Simulation has long been used in the manufacturing industry to help determine, and suggest ways of increasing, production capacity under a variety of scenarios. Indeed, historically, this economic sector was the first to make extensive use of simulation. Over the last several decades, and continuing today, the most numerous applications of simulation to manufacturing operations involve mass production facilities such as those fabricating motor vehicles or home appliances. Less frequently, but very usefully, simulation has been applied to customized manufacturing or fabrication applications, such as the building of ships to individualized specifications. In the case study described in this paper, simulation was successfully applied, in synergy with other techniques of industrial engineering, to assess and increase the throughput capacity of a manufacturer of custom-built personal jet airplanes with a four-to-six passenger (plus moderate amounts of luggage) carrying capacity.

This presentation discusses modeling challenges, approach, and findings for the throughput capacity verification of a parking system. This system consists of a totally automated four-story parking structure located next to a train station. Demand variations through the day for parking and retrieving cars are verified using simulation and equipment constraints are identified.

The most venerable and the most highly varied general application area in which simulation has frequently and repeatedly proved its economic value is the manufacturing sector of the economy. Manufacturing applications of simulation have included attention to complex issues of equipment and/or worker downtime, problems of facility layout, work and line balancing, bottleneck analysis, and material handling. Furthermore, simulation has proved itself capable of addressing productivity and efficiency improvement tasks in which these complexities overlap and interact. Historically, much of the success simulation has enjoyed in other economic sectors (e.g., service, transportation, and health care) has stemmed in large measure from the reputation it earned in the manufacturing sector. The manufacturing application described in this paper proved the cost-effective feasibility of designing sortation operations downstream of an assembly line, and scheduling SKU pickups there, with no risk of blockage of that line.

Simulation has long been a significant and powerful force for the improvement of manufacturing operations. More recently, it has been used to increase the efficiency, efficacy, and economy of service operations. In this case study, we describe the valuable contributions simulation made to the improvement of operations at numerous business locations of a company renting vehicles (without drivers). Specifically, discrete-event process simulation analyses played a pivotal role in the construction and implementation of the "Demand-Driven Workforce Scheduler" (DdWS) now used at the client company.

Discrete-event process simulation, originally the benefactor of the manufacturing sector of the economy, has expanded aggressively into the service sector of the economy, much to the benefit and gratitude of its new cadre of industrial engineers and management strategists. The study documented in this paper originated within a large health-care insurance provider seeking optimal strategies relative to target inventories of pending inquiries concerning insurance policy coverage and concomitant staffing levels of policy analysts. Since several clients of this insurance provider were large companies within the automotive industry, the provider dedicated significant staffing segments to the service of these accounts (hence to the employees of those automotive companies who thereby held insurance coverage). The simulation study worked within this constraint to provide management valuable strategic recommendations. Most specifically, the insurance provider wished to develop a model capable of predicting service levels (average time required to answer specific questions submitted on behalf of two major clients and average inventory level of these questions pending) as a function of number of full-time-equivalent analysts assigned to each of those clients.

Discrete-event process simulation, which boasts a long and enviable history of guiding improvements to manufacturing operations, extended its successes in the study reported here. A small manufacturer of extruded window seals, as a member of the automotive industry supply chain, used discrete-event simulation and allied statistical input and output analyses to comparatively evaluate four alternatives and select the best one based on various performance metrics and business scenarios.

Simulation has long been recognized as an analytical tool of high power and wide applicability when applied to the improvement of manufacturing processes. Indeed, historically, manufacturing applications were the first major purview of simulation usage by large companies. As manufacturing processes increase in complexity, both operational and economic, the capabilities of simulation increase both in importance and in difficulty of duplication by alternative analytical methods. In this paper, we examine in detail the application of simulation to an automotive stamping plant. Simulation identified bottlenecks in material handling, pointed the way to increasing utilization of a costly stamping press, and quantified the relationships between specific capital investments under consideration and the throughput increase to be expected.

Discrete-process simulation, long used in the manufacturing sector of the economy for process analysis and improvement, has more recently, yet extensively, proved its value in the service industry for the same purposes. Very simple queuing situations are amenable to closed-form analysis; however, queuing environments typical of actual contexts in the service industry defy such analyses, except perhaps as initial approximations. In this study, discrete-process simulation was applied to the problems of a credit union whose drive-through operations had proved themselves inadequate to meet peak demands. The results of the study guided credit union management in evaluating proposed alternatives to improve service to drive-through customers at reasonable expense in both time and capital expenditure.