Knowledge that Transforms

We introduce a general approach to the coordination and control of material and information flow in multiple cell manufacturing systems. This approach uses production authorization cards (called PAC system) and generalizes such well‐known approaches as MRP (material requirements planning), KANBAN (japanese card system), OPT (optimized production technology), BSS (base. stock system), IC (integral control), CONWIP (constant work‐in‐process), and others. It provides a framework for developing coordination and control mechanisms that combine the desirable features of more than one of these traditional approaches. The coordination is achieved by the rules that determine when and how material and information flow through the system and by the appropriate choice of the parameters of these rules. We also discuss various models of the PAC system that can be used to gain insight into the impact of the choices of the parameters. Directions for future research in this area is also outlined.

In a multiproduct, parallel machine environment, it may be beneficial to dedicate one or more of the machines to a single product for consecutive time periods. However, previous lot‐sizing and scheduling models usually do not allow for such short‐term dedication. This paper presents a mixed‐integer programming model that allows for short‐term dedication in scheduling parallel machines serving multiple products with dynamic demands. It also describes a Lagrangian‐based algorithm for solving such scheduling problems. An experiment verifies the effectiveness of the algorithm and demonstrates the importance of allowing for short‐term dedication. Capacity utilization, one of six factors investigated, greatly affects the use of dedication. A strong interaction effect between the number of machines and the number of products is also seen with respect to the usefulness of short‐term dedication. A measure of estimated production frequency incorporates these two factors along with magnitudes of periodic demands. This measure has a strong relationship with the amount of short‐term dedication used in solutions. Operations managers employing parallel machines could use the experimental results in deciding whether to use short‐term dedication to reduce costs.

Evidence suggests that factory‐based service will become the next form of competition among manufacturers. If this is true, then manufacturing executives will have to obtain a clear understanding of the service capabilities of their plants and adjust their strategies accordingly. We define a set of factory‐based services, information, problem solving, sales, and support, and suggest that they be considered in developing manufacturing strategy. Several propositions provide a framework for future research by linking service performance variables to conventionally accepted manufacturing performance variables.

Our understanding of quality has undergone great changes over the last decade, propelled forward by the quality paradigm that has evolved in Japan. This paradigm has rendered obsolete the traditional quality‐cost trade off model. I outline the key elements responsible for forcing a new understanding of quality‐cost relationships.

This is the second of two papers in which I use information from the technological history of the disk drive industry to examine the usefulness of the S‐curve framework for managers at the firm level in planning for new technology development. In this article I show that it is in architectural, rather than component innovation, that entrant firms exhibit an attacker's advantage. A conventionally drawn sequence of intersecting S‐curves is a misleading conceptualization of the substitution process for new architectural technologies, because it characterizes architectural innovations strictly in technical terms. Innovations in architectural technologies frequently redefine the functionality of products and address product performance needs in new or remote markets, rather than mainstream ones. Such innovations in architectural technologies entail market innovation as much as technology development, and it is in their ability to aggressively enter emerging or remote markets that entrant firms exhibit an attacker's advantage. I propose a different S‐curve framework for processes of architectural technology change that comprehends both its technological and market aspects.

Station interdependence, blocking caused by finite buffer capacities, and periodic material handling make modeling and analysis of kanban‐controlled lines challenging. Also, one must consider flows of material as well as flows of kanbans. The many models given in the literature contribute to the confusion and debate that often characterize kanban research. The only element common to all kanban systems appears to be finite buffer capacities. I describe blocking by total queue size, blocking by part type, and the single‐card and twocard systems. I review the kanban literature and organize it by type of system and decision area. First, I discuss elements of system design, including setting kanban numbers, performance measures, material‐handling frequencies, and container sizes. Then I cover the production control topics of sequencing and batch‐sizing. I conclude with a comparison of kanban and conventional methods of production control and with suggestions for future research.

The technology S‐curve is a useful framework describing the substitution of new for old technologies at the industry level. In this paper I use information from the technological history of the disk drive industry to examine the usefulness of the S‐curve framework for managers at the firm level in planning for new technology development. Because improvements in over‐all disk drive product performance result from the interaction of improved component technologies and new architectural technologies, each of these must be monitored and managed. This paper focuses on component technology S‐curves, and a subsequent paper, also published in this issue of the journal, examines architectural technology Scurves. Improvement in individual components followed S‐curve patterns, but I show that the flattening of S‐curves is a firm‐specific, rather than uniform industry phenomenon. Lack of progress in conventional technologies may be the result, rather than the stimulus, of a forecast that the conventional technology is maturing, and some firms demonstrated the ability to wring far greater levels of performance from existing component technologies than other firms. Attacking entrant firms evidenced a distinct disadvantage versus incumbent firms in developing and using new component technologies. Firms pursuing aggressive Scurve switching strategies in component technology development gained no strategic advantage over firms whose strategies focused on extending the life of established component technologies.