SOLVING A COMBINED PART-SELECTION,MACHINE-LOADING,AND TOOL-CONFIGURATION PROBLEM IN FLEXIBLE MANUFACTURING SYSTEMS*

Loading too many or too few copies of tools may result in waste of tool magazine slots and unnecessary machine shutdowns. This is a consequence of not integrating the tool-configuration problem with other flexible manufacturing system (FMS) planning problems. Solving part-selection, machine-loading and tool-configuration problems independently may cause entire solutions to be infeasible. We propose both an approach to the explicit formulation of tool configuration problems and the simultaneous solution of part-selection, machine-loading and tool-configuration problems. We developed and solved sequentially some associated bicriteria models sequentially. We also discussed the effects of considering some secondary objectives on system performance and described the concepts of critical magazine size and critical machining time using an example problem. Unnecessary allocation and under-use of tool magazine capacity and machining time could be reduced by considering the critical magazine size and machining time. Finally, we suggest using a method based on Lagrangian relaxation for solving large size problems.     

TRACKING PRODUCT-PROCESS INTERACTIONS: A RESEARCH PARADIGM*

To design (or redesign) a competitive product, it is imperative that both the sales and manufacturing cost implications are assessed in a structured way. That is, the interactive (multidimensional) aspects of manufacturing and marketing variables need to be positioned in a proper perspective so that the system impact of variation in one or more variables may be ascertained quickly. In this paper we show how some of the system-related paradigms can be used as foundations for developing quantitative and qualitative models for tracking such interactive ímpacts. The emphasis is not on building complex mathematical models to solve specific problems but on providing a framework where system properties expressed as simple postulates can be used in an intelligent way to assess the impact of improvements in specific product-process scenarios.     

Social Defenses Against Organizational Learning

It is argued that for organizational learning to occur maladaptive social defenses within the organization have to be altered. The origins of the concept of social defenses are traced through the work of Jaques and Menzies. A new concept of system domain, and related concepts of system domain fabric, and system domain defenses, are proposed in order to account for the difficulties in sustaining organizational change in organizations that share a similar primary task. Organizational learning is defined as occurring when there is co-evolution of organizational container and contained. The article distills variables from three successful consultancy/action research projects which are characteristic of organizations that are learning, and it is hypothesized that the creation of organizational awareness is necessary for organizational learning to occur.     

INSIGHTS ON SERVICE SYSTEM DESIGN FROM A NORMAL APPROXIMATION TO ERLANG'S DELAY FORMULA

We show how a simple normal approximation to Erlang's delay formula can be used to analyze capacity and staffing problems in service systems that can be modeled as M/M/s queues. The numbers of servers, s, needed in an M/M/s queueing system to assure a probability of delay of, at most, p can be well approximated by s ≅ p + z_***I-p+, where z_1-p, is the (1 - p)th percentile of the standard normal distribution and ρ, the presented load on the system, is the ratio of Λ, the customer arrival rate, to μ, the service rate. We examine the accuracy of this approximation over a set of parameters typical of service operations ranging from police patrol, through telemarketing to automatic teller machines, and we demonstrate that it tends to slightly underestimate the number of servers actually needed to hit the delay probability target—adding one server to the number suggested by the above formula typically gives the exact result. More importantly, the structure of the approximation promotes operational insight by explicitly linking the number of servers with server utilization and the customer service level. Using a scenario based on an actual teleservicing operation, we show how operations managers and designers can quickly obtain insights about the trade-offs between system size, system utilization and customer service. We argue that this little used approach deserves a prominent role in the operations analyst's and operations manager's toolbags.     

Increase in the prevalence of metabolic syndrome among workers according to age

Androgen levels decline over a man's lifetime. In a proportion of men (increasing with age), levels fall below values that have been established by conventional laboratory criteria as indicative of hypogonadism. Testosterone has a wide range of non-reproductive actions: it preserves bone and muscle mass, it acts on non-sexual mental functioning and it stimulates red blood cell formation. Long-term androgen deficiency has a great impact on quality of life. The first intervention studies provide indications that androgen treatment of men with true androgen deficiency is helpful. Obviously, only men who are testosterone-deficient will benefit from androgen supplementation. The diag nosis of testosterone deficiency in old age is not unambiguous. Signs and symptoms of aging sometimes clinically overlap with those of testosterone deficiency. The groups that are at higher risk of testosterone deficiency are those men with disease (pulmonary disease, gastrointestinal disease, rheumatoid disease, etc.). Usually, sex hormone binding globulin levels increase with aging, leading to lower levels of free, biologically available testosterone. For the time being, arbitrary criteria for testosterone deficiency in aging men have to be adopted. The best practical approach is to calculate the free testosterone level. The calculation can be found at www.issam.ch under 'Tools'.     

UPSTREAM VOLATILITY IN THE SUPPLY CHAIN: THE MACHINE TOOL INDUSTRY AS A CASE STUDY

Cyclicality is a well‐known and accepted fact of life in market‐driven economies. Less well known or understood, however, is the phenomenon of amplification as one looks “upstream” in the industrial supply chain. We examine the amplification phenomenon and its implications through the lens of one upstream industry that is notorious for the intensity of the business cycles it faces: the machine tool industry. Amplification of demand volatility in capital equipment supply chains, e. g., machine tools, is particularly large relative to that seen in distribution and component parts supply chains. We present a system dynamics simulation model to capture demand volatility amplification in capital supply chains. We explore the lead‐time, inventory, production, productivity, and staffing implications of these dynamic forces. Several results stand out. First, volatility hurts productivity and lowers average worker experience. Second, even though machine tool builders can do little to reduce the volatility in their order streams through choice of forecast rule, a smoother forecasting policy will lead companies to retain more of their skilled work force. This retention of skilled employees is often cited as one of the advantages that European and Japanese companies have had relative to their U. S. competitors. Our results suggest some insights for supply chain design and management: downstream customers can do a great deal to reduce the volatility for upstream suppliers through their choice of order forecast rule. In particular, companies that use smoother forecasting policies tend to impose less of their own volatility upon their supply base and may consequently enjoy system‐wide cost reduction.     

IMPROVING POM LEARNING: SYSTEMS THINKING AND TRANSPARENT-BOX BUSINESS SIMULATORS

It is well known by systems thinkers that the behavior of complex systems (for example, the company as a whole or the operations subsystem) depends upon their structure (the set of system variables and their interrelationships). In our opinion, the methods and tools presently used for production and operations management (pom) teaching are insufficient to cope with an ever more complex reality. Over the last few years, the research group GIdEao, following an original idea (Machuca 1992a, 1992b) has been developing transparent-box business simulators (TBBSS) based on systems thinking and system dynamics models; the aim was to maintain the advantages of the existing didactic tools while mitigating their drawbacks. The most distinctive feature of TBBSS (as opposed to the traditional black-box business games) is that the structure of the system to be simulated is always accessible to the users, who can thus reflect on the causes underlying the results obtained and thereby improve decision-making and the learning process. We will show how to work with TBBSS, and we will comment on the results obtained in an empirical experiment which aims to measure the influence of TBBSS on the learning process.     

A MODEL FOR SWITCHING DISPATCHING RULES IN REAL TIME IN A FLEXIBLE MANUFACTURING CELL

We model choice of dispatching rules in real time (system state dependent) as a pattern recognition problem, using a modified version of Data Envelopment Analysis. A data base of system state and performance values is created from extensive simulation, and this data base is used to train the pattern-recognition model. Our results show that the model is very effective in choosing a mix of dispatching rules over a period of time, varying the mix with system objectives, and performing better than the strategy of using fixed rules. We show how “If-Then” decision rules can be created from the model and portrayed in a decision-tree-like diagram. Since such decision rules are based on rigorous mathematical foundations, optimization will be ensured in our approach.     

AN OVERVIEW OF TRADEOFF CURVES IN MANUFACTURING SYSTEMS DESIGN

In this paper we review the use of tradeoff curves in the design of manufacturing systems that can be modeled as open queueing networks. We focus particularly on the tradeoff between expected work-in-process (or product leadtime) and capacity investment in job shops. We review the algorithms in the literature to derive tradeoff curves and illustrate their application in evaluating the efficiency of the system, in deciding how much capacity to have, how to allocate resources between the reduction of uncertainty and the introduction of new technologies, and how to assess the impact of changes in products throughput and product mix. The methodology is illustrated with an example derived from an actual application in the semiconductor industry.     

THE EFFECT OF LEARNING ON THE OPERATION OF MIXED-MODEL ASSEMBLY LINES

The common approach to balancing mixed-model assembly lines assumes that the line operators are well trained and that the learning effect is negligible. The assumption is that the line operates in steady state over a long period of time. Time-based competition and frequent design changes in many products make this assumption incorrect, and the effect of learning on mixed-model lines should not be neglected. We defined start-up period and developed a model for the line design during start-up. It can be used to evaluate a proposed line design or to develop a feasible line design and to estimate its cost. This proposed model integrates mixed-model learning curves with aggregate planning under learning and a mixed-model line design into a comprehensive framework designed to minimize the total cost of the line during the start-up period.