Amiya K. Chakravarty

Decision support in flexible manufacturing systems using timed Petri nets

Abstract Contingency response in a dynamic system such as a flexible manufacturing system requires that the system be able to identify and evaluate a number of alternatives. This paper shows how dummy transitions can be incorporated in a timed Petri net to model contingencies in the system such as machine or tool breakdown, quality deterioration, or production volume surge, etc. An algorithm is presented to evaluate system response in the steady state. A decision support system complete with a problem processor (incorporating the Petri net model), a database, and a query system is outlined.

An object-oriented knowledge representation for hierarchical real-time control of flexible manufacturing

In this paper we demonstrate how a knowledge base can be constructed and used for real-time control of tool loading in a flexible manufacturing system (FMS). A procedure for dynamic tool loading is delineated to support variable production requirements expressed as a master production schedule (MPS). The main emphasis of this work is to propose a framework for real-time control to provide insights into the use of object-oriented structures for representing FMS entities.

Line balancing with task learning effects

Abstract In this paper we show how the learning effects of the individual tasks can be incorporated in the initial design of the stations so that the system may not experience large idle times. We account for the learning effects in assigning tasks to stations by linking the task assignment to the formation of dynamic (in time) bottleneck stations. The station design problem is modeled as a dynamic recursive optimization with computational complexity of O( M2N), where Mis the number of tasks and Nthe number of production units. Using a computer simulation for a system designed by using our task assignment procedure, we compare the system idle times with/without ignoring the learning effects.

Discount pricing policies for inventories subject to declining demand

Until only recently, the mechanism behind determining item price has been ignored and the discount price taken as a given in quantity-discount inventory decision problems. Inventory subject to declining demand further complicates both pricing and replenishment decisions. This article provides the vendor with the means for optimally determining both the discount price and replenishment order frequency for all buyers in the system in an environment of declining demand. In the multiple-buyer case, we provide an efficient algorithm for classifying buyers into homogeneous subgroups to further enhance joint cost savings among all system participants.

Dimensions of manufacturing automation

The gamut of manufacturing automation and its ramifications in relation, to the strategic and operational issues can be appreciated only if the forces driving the system towards automation and their interrelationships are understood, Whether the automated technology is rigid (hard automation) or flexible; whether the control architecture for the system is interactive, passive, or intelligent; and whether the system is a direct evolution from a corresponding conventional (non-automated) system are some of the important considerations. A framework is required to relate the system parameters, leading to different configurations, with the strategic issues such as mix of configurations and path of evolution from one to another (or a mix) configuration, and operational issues such as a hierarchical (push) versus pull production control and the software logic support. Such a framework in terms of technological sophistication levels and control software sophistication levels is presented.

Analysis of flexibility with rationing for a mix of manufacturing facilities

A major competitive advantage of a flexible manufacturing facility is its ability to cope with uncertainties in demand. At a strategic level, capacity-size decisions for a mix of flexible facilities (each not necessarily producing the same combination of products) are made based on aggregates of product types. Such an approach overlooks possible capacity-devouring by some products, arising at the operational level, when the aggregate demand for the period exceeds the available capacity. A rationing policy is required to ensure that the available aggregate capacity of the facilities is shared equitably. In this article, it is shown that such a rationing policy has an impact on the required capacity size and, therefore, must be integrated with the decisions at the strategic level. Several properties indicating the relative preferences of certain facility strategies are also established.

TECHNICAL NOTE: Dynamic Manning of Long Cycle Assembly Lines With Learning Effect

Abstract This paper presents a model to design assembly lines which require long cycle times and complete relatively few products. Work-force requirements in such lines are dynamic in nature, since due to learning, workers performance time is a decreasing function of the number of units already being assembled. Instead of balancing the cycle time at all stages, the model permits the cycle time to decrease in time. An iterative linear programming approach is used to minimize total cost, including labor cost, hiring and lay off by varying the cycle time of the line.

Multi-item inventory grouping with dependent set-up cost and group overhead cost

Abstract The inventory control problem can be greatly simplified if the replenishments of inventory items are coordinated with one another. That is, whenever an item is replenished, n other items, where n is a decision variable, are also replenished. One way to ensure this would be to classify the inventory items into several groups with a common order interval for each group. In this paper we establish that the optimal groups will be consecutive by hD/A where h, D and A are the holding cost, demand rate and setup cost of an item, respectively. Using this consecutiveness property and incorporating a group overhead cost we develop a shortest-path model which creates the optimal groups. We compare our results with the policy of inventory coordination using integer multiplier constraints for order cycles.

Simulated safety stock allocation in a two-echelon distribution system

This paper deals with two important decisions in a two-echelon inventory system operating under stochastic demand and stochastic leadtime. The first of these decisions is the aggregate level of safety stock carried in the system, The second decision is the allocation of the total safety stock within the system. A simulation is performed to study the sensitivity of the system to both decisions. Based on the study, guidelines for efficient management of safety stocks in a two-echelon inventory system are suggested.

Modelling the effects of learning and job enlargement on assembly systems with parallel lines

Abstract In an assembly system with a fixed number of workers, job enlargement leads to parallel lines. Job enlargement reduces absenteeism and turnovers, thereby increasing productivity. Job enlargement also reduces the number of repetitions per period reducing the learning effect and hence productivity. In an optimal job design, the loss of learning must be traded off with the reduction in absenteeism and turnovers. In this paper we show that an optimal job design exists with respect to the system response time and propose an analytical model to achieve such a design. Our experience with the model suggests that an optimal job design is most important when a new system is considered, and when significant learning takes place.