In this paper, we study a manufacturing system with downward substitution in sales, i.e., selling superior products as inferior ones when the demand for the latter cannot be met immediately, in order to reduce the backlog cost. However, downward substitution in sales also causes profit loss. Therefore, controlling a manufacturing system with downward substitution in sales in order to minimize total production cost is a problem worthy of investigation. In this paper, we focus on the production and sale control problem for a two-product-type manufacturing system with downward substitution in sales and time-delay between the releasing of raw materials and the output of final goods. The system is decomposed into two subsystems. In the first subsystem, the state variables are total production surpluses (i.e., the sum of work-in-process and final goods surpluses), and a hedging point policy with a new structure is constructed to control the raw material releasing rates of the two product-types. In the second subsystem, the state variables are the final goods surpluses, and a new switching curve policy is constructed to control the downward substitution rate in sales. Numerical experiments show that downward substitution in sales contributes to the reduction of total production cost, especially when the time-delay is large.

Interest in recycling has surged due to increasing material costs, environmental concerns over material production and disposal, and laws designed to improve material recycling rates. In response, recycling systems are becoming more complex as increasing material recovery is required from products with complicated material mixtures such as waste electrical and electronic equipment (WEEE) and ELVs. To increase performance and process complex material mixtures, separation systems are typically organized as highly integrated multistage systems. However, the problem of estimating the performance and designing multistage separation systems has rarely been tackled from a systems engineering perspective, resulting in poor integration and suboptimal configuration of industrial multistage separation systems. This paper presents a new approach to modeling, analyzing, and designing multistage separation systems to meet specified performance goals in terms of recovery/grade. Results can be used to generate maps of optimal system configurations for different requirements. The industrial benefits are illustrated by a real case study.

A closed-loop production control algorithm for a medical device manufacturing facility of an international healthcare conglomerate with due dates, significant setup times, and random disruptions is proposed. The algorithm is problem driven, exploits a hierarchical setup structure, and uses real-time control. The algorithm has been reduced to a set of simplistic rules with which floor management feels comfortable. The purpose of this research is to provide the theoretical underpinnings of those simple rules.>

The synthesis of operating policies for manufacturing systems is discussed. These are feedback laws that respond to potentially disruptive events. Laws are developed that are based on realistic dynamic programming models that account for the discrete nature of manufacturing and are computationally tractable. These scheduling and planning policies have a hierarchical structure which is systematically based on the production process. The levels of the hierarchy correspond to classes of events that occur with distinct frequencies. At each level, feedback laws select times for the controllable events whose frequency class is treated at that level and frequency targets for much higher-frequency controllable events.>

In this paper, the presence of delay in a job shop is addressed. We show that delay is an important consideration in many manufacturing systems that are modeled as continuous flow processes. A scheduling policy for a job shop with delays is then derived using theoretical arguments and heuristics.

This paper presents a method for real-time scheduling and routing of material in a Flexible Manufacturing System (FMS). It extends the earlier scheduling work of Kimemia and Gershwin. The FMS model includes machines that fail at random times and stay down for random lengths of time. The new element is the capability of different machines to perform some of the same operations. The times that different machines require to perform the same operation may differ. This paper includes a model, its analysis, a real-time algorithm, and examples.

The scheduling of a V.L.S.I. manufacturing facility is being studied using M.I.T.'s new V.L.S.I. Research Laboratory (V.R.L.) as a testbed. This paper describes the facility, outlines the scheduling methodology that is under investigation and presents the design of the initial preliminary scheduling system.