Thomas G. Schmitt

Resolving uncertainty in manufacturing systems

Abstract This paper examines the effectiveness of three commonly practiced methods used to resolve uncertainty in multi-stage manufacturing systems: safety stock under regenerative material requirements planning (MRP) updates, safety capacity under regenerative MRP updates, and net change MRP updates, i.e., continuous rather than regenerative (periodic) updates. The use of safety stock reflects a decision to permanently store materials and labor capacity in the form of inventory. When unexpected shortages arise between regenerative MRP updates, safety stock may be depleted but it will be replenished in subsequent periods. The second method, safety capacity, overstates the MRP capacity requirements at the individual work centers by a prescribed amount of direct labor. Safety capacity either will be allocated to unanticipated requirements which arise between MRP regenerations or will be spent as idle time. The third method, net change, offers a means of dealing with uncertainty by rescheduling instead of buffering, provided there is sufficient lead time to execute the changes in the material and capacity plans. Much of the inventory management research has addressed the use of safety stock as a buffer against uncertainty for a single product and manufacturing stage. However, there has been no work which evaluates the performance of safety stock relative to other resolution methods such as safety capacity or more frequent planning revisions. In this paper, a simulation model of a multi-stage (fabrication and assembly) process is used to characterize the behavior of the three resolution methods when errors are present in the demand and time standard estimates. Four end products are completed at an assembly center and altogether, the end products require the fabrication of twelve component parts in a job shop which contains eight work centers. In addition to the examination of the three methods under different sources and levels of uncertainty, different levels of bill of material commonality, MRP planned lead times, MRP lot sizes, equipment set-up times and priority dispatching rules are considered in the experimental design. The simulation results indicate that the choice among methods depends upon the source of uncertainty, and costs related to regular time employment, employment changes, equipment set ups and materials investment. For example, the choice between safety stock and safety capacity represents a compromise between materials investment and regular time employment costs. The net change method is not designed to deal effectively with time standard errors, although its use may be preferred over the two buffering alternatives when errors are present in the demand forecasts and when the costs of employment changes and equipment set ups are low. The simulation results also indicate that regardless of the method used, efforts to improve forecasts of demands or processing times may be justified by corresponding improvements in manufacturing performance.

Production classification system: concepts, models and strategies

Production processes are most frequently classified in the literature into one of three categories: projects, intermittent processes (i.e., job or flow shops), or continuous processes (i.e., assembly lines or flow processes). A major shortcoming of this classification system is that it often fails to capture important aspects of real world production processes, thus providing manufacturing managers with little conceptual work to guide their decision-making. In this paper, a more comprehensive framework (which we denote as the production classification system, or PCS) is developed which defines and relates many types of production processes, In addition, a direct linkage between this framework and corporate competitive strategy is described.

Improved network based algorithms for the assembly line balancing problem

In this paper, we present two network based algorithms for solving Type 1 assembly line balancing problems. These algorithms are based on the generation of the network of feasible subsets; the shortest path through this network corresponds to the minimum cost solution. While the methods presented here may require the generation of all feasible subsets, they use upper and lower bounds and dominance to eliminate many of these subsets. The first method (which we call the Frontscan algorithm) evaluates nodes in a manner similar to a procedure originally suggested by Mansoor (1967); the second procedure (which we call the Backscan algorithm) evaluates nodes by proceeding backwards through the network. Both procedures are quite versatile and are easily adapted to the line balancing problem with stochastic task times, duplicate parallel work stations, zoning restrictions, etc. Computational tests indicate that these algorithms are more efficient than previous network based methods (including dynamic programming ...

Economic lot scheduling with lost sales and setup times

We introduce a new modeling framework for the classic economic lot scheduling problem that permits lost sales if they lead to higher profits. The model also accounts for setup times at a facility, but assumes no explicit incremental setup cost in the objective. Despite assumptions of deterministic demands, production rates and setup times, the cost of carrying inventory may make lost sales during a cycle economically attractive. Statistical analysis on randomly generated problems ranging in size from 100 to 1000 products indicates that the computation time grows by the square of the number of products.

Quadrant Homes Applies Lean Concepts in a Project Environment

Quadrant Homes, a subsidiary of Weyerhaeuser Corporation, provides transferable lessons for applying lean-manufacturing concepts in project environments. The company has obtained impressive market and financial results, using an even-flow, predictable scheduling model in which it starts six houses per day and finishes each one in exactly 54 days. Quadrant follows recognized lean principles, including (1) designing its value stream around customer needs, (2) balancing work so all stages flow evenly, (3) operating on the basis of customer pull, and (4) continuously improving. Quadrant makes the lean principles work in a project environment by (1) knowing what can be standardized and what must be customized, (2) carefully setting and consistently managing customer expectations, (3) aligning goals of all stakeholders, and (4) recognizing that variances will occur, and designing routines to handle them when they do.

ASP, The Art and Science of Practice: Three Challenges for a Lean Enterprise in Turbulent Times

A lean enterprise ties together and synchronizes all elements of its value-delivery system to provide for the needs of target customers. Organizations applying lean concepts in a systematic manner have been highly successful from operational, market, and financial perspectives. Once effectively in place, however, lean value-delivery systems can be more easily derailed than their leaders imagine, particularly in turbulent times. We identify three potential challenges for lean enterprises: 1 locked operating model: failure to change the value-delivery system in response to market and economic disruptions; 2 backward drift to pre-lean practices: regression toward wasteful inventory accumulations, backlogs, and complexity; 3 lean islands: isolation of lean practices within the walls of the company. Our observations at Quadrant Homes as it navigated the Great Recession, supplemented by our research at other companies, leads to recommendations for lean organizations to apply in countering these challenges.