A Systems Approach to AMT Deployment

Frontmatter

1. Setting the Scene

Abstract

Over the last few decades there have been countless surveys which have disclosed the difficulties involved in introducing new technology into manufacturing industry. Such surveys are usually conducted by external observers and consultants, who examine the attitudes of senior management to these difficulties. Our approach is to concentrate more on the behaviour of middle and lower managers, with emphasis on the detailed analyses of industrial performances in real time. These analyses involve a unique comprehensive system of information gathering including questionnaires, structured interviews, analysis of company data and the generation of our own data.

A. Davies, J. E. Cherrington

2. Organizational Factors Affecting the Introduction and Efficiency of AMT Operation in Small Firms

Abstract

A number of authors have stipulated that organizational and human factors are more critical than technological factors in advanced manufacturing technology (AMT) project management and implementation programmes [1], but what are “organizational factors” and how can we identify them?

D. G. Coward, E. Schott

3. Combined Company Profiling

Abstract

The successful implementation of advanced manufacturing technology can result in substantial improvements in productivity and competitive advantage. The key words are “successful implementation”; the use of computer-aided production management systems and CNC machine tools has been widely documented. Unfortunately many implementations have not performed anything like as well as expected. The question has to be asked: Why? An obvious answer is the fact that manufacturing companies can vary enormously in terms of product, management, manufacturing technology, labour and last but not least financial backing. One of the first steps along the path to discovering what makes a successful user of AMT is the development of a classification system. If one company can be assessed against another then the possibility of defining the characteristics or elements required for the successful implementation of AMT should be greatly enhanced.

T. H. A. Burden

4. Learning Curve Models

Abstract

In using learning curves for AMT startup, we seek to identify a number of patterns in the basic data, each of which is an important source of information to be fed into the management control machinery. These patterns may be classified as follows:

1.

A trend line, which in some “best” sense can be used for predicting future output. This line can be influenced by proper design and planning of the product line.

 

2.

“Normal” scatter about the trend line, which constitutes a natural and acceptable variation, and which can be used for setting the upper and lower bounds of predicted output.

 

3.

“Abnormal” scatter about the trend line, which results in an unacceptable variation. It indicates an avoidable loss in production which can be traced to an assignable cause and hence eliminated by management control.

 

4.

“Deterministic” changes in the trend line. These may be long- or short-term, and have an assignable cause. An example of a management-induced cause is a planned change in the size or constitution of the direct labour force.

 

D. R. Towill, J. E. Cherrington

5. Forecasting via Learning Curves

Abstract

In Chapter 4 we met the family of learning curve models which can be used to describe the dynamics of AMT startup. We now need to develop algorithms which will estimate the parameters for the selected model. If the modelling is to be undertaken on a historical basis, i.e. if the effective steady state has been reached, then simple graphical techniques may prove adequate, especially if the data is smoothed before curve fitting takes place.

D. R. Towill, M. M. Naim

6. Dynamics of AMT Capacity Planning

Abstract

The introduction of advanced manufacturing technology (AMT) to an industrial concern can result in a protracted startup period. This may well extend into the anticipated operating phase of a new installation and thereby limit the productive capacity of the plant. In assessing the dynamics of capacity planning we need to understand the significance of any estimate made of Ŷ _c (the initial productivity), Ŷ _f (the productivity gain) and \(\hat{\tau }\) (the rate at which the improvement in productivity is gained). “^” means the best estimate available at the time a forecast is to be made.

A. Davies, H. Lewis

7. Use of Discrete Event Simulation in Evaluating FMS Performance

Abstract

Discrete event simulation (DES) is a well-recognized technique in evaluating the performance of flexible manufacturing systems (FMS). FMSs lend themselves to such a method because of the inherent complex element interactions, the queueing principles involved and the changes of state that occur within them. In particular, to attempt to rely on intuition, experience or static optimization alone can lead only to a limited FMS design solution. DES allows the analyst to recognize the dynamics of FMS while also allowing him to interact with the system model in such a way that changes in, say, layout, system design and operation strategies (scheduling, routing, etc.) may be assessed. Hence, “what if?” scenarios are orchestrated [1]. The analyst not only is able to make changes to the simulation rules but also is capable of altering data records and displays.

M. M. Naim, S. M. Hoh

8. FMS Shop-Floor Experience

Abstract

The all-embracing definition of AMT referred to in Chapter 1 may well be valid; in practice, however, advanced manufacturing technology is often thought of as being synonymous with flexible manufacturing systems (FMS). These systems are typified by the use of computer-controlled production equipment, and, depending upon the level of sophistication, can form an extensive automated and integrated machining/assembly plant.

A. Davies, M. M. Naim

9. Case Studies Based on Three AMT Users

Abstract

The analysis of productivity losses during startup requires management to determine the time when, in their view, commissioning finishes and production startup commences. In larger companies this is relatively straightforward because system engineers record the time of handover of the AMT to production personnel. Unfortunately, with smaller companies it is not always possible to identify this change so precisely.

D. G. Coward, J. E. Cherrington

10. Organizational Problems in the Introduction of AMT into the Large Firm

Abstract

The following study provides a detailed description of the non-technical, organizational factors affecting a £3.2m AMT project. The host organization is defined primarily in terms of its structure and culture before and after the AMT project. Prevalent attitudes among those in a position to influence AMT implementation and its operation are also revealed in transcribed excerpts of tape-recorded interviews.

E. Schott, M. M. Naim

11. AMT Vendor Experience

Abstract

In examining the conception, design, planning, implementation and steady-state operation of the flexible manufacturing system (FMS) as a production facility (as described in Chapter 7), it is necessary to ensure that “fact” is filtered from “fiction”. This is not to say that facts are intentionally withheld, or that rather colourful claims are deliberately made. However, if an FMS is treated in isolation without obtaining a relative perspective of its capabilities and performance then it is very easy to make false judgements.

M. M. Naim, E. Schott

12. General Methodology for Smoothing the Introduction of AMT

Abstract

Most of the organizations investigated in this study had some experience of computerized equipment and were interested in acquiring more. Some of these organizations were recognized as brand leaders, with excellent reputations in applying high technology. Even so, only a few companies were obtaining the full benefits of AMT as measured by such parameters as programmed unmanned running. The reasons for this were many, but more often than not amounted to organizational faults. With hindsight, these were inexplicable, because it is likely that all these organizations would recognize the stages outlined in Fig. 12.1 as those comprising a general methodology for smoothing the successful introduction of AMT. However, no organization would necessarily accept the reasons why it had failed to adopt the methodology completely.

J. E. Cherrington, D. G. Coward

Backmatter