Design of Manufacturing Systems to Support Volume Flexibility

ABSTRACT This paper presents an Axiomatic Design framework formanufacturing system design and illustrates how leancellular manufacturing can achieve volume flexibility. Axi-omatic Design creates a design framework by mappingthe functional requirements of a system to specific designparameters. Volume flexibility is often neglected as arequirement of manufacturing systems. Very few indus-tries are fortunate enough to experience stable or pre-dictable product demand. In reality, demand is oftenvolatile and uncertain. It is important that manufacturingsystem designers are aware of manufacturing systemtypes which can accommodate volume flexibility and fol-low a structured design methodology that assures that allrequirements are met by the system. INTRODUCTION Recent decades have led to the development and prolif-eration of many new paradigms in manufacturing. Withthe advent of Numerically Controlled (NC) and later Com-puter Numerically Controlled (CNC) machine tools androbotics, the complexity of manufacturing systems hasgrown considerably. In many instances, the advantagesand limitations of these new tools were not understood.This confusion led to many costly mistakes in manufac-turing system design. Many companies believed thatautomation was the wave of the future and invested inexpensive automated systems only to find that they werenot cost effective.There are two reasons why such mistakes have beenmade and continue to be made. First, the manufacturingfield as a whole does not fully understand the advantagesand disadvantages of different types of manufacturingsystems. Since the mid-1970's the variety of manufactur-ing system types has grown considerably. Since thattime, Flexible Manufacturing Systems, Agile ProductionSystems, and Lean Cellular Systems, have becomeaccepted types of manufacturing systems. Prior to that,the main types of systems were limited to Job Shops("jumbled flow" systems), Disconnected Flow Lines(Batch Production), and Transfer Lines. The develop-ment of new system types complicates manufacturingsystem design considerably. Careful consideration of therequirements of the system is required to support aninformed system type selection.A major reason why highly automated manufacturing sys-tems may not be cost effective is that product demandcan be very unpredictable. Generally, the more auto-mated the system is, the less flexible it is in terms of vol-ume. An automated transfer line, for example may be themost cost effective type of system available at a particu-lar production rate. If demand increases or decreases,however, an automated system is either unable to meetthe demand or must take a variable cost increase (over-time, etc.) to do so. In many industries, demand is vola-tile and uncertain. As a result, the forecast of demand israrely accurate. Figure 1 illustrates that even with anaccurate forecast, demand will be normally distributedabout the forecast. If the forecast is skewed, the actualdistribution will be shifted either to the left or right.Figure 1. The uncertainty of the demand forecastThe problem of forecasting is magnified as the leadtimerequired to construct and validate a manufacturing sys-tem increases. As this leadtime increases, a longerrange forecast is required. The deviation ( ∆) between theforecast and the actual demand can be expected toincrease the farther into the future the forecast predicts.The second reason for ineffective manufacturing systemdesigns is that there has been no structured methodol-ogy to follow. Tools such as Quality Function Deployment(QFD) and Axiomatic Design have proven to be very