Roger E. Bohn

Learning and process improvement during production ramp-up

Abstract Rapid product lifecycles and high development costs pressure manufacturing firms to cut not only their development times (time-to-market), but also the time to reach full capacity utilization (time-to-volume). The period between completion of development and full capacity utilization is known as production ramp-up. During that time, the new production process is ill understood, which causes low yields and low production rates. This paper analyzes the interactions among capacity utilization, yields, and process improvement (learning). We model learning in the form of deliberate experiments, which reduce capacity in the short run. This creates a trade-off between experiments and production. High selling prices during ramp-up raise the opportunity cost of experiments, yet early learning is more valuable than later learning. We formalize the resulting intertemporal trade-off between the short-term opportunity cost of capacity and the long term value of learning as a dynamic program. The paper also examines the tradeoff between production speed and yield/quality, where faster production rates lead to more defects. Finally, we show what happens if managers misunderstand the sources of learning.

Optimal pricing in electrical networks over space and time

An electrical system is modelled with a transmission network, customers, central generators, and independent generators. The system is subject to stochastic failures and stochastic demand parameters. Optimal spot prices are derived for the system. They vary stochastically with space and time, and depend on electrical load flow patterns. The price difference between two locations or two voltage levels, and the wheeling charge between them, will change magnitude and sometimes sign over time, as a function of events throughout the network. Current spatial pricing methods are significantly different from the spot-price-based methods derived here.

International product transfer and production ramp‐up: a case study from the data storage industry

Many high-tech industries are shifting their focus from minimizing time-to-market to minimizing time-to-volume. This puts the tail end of product development, the production ramp-up, in a critical position. This article presents a case study of product transfer and production ramp-up in the hard disk drive industry. We provide a detailed description of the ramp-up period. By documenting detailed time-series of several operational measures, we also shed light on the various forces that allow an organization to increase its production volume. Finally, the setting allows us to study product transfer from development in the USA to an Asian production facility. We find that the physical distance is successfully overcome by several mechanisms.

The economics of yield-driven processes

Abstract The economic performance of many modern production processes is substantially influenced by process yields. Their first effect is on product cost — in some cases, low-yields can cause costs to double or worse. Yet measuring only costs can substantially underestimate the importance of yield improvement. We show that yields are especially important in periods of constrained capacity, such as new product ramp-up. Our analysis is illustrated with numerical examples taken from hard disk drive manufacturing. A three percentage point increase in yields can be worth about 6% of gross revenue and 17% of contribution. In fact, an eight percentage point improvement in process yields can outweigh a US

A dynamic approach to operations management: An alternative to static optimization

20/h increase in direct labor wages. Therefore, yields, in addition to or instead of labor costs, should be a focus of attention when making decisions such as new factory siting and type of automation. The paper also provides rules for when to rework, and shows that cost minimization logic can again give wrong answers.

Mitigating the Coming Internet Crunch: Multiple Service Levels via Precedence

Abstract In todays globally competitive manufacturing environment, many firms are compelled to rapidly improve and evolve their operations. But traditional formal analysis of operations management is “static”, emphasizing optimization in a steady state world. We propose an alternative “dynamic” approach to analyzing operations management. Our approach deals explicitly with four elements not considered by most static approaches: knowledge, learning, contingencies, and problem solving. In studying each of these elements in detail, emphasis shifts from improving efficiency assuming complete technological knowledge, to deliberately enhancing rates of improvement and of adaptation to new situations. Robotic assembly of watches is discussed in detail as an example of a process that ought to fit the static approach, i.e., be managed for static efficiency. In fact, we find that the process is managed dynamically. We propose several ways of applying traditional modeling tools to dynamic issues. Considerable further research will be needed to develop models for dynamic situations that are as powerful as traditional models are for static situations.

Globalization of Production: Insights from the Hard Disk Drive Industry

The current architecture and implementation of the Internet assumes a vast aggregation of traffic from many sources and stochastic distribution of traffic both in space (traffic source) and time (burstiness of traffic volume). Given this general assumption, Internet components typically have little if any ability to control the volume and distribution of incoming traffic. As a result the network, particularly from the perspective of the router, is vulnerable to significant consumption of networking resources by high-volume applications, with possibly little stochastic behavior, from a few users. This often impacts the overall profile of network traffic as aggregated from many clients. An example is the continuous flows introduced by real time applications such as packet audio, video, or rapidly changing graphics.This situation creates a time window where applications exist on a network not designed for them, but before an appropriately architected network can augment the current infrastructure and cope with the new type of workload. We propose a scheme for voluntarily setting Internet traffic priorities by end-users and applications, using the existing 3-bit Precedence field in the Internet Protocol header.Our proposal has three elements. First, network routers would queue incoming packets by IP Precedence value instead of the customary single-threaded FIFO. Second, users and their applications would voluntarily use different and appropriate precedence values in their outgoing transmissions according to some defined criteria. Third, network service providers may monitor the precedence levels of traffic entering their network, and use some mechanism such as a quota system to discourage users from setting high precedence values on all their traffic. All three elements can be implemented gradually and selectively across the Internet infrastructure, providing a smooth transition path from the present system. The experience we gain from an implementation will furthermore provide a valuable knowledge base from which to develop sound accounting and billing mechanisms and policies in the future.

System security control and optimal pricing of electricity

Abstract Rapid change in the geographical location of production raises important questions regarding the welfare, development potential, and competitive position of different countries and regions. This paper explores in detail the geography of economic activity in a specific industry, the hard disk drive (HDD) component of the computer industry. Firms in the HDD industry are breaking the production system into ever smaller distinct steps, and spreading the physical location of these steps around the world. Firms from the United States dominate the industry. Our findings suggest that globalization has enabled US firms to sustain their dominant position in the industry, preserve employment in the United States (and possibly expand it), and increase employment worldwide, most notably in Southeast Asia.

An experiment in real time pricing for control of electric thermal storage systems

Abstract Optimal electricity spot pricing internalizes electricity transportation network costs and constraints. We extend spot pricing theory by including system security control issues in the model. The engineering and physics of system security control imposes a need for speed and precision of response. Traditionally this need has been met by central control of centrally owned equipment and little control of customer-owned equipment. We show that socially optimum prices exist which decentralize security control by internalizing its costs. These prices are robust and feasible to determine without unreasonable information requirements by the market maker. Families of optimal prices and price/quantity controls are determined and interpreted. Contingency planning and enhanced centre/market-maker roles are derived. Applications of immediate interest are also discussed, such as pricing of interruptible loads and assignment of power pool reserves. Symmetry between demand side and supply side security control is shown to be optimal.

From Art to Science in Manufacturing: The Evolution of Technological Knowledge

The authors present the results of an experiment designed to test the economic benefits of real-time pricing (RTP) used to schedule electric thermal storage (ETS) systems in a New York utilitys service territory during the winter of 1989-1990. Three customers with EST systems were placed on an experimental RTP rate for their heating load only. A complete automated RTP-based control system was designed and retrofitted in place of the existing time-of-use (TOU)-based control system. The design, development, and implementation of the experimental RTP rate, customer response algorithms, and the energy management systems are described. Costs to the utility of the provision of service went down by about 10% beyond savings achieved under the TOU-based control system for a system with no storage. >