Robert H. Hayes

Restoring our Competitive Edge: Competing Through Manufacturing

The New Competitive Challenge for Manufacturing. The Concept of Manufacturing Strategy. Long-term Capacity Strategies. Facilities Strategy. Implementing Facilities Planning Processes. The Technology of Manufacturing Processes. Matching Process Technology with Product/Market Requirements. The Experience Curve--A Framework for Manufacturing Performance Improvement. Vertical Integration and Sourcing. Managing Changes in Manufacturings Technology and Structure. German Approaches to Manufacturing Management. Japanese Approaches to Manufacturing Management. Learning from Your World-class Competitors. Building Manufacturings Competitive Potential. Index.

Operations-based Strategy

Although most companies confine their operations organizations to restricted, tactical roles, in some of the most successful firms operations has served as the foundation for-indeed, the driver behind-successful strategic attacks and defenses. This is most clearly seen in cases where small companies-although lacking the advantages of size, marker position, and proprietary technology-take on big companies and in a relatively short time push their way to industry dominance. In such cases, the key to success often is an operations-based advantage. The peculiar nature of this advantage provides insight into the reasons many former industry leaders did not react more promptly and vigorously to such attacks, and why others, in contrast, were able to defend themselves successfully.

Requirements for successful implementation of new manufacturing technologies

Abstract This paper addresses the issue of why many U.S. companies have had major problems implementing “programmable automation” technologies in a manner to exploit their full potential. Many competitors in Japan and Europe have been much more successful. The theme of the paper is that the real impediment to the effective use of this new manufacturing hardware lies in some deeply entrenched attitudes and ways of doing things that are incompatible with the requirements and unique capabilities of the new hardware. Barriers to successful implementation are explored and implications for managerial practice are discussed.

Efficiency of Simple Order Statistic Estimates When Losses are Piecewise Linear

Abstract When losses are piecewise linear, optimal decision-making hinges on estimating a specified fractile of a probability distribution. In this article we investigate, through examples, the operating characteristics of an estimation procedure which utilizes simple linear combinations of one or two values in the order statistic generated by an observation vector. Such estimates appear to be remarkably efficient compared to the estimates generated by simple parametric procedures; moreover, this efficiency does not appear to be damaged excessively by the presence of moderate amounts of autocorrelation in the sample values. It also appears to be possible to exploit informal knowledge about the shape of the distribution to improve the efficiency of this procedure.