Charles M. Weber

Yield learning and the sources of profitability in semiconductor manufacturing and process development

A numerical model that identifies the high-leverage variables associated with profitability in semiconductor manufacturing is presented. Varying the parameters of the model demonstrates that a rapid yield-learning rate determines profitability more than any other factor does. Factors such as ramping-up early, adding fab capacity, depressing the terminal fault density, and shrinking die size all yield diminishing returns. The model also suggests that developing a rapid problem-solving capability in the early stages of process development enables successful yield learning.

Mask Cost and Profitability in Photomask Manufacturing: An Empirical Analysis

An empirical study of the economics of manufacturing photomasks concludes that the uncontrolled growth of optical proximity effect correction and resolution enhancement techniques is driving up the cost of pattern generation and mask inspection to levels that threaten the profitability of photomask manufacturing. The intrinsic cost of some leading edge photomasks has already exceeded the price that customers are willing to pay for them. A model of the lifecycle of photomask manufacturing, developed from interviews involving the 1990-to-2005 operations of six mask shops and a survey of seven photomask manufacturers, shows that design for manufacturability (DFM) constitutes the most promising approach for alleviating this market impasse. Unilateral action by mask shops to increase their capital productivity is necessary but insufficient and perhaps unaffordable. DFM solutions will require the majority of participants in the lithography value chain to collaborate according to a volatile demand schedule that is driven by semiconductor manufacturers

Optimizing Your Position on the Operating Curve: How Can a Fab Truly Maximize Its Performance?

An empirically grounded model of a fab operating curve that is sufficiently accurate to make capitalization decisions has identified preferred domains of fab performance. This finding contradicts extant theory, which argues that all operating points on the same operating curve should reflect the same level of performance. The model is used to simulate the performance of a stylized fab that operates under realistic conditions. Results of the simulation show that significant additional revenue and profit can be generated by extending the lean approach to managing the operating curve that is practiced in most fabs today to an approach that is both lean and value driven.

Do Learning Organizations have Strokes of Genius

Do learning organizations have strokes of genius? An empirical study of 34 high technology R&D and manufacturing organizations suggests not. The roots of punctuated equilibrium in organizational learning can be traced to learning activities that occur within organizational subsystems, primarily during R&D. Continuous improvement at the subsystem level contributes significantly to a delayed, rapid surge in organizational performance. Managers coordinate subsystem-level activities to maximize organizational performance by trading off the revenues expected from timely learning against the expected costs. Knowledge accumulated within organizational subsystems can remain hidden from organization-level performance metrics for prolonged periods of time

Scale, Scope, and Speed—Managing the Challenges of Multiproduct Manufacturing

An empirically grounded model characterizes the challenges of modern multiproduct manufacturing, where products that operate in highly contrasting economic environments run in one fab. Three product classes are taken into consideration-VLSI circuits for which unit sales prices are highly time dependent; specialty chips for which unit sales prices and total demand are specified a priori; and commodity components whose unit sales prices are low, predictable, and either flat or cyclical. The model calculates the impact of manufacturing cycle time on cost structure and the ability to generate revenue, and it simulates the economic consequences of a variety of production plans involving the three product classes. The findings of this paper suggest that an integrated approach to managing scale, scope, and fab cycle time can bring about dramatic increases in fab performance as measured by the net profit that the fab accumulates.

Characterizing the Economic Value of Organizational Learning in Semiconductor Manufacturing

This paper describes an empirical study that assesses the economic value of various forms of organizational learning that are common in semiconductor manufacturing. This study considers three business environments: very large-scale integrated circuits, commodity components, and specialty parts with high value added. This study finds that the economic value of organizational learning varies over time, the relative economic value of different learning practices varies over time, the external economic environment strongly influences the economic value of different learning practices, the economic value of learning can be positive or negative, and the synergy between different kinds of learning can be positive or negative. The primary contribution of this paper is an empirically grounded model of organizational learning in the semiconductor manufacturing industry, which potentially enhances the profitability of semiconductor manufacturing ventures. The model helps practicing managers make investment decisions through scenario planning and identifies learning strategies that are tailored to their particular economic environment. This paper also provides insight into the structure of technological knowledge in semiconductor manufacturing, which has historically been treated as a black box.

Enabling Collaborative Solutions Across the Semiconductor Manufacturing Ecosystem

A qualitative empirical study of 29 semiconductor manufacturer and supplier firms investigates the challenges associated with implementing lean practices that require broadly based collaboration across firms. The studys primary contribution is a model of the semiconductor manufacturing ecosystem, which shows how chipmakers, suppliers of enabling technologies, subsystem suppliers, and their respective competitors interact to develop the right technologies at the right time. The study finds that the biggest challenge to industry-wide collaboration is managing knowledge flows between users and suppliers in a manner that allows all parties to collaborate without losing competitive advantage. The paper also presents insights into how inter-organizational knowledge is created synchronously in the semiconductor industry. Finally, the paper makes suggestions as to how interfirm knowledge can be managed.

OPENING THE BLACK BOX OF TECHNOLOGY ADOPTION: THE MOTIVE-TECHNOLOGY-BELIEF FRAMEWORK

A qualitative empirical study explores the psychological process by which transportation consumers adopt alternatives to single occupancy vehicles. The studys findings give rise to the Motive-Technology-Belief (MTB) framework, a theory that conceives of technology adoption in terms of three mental structures: motives are inner mental reasons; technologies are tools that pertain to motives; and beliefs are associations between motives and/or technologies. Their behavioral interactions are governed by three conscious processes: selecting is the process of choosing a tool in response to an immediate need; evaluating is the process of forming beliefs about tools; and maintaining is the process of determining the functional status of tools. They are augmented by five unconscious auxiliary processes: perceiving, focusing, framing, consolidating, and acting. The primary contribution of the paper is a framework for a causal adoption process theory that is solidly grounded in empirical observations and prior literature, and is well-suited to guide the construction of simulated consumer agents. The theory establishes a foundation for agent-based market simulation that gives new product development and service innovation managers improved ability to forecast emerging market conditions.

Organizational Learning and Capital Productivity in Semiconductor Manufacturing

This paper presents an empirical study, which leads to a theoretical framework that links organizational learning and capital productivity. The approach described in this paper helps fab managers make fundamental strategic decisions concerning capital investment and point of entry by engaging in scenario planning. Three strategic options for semiconductor manufacturing are analyzed in detail-leading-edge manufacturer, fast follower, and slow follower. The study concludes that profitability and capital productivity can be in conflict with each other. Leading-edge manufacturers can make large profits, if they ramp up to volume production in a timely manner, but their return on investment and thus their capital productivity are relatively low. Generally, manufacturers that do not run state-of-the-art processes are less profitable than those that do, but their return on investment and thus their capital productivity is comparatively high. Fast followers, which import part of their manufacturing process and ramp to volume production rapidly but with a delay, neither break even nor recover their investment.

BRIDGING THE GAP BETWEEN ARTIFICIAL MARKET SIMULATIONS AND QUALITATIVE RESEARCH IN DIFFUSION OF INNOVATION

Artificial markets (AMs) are an emerging form of agent-based simulation (ABS), in which agents represent individual consumers, firms, or industries interacting under simulated market conditions. The validity of the method depends on the ability of researchers to construct simulated agents that faithfully capture the key behavior of targeted entities. Without such a correspondence the simulation cannot be considered to be a valid representation of market dynamics. To date, no such correspondence has been established. Yet, for artificial markets to achieve their potential as a tool for marketing practice it is crucial that closer ties be forged with mainstream methods for consumer behavioral research, especially qualitative methods. The primary contribution of this article is a novel method combining qualitative marketing research (inductive case studies, grounded theory, and sequence analysis) and software engineering techniques to synthesize simulation-ready theories of consumer behavior. We provide a step-by-step explanation and a demonstrative example of theory-building from the consumer technology adoption domain. The outcome is a theory of consumer adoption behavior that is sufficiently precise and formal to be expressed in Unified Modeling Language (UML). The article concludes with a discussion of the limitations of the method, recommendations for its implementation in the study of diffusion of innovation (DOI) and suggestions for further research. The arguments and findings in this article that pertain to artificial markets can be generalized with respect to most agent-based simulations, including those applied to the study of diffusion of innovation. The results of an ABS of innovation diffusion cannot be relied upon unless the agents are based on a theory of adoption that grounded in empirical observations of the targeted entities — regardless of whether those entities are consumers, firms or industries. Qualitative research of adoption behavior is thus a useful precursor to successful agent-based approaches to studying the diffusion of innovations.