Taiwan, R.O.C (2) Department of Statistics and Information Sciences, Fu-Jen Catholic University Taipei, Taiwan, R.O.C (3) Department of Business Administration, Fu-Jen Catholic University Taipei, Taiwan, R.O.C (4) Institute of Applied Statistics, Fu-Jen Catholic University Taipei, Taiwan, R.O.C Article History: Registration Date: 05/10/2004

This paper focuses on lot release control and scheduling problems in a semiconductor wafer fab producing multiple products that have different due dates and different process flows. For lot release control, it is necessary to determine the type of a wafer lot and the time to release wafers into the wafer fab, while it is necessary to determine sequences of processing waiting lots in front of workstations for lot scheduling. New dispatching rules are developed for lot release control and scheduling considering special features of the wafer fabrication process. Simulation experiments are carried out to test the dispatching rules. Results show that lot release control and lot scheduling at photolithography workstations are more important than scheduling at other workstations. Also, it is shown that new dispatching rules work better in terms of tardiness of orders than existing rules such as the EDD (earliest due date) rule and other well-known dispatching rules for multimachine scheduling. Index Terms - Production control, scheduling, simulation.

Final product inspection of a multi-attribute product, such as in the electronic assembly industry, involves expensive facilities. The correlation among attributes may be used for reducing the efforts needed for screening the products; however, engineers without an appropriate statistical-economical analysis tools do not take risks, and they designate full inspection of each item. We propose a double stage inspection program for reducing inspection efforts. Assuming that the joint distribution is known, the conditional probability that a product is 'good' may be evaluated conditional upon the observation of the product's first-stage inspected quality attributes. Then, an expected cost minimization is implemented in order to decide whether a second inspection stage is required or a classification should be based solely on the first inspection stage. The cost factors include inspection and false classification. The method is illustrated on a real data set from a particular electronic product of Motorola-Arad Ltd., 1. Introduction Consider a production process in which, for every product, a final inspection should be conducted for n of its characteristics. Investigation of this problem was motivated by the [...]

The effects of random disruptions in a bottleneck production facility are examined. This study assumes the existence of uniform demand and production rates, exponential time between breakdowns, regular restoration times, positive setup cost or setup time or both, and backordered excess demand. An (s, S) policy is developed as the production control policy for the system and expressions were generated for the operating characteristics of the system. A numerical experiment indicated that setup cost reduction in reliable production systems can more effectively minimize total operating cost while setup cost reduction in unreliable production systems generate higher optimal safety stock level. Moreover, because they are vulnerable to disruptions, just-in-time systems require the accurate measurement of the safety stock levels.

Manufacturing plants whose customer plants demand just-in-time (JIT) deliveries usually negotiate bounds on JIT contracts with these customers in consideration of the the randomness in both the production and demand processes. One way of establishing such bounds is by setting 'quotas' or 'target inventory levels.' Two models are presented that consider the problem of establishing the ideal quota from the point of view of supplier plant. Specifically, the models seek to determine the best structure for the negotiated bounds on the JIT contracts and to offer quantitative input to the negotiation process. The models indicate that a quota or a guaranteed inventory level can serve as the basis for bounding the responsibility of the manufacturer for satisfying variable demands.

A novel approach to the generalisation of the conflict generating effects of product price changes on household incomes and utilities is developed. It is based upon the concepts of household production of goods and complementarities in production between households. Economy outputs are imputed to households. The imputed household outputs may be positive or negative. Households have an incentive to supply factors to firms if and only if at least one imputed output is negative. It is shown that households which are complementary in production are competitive in distribution. The results are generalised to economies with increasing returns to scale industries. Keywords: Price changes; Conflict generation; Distribution; Increasing returns to scale

Manufacturers of 'style' goods are facing both profit opportunities and production planning and management challenges due to the globalization of trade. Companies can take advantage of variances in the timing of the selling season of geographically dispersed markets. However, an issue called the 'global' newsvendor problem occurs whenever 'style goods' are sold to two markets with non-overlapping selling seasons. Statistical analysis indicate that decentralized production control policies exhibit suboptimality whenever independent profit centers are used and constant transfer pricing policies are implemented. This can be solved by adopting a decentralized production control structure with a nonlinear pricing plan provided by an intermediate organizational group.

Lean logistics is an alternative approach to the management and design of logistics systems. A discussion was done on the production system logic started by Toyota and the dilemma being faced by managers who try to implement new practices and proposals on the logic of value creation. At the core of this new logic is a detailed discussion on the wastes or inefficiencies lying in systems. It is important to understand these concepts so that improvements can be done in the development of a lean logistics system., Problem definition The last ten to 15 years has seen a series of 'new' business solutions - each of which contributed a new perspective - but each of which may [...]

A simple framework can help you figure out the answer. Never has so much technology and brainpower been applied to improving supply chain performance. Point-of-sale scanners allow companies to capture [...]

An extension of Berkley and Kiran's 1991 study on the effects of four kanban policies, which include number of kanbans and status of waiting withdrawal kanbans, showed the impact of those policies in four performance criteria such as average customer wait-time and total inventory. The result is a good tool for managers in evaluating system performance in an improvement process where these kanban variables are present. The data regarding withdrawal kanbans in sequencing decisions leads to the simultaneous improvement in customer wait time and total inventory.

One of the important issues in quality control is finding the optimal target value for a process under various inspection policies. Researchers have considered various aspects of this problem with 100% inspection and with quality sampling plans. In this paper we consider the problem of targeting the set point when rectifying inspection is used. We develop a model for this problem and propose a scheme for solving it. We also provide a numerical example. Key words - acceptance sampling, optimal target value, process optimization, rectifying inspection

We consider the problem of reducing the cycle time required for producing wafers at a given rate in high-volume single-product semiconductor fabs. Based on theoretical results, we propose a new method of input control that uses intersecting hyperplanes to decide when to release a new lot into the wafer fab. The release control rules constructed thus are said to belong to the class of linear control rules. We provide numerical examples to demonstrate that our method gives nearly optimal results for flowline and probabilistic reentrant flowline models. We then propose the linear control rule called descending control (DEC) and give a hybrid simulation-optimization procedure for determining DEC rules in real-life settings. We provide numerical results for the HP development fab model of Wein [31].

The effectiveness of the two-boundary production control is compared against the actual uniform loading policy used in the semiconductor plant studied through a simulation model. Results of the comparison prove that the two-boundary policy is the most stable against unexpected contingencies such as production equipment failures and demand variations. It has been observed that the efficiency of the semiconductor plant can be improved by cutting down on cycle time, work-in-process and inventory costs.

We examine a monopoly facing an uncertain demand and maximizing profits over a two-period horizon. Conditions are developed under which the firm will find it optimal to 'experiment,' or adjust initial prices or quantities away from their myopically optimal level in order to increase the informativeness of observed market outcomes and hence increase future profits. We establish conditions under which experimentation will lead a quantity-setting firm to increase or decrease quantity. Finally, we develop conditions under which experimenting firms will choose to be either price-setters or quantity-setters.

On-line production control problems are solved by the conjunction of off-line adaptive solutions with the expected value of perfect information (EVPI) principle. Such problems are optimizations of the expected net profit where the state variables are conditioned on future decisions. By using extensive simulations, the EVPI algorithm and the adaptive algorithm AD/T are found to be the most efficient and accurate.