Gdm Frizelle

Measuring complexity as an aid to developing operational strategy

One of the difficulties in developing a coherent operational strategy is to know how the various elements of a manufacturing system interact and to assess the relevant importance of each. Looks at the manufacturing systems and how complex they are. A measure which calculates the systems′ complexity and the contribution from each operational source has been developed. It thus provides a tool that can assist in a strategy development exercise by quantifying the problem areas on a common basis. The approach has been used at three manufacturing sites. The resulting analysis allowed the local management, in each case, to identify the key areas of weakness, in both the short and medium term. As such it gave each of them a possible starting‐point from which to formulate an operational strategy.

An information‐theoretic methodology for measuring the operational complexity of supplier‐customer systems

In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to exhibit operational complexity. The operational complexity of supplier‐customer systems is primarily characterised by the uncertainty of the system. As the operational complexity of a system increases there is an associated increase in the amount of information required to monitor and manage that system. Based on this understanding, a novel information‐theoretic entropy‐based methodology for measuring and analysing the operational complexity of supplier‐customer systems has been developed. This paper makes contributions in the theoretical, conceptual and practical developments of the methodology. The methodology can quantitatively detect and prioritise operational complexity hotspots. At the interface, the framework can identify and quantify the transfer of operational complexity. Within the internal manufacturing system, the framework...

An entropic measurement of queueing behaviour in a class of manufacturing operations

This paper is motivated by a view that there is practical value in being able to measure aspects of complexity in industrial, particularly manufacturing, systems. We address, at a decreasing level of generality, the following questions. What is required from a measure that might reflect some aspects of complexity in a large dynamical system? What is the appropriate measure? How do the main characteristics of this measure show themselves in the systems of interest? Does the proposed measurement process lead to useful theoretical and practical insights? In answer to questions (i) and (ii), we suggest that in general one measures the rate of variety of behaviour the system can exhibit, and propose the Kolmogorov–Sinai (KS) entropy of the corresponding random process as a convenient measure. We then consider input–output processes as models for manufacturing systems and discuss some simple mathematical observations on how the KS entropy can be assessed in terms of random queues and a state of the server. Next, we take into account some basic features of a manufacturing process and propose formulae for its operational and structural complexity, thus answering (iii). Finally, to answer (iv), a case study is given demonstrating how the proposed measure can be used in a manufacturing plant, and we discuss practical insights for the company involved.

Minimizing the number of tool switches on a flexible machine: An empirical study

This paper looks at the issue of tool switching in manufacturing companies. The findings, based on work with seven companies, show that industry is aware that excessive tool switches can result in substantial time being spent in tool set-ups. The efficiency of the methods currently employed by these companies was assessed. These methods were compared with some available tool switching heuristics. The results show that tool switching heuristics are applicable to real problems in industry and that they consistently outperform the current methods used within companies.

The measurement of complexity in production and other commercial systems

The paper gives a review of three case studies of complexity of production systems in manufacturing and commercial industry and develops mathematical methods stemming from these studies. We use as measures of complexity various (long term) entropy rates that naturally emerge in the analysis of systems under consideration; in our case, the main focus is on (physical or virtual) queues and related phenomena. Consequently, a system is considered ‘more complex’ when its entropy rates are higher. The same principle is applied when different subsystems of a given system are compared with each other, identifying a ‘bottleneck’. The numerical values for entropy rates are determined in the course of observation and recording, subject to some simplifying assumptions. To enable us to make effective comparisons, we introduce various classifications of queue-related conditions in systems under investigation. We also discuss a number of practical issues that emerge here, including noise and data loss.

Deriving a Methodology for Implementing CAPM Systems

A methodology for implementing CAPM systems is described. The research was motivated by evidence of dissatisfaction with the performance of current systems, and the existence of no generic methodology. A superposition process was employed. Areas of functional management were explored for sources of implementation methodologies and yielded a number of attributes for successful implementation. The emergent structure was then validated against field studies. The result, a methodology for improving control, is a three‐level hierarchy. The first level assesses the ability of the organisation to absorb change. The next considers the options for better control. The lowest level is concerned with implementation.

Complexity in the supply chain

It is well understood that supply chains are complex. However less clear is just what complexity means in this context. This paper reports on the outcome of five years of research on complexity in supply chains. One of the outputs from the research has been the development of a metric to measure one form of complexity within the chain, called operational complexity. Three elements are identified. The first two are referred to as structural complexity. They cover how products are allocated to resources in the chain and how the chain is controlled. The third element is how the chain performs. In particular does it behave in a predictable way. A model has been developed along with a metric to measure complexity. The ideas were applied to two distinct types of chain. The first was a typical make to stock environment. Here the aim was to reduce inventory in the chain. Reducing operational complexity was seen as a way of doing this. The second was a design to order environment. The findings in each case helped the chains both to understand better the mechanisms involved and to bring about improvements.

A classification and measurement structure for manufacturing plants

Abstract Traditional ways of classifying manufacturing plants are proving increasingly unsatisfactory, particularly with the advent of flexible manufacturing systems (FMS). An alternative is proposed based on the idea that the plant structure can be used as a basis. This is seen to evolve from progressively mapping product structures (referred to as product path structures) onto the resources available. It results in six identifiable structures, referred to as Cottage Industry, I, V, A, Diamond and T. In addition a measure of complexity for each type of plant is developed based on the extent to which its structure distorts flow. The measure, based on information theory, relates to the likely extent of the distortion. The measure is then used to make a number of predictions about how the six plant structures will behave

Minimizing the number of tool switches on a flexible machine: An experimental study

Abstract Tool switching heuristics determine the sequence for the parts and the associated sequence for the tools for the tool magazine so that the total number of tool switches is minimized. This paper examines whether there is a need for tool switching heuristics in industry and assesses the validity and usefulness of current approaches. Studies that have tested the performance of tool switching heuristics are examined and their flaws highlighted. The research then goes on to test the heuristics on a much broader range of problems using a rigorous framework. The results reveal which heuristics perform more robustly than others and link the performance of different heuristics to different problem types.

CIM2000: a tool to help SMEs develop operational strategy

This paper presents an approach developed to assist small- to medium-sized enterprises (SMEs) in manufacturing to formulate operational strategy. Such companies have particular problems when faced with making strategic planning and investment decisions. They rarely have either the time, money or expertise to do it unaided. The CIM2000 tool was created as a possible way to provide relatively quick and inexpensive help. It comprises a methodology supported by interactive software. The methodology is undertaken in a workshop and aims to build consensus and reach agreed conclusions. It is linked to a best practice data base. The tools have been tested in ten SMEs selected for the diversity of businesses that they represent. The findings showed that they felt that the exercise had brought tangible benefits to their company.