Industrial Objectives and Industrial Performance E-Book

Lamia Berrah

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 383

Veröffentlichungsjahr: 2018

Beschreibung

This book aims to provide a synthesis of work and ideas done by our team over the last fifteen years in the field of information processing for expression of industrial performance. The statement of objectives on the one hand and the calculation of the other performances are discussed, with the search for the explanation of the link between these two basic steps of an industrial improvement. Beyond the synthetic and typological character of this study, the originality of this work lies in the consideration of the temporal dimension of the objectives, and spread on performance expressions. A fuzzy processing and multi-criteria aggregations time information that can be quantitative, qualitative or symbolic are proposed, in line with industrial practice and literature in the field of performance management.

Leseprobe

Table of Contents

Cover

Title

Copyright

Foreword

1 The Industrial System

1.1. Introduction

1.2. The

RB

company’s “Hydraulic Cylinder Production” line

1.3. Characterization of the industrial system

1.4. A few words about information handling for the “Hydraulic Cylinder Production” line of the

RB

company

1.5. Obj ectives and systems theory

1.6. Summary

2 Industrial Objectives: The Variable

2.1. Introduction

2.2. The objective and the variable: re-reading the tale of the chicken and the egg

2.3. Definition of the notion of a variable

2.4. When a variable becomes a criterion

2.5. Industrial typology

2.6. Relationships between variables: industrial practice

2.7. Semantic and choice of a variable: the power of an intention

2.8. Summary

3 Industrial Objectives: The Value

3.1. Introduction

3.2. A value to define the objective

3.3. The value and the intention

3.4. The value and the time

3.5. The observer’s intention and the temporal horizon: converging perspectives

3.6. What is said about objectives

3.7. Summary

4 Industrial Objectives: A Fuzzy Formalization to Move from Natural Language to Numbers

4.1. Introduction

4.2. The interest of using the theory of fuzzy subsets

4.3. When Mr.

C.C.

expresses himself about the Throughput time of the “Hydraulic Cylinder Production” line

4.4. Numbers and words

4.5. Graduality and fuzzy subsets

4.6. Operations between fuzzy subsets

4.7. Imprecision of measurements and theory of possibilities

4.8. Summary

5 Industrial Objectives: Outlining Performance Expression

5.1. Introduction

5.2. The notion of performance

5.3. From performance to performance expression

5.4. The process of

precisiation

of the finality into obj ectives : model and notations

5.5. Computation of performance expression: our assumptions

5.6. Summary

6 Industrial Objectives: Computation of Performance Expression of the Desire-Objective

6.1. Introduction

6.2. Returning to the notion of the desire-objective

6.3. “Computation” of the performance expression of a desire-objective

6.4. The observer expresses their “feeling” directly

6.5. The observer has a measurement value associated with the considered variable

6.6. The observer has a set of measurement values or of information associated with the considered variable

6.7. Looking back over computation

6.8. Summary

7 Industrial Objectives: Computation of the Performance Expression of the Requirement-Objective

7.1. Introduction

7.2. Returning to the notion of a requirement-objective

7.3. A few points about the notion of scale

7.4. Computation of the performance expression for the improvement-objective

7.5. Computation of the performance expression of the inadequacy-objective

7.6. Summary

Conclusion

Bibliography

Index

End User License Agreement

List of Tables

1 The Industrial System

Table 1.1. Measurement formats for the line’s “classics”

Table 1.2. Data given to Mr. C.C. concerning the “Hydraulic Cylinder Production” line

2 Industrial Objectives: The Variable

Table 2.1. Mr. C.C. describes, depending on the attributes that he has selected, the alternatives in relation to the reduction of the Throughput time

Table 2.2. Mr. C.C. gives sense to the values of his attributes, in light of the alternatives that he has examined

3 Industrial Objectives: The Value

Table 3.1. The company RB displays the eight rules of its RB Production System

Table 3.2. Interactions between the objective value, its semantic and the temporal horizon which can be associated with it

Table 3.3. Typology of action verbs for objective declaration* [DUC 99, p. 95]

Table 3.4. Mr. C.C. declares his objectives for the “Hydraulic Cylinder Production” line

4 Industrial Objectives: A Fuzzy Formalization to Move from Natural Language to Numbers

Table 4.1. Correspondence between numerical values and linguistic terms used by Mr. C.C. to qualify the Throughput time

6 Industrial Objectives: Computation of Performance Expression of the Desire-Objective

Table 6.1. Mr. C.C. gives the relation between the linguistic terms of the performance measurement values and the performance expressions

Table 6.2. Mr. C.C’s team turns their hand to all that is fuzzy and to Ecology of the line

7 Industrial Objectives: Computation of the Performance Expression of the Requirement-Objective

Table 7.1. Value and temporal horizon associated with the requirement-objective

Table 7.2. The improvement-objectives of Mr. C.C.

Table 7.3. Comparison function for computation of the performance expression associated with the Throughput time

Table 7.4. Reminder of the inadequacy-objectives associated with the Throughput time and with the Non-compliance rate

Landmarks

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Table of Contents

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e1

Industrial Objectives and Industrial Performance

Concepts and Fuzzy Handling

Lamia Berrah

Vincent Clivillé

Laurent Foulloy

First published 2018 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK

www.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA

www.wiley.com

© ISTE Ltd 2018 The rights of Lamia Berrah, Vincent Clivillé and Laurent Foulloy to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2017964349

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-84821-955-7

Foreword

The era of “make then sell”, harking back to a world where supply was lower than demand, is now long gone for most products, and therefore for most companies. Competition has made a permanent quest for improvement into an absolute imperative for guaranteed survival. With this in mind, performance measurement is the first step (diagnosis) and the last step (results analysis) and also the leitmotif of improvement projects, all at the same time.

It is therefore not surprising that the number of scientific publications about performance evaluation increased spectacularly at the end of the 1990s, with more than 3600 articles published between 1994 and 1996, and a book published every two weeks just in the USA1.

On the basis of consultants’ practice on the one hand, and inspiring references on the other, companies have set up scorecards often including tens of KPIs (Key Performance Indicators), with the aim of comparing themselves to and measuring themselves up against the competition. Affirmation of “Business Intelligence”, supported by ever more widereaching information systems, could therefore have sounded the death knell for the performance measurement adventure and its shift to becoming a standard routine activity; in short, a done deal. However, the problem appears to be far from solved: in fact more than an estimated 50,000 scientific articles will be published on the subject in 2017...

Indeed, just by looking at the reality of industry, we can clearly see the problems that remain: in many companies, precise and up-to-date scorecards (a requirement of visual management…) continue to be based on badly formalized objectives, handled by performance measurements with many undesired effects; misunderstandings build up between supply chain partners, brought on by different interpretations of common performance measurements which are often greater sources of dissent than they are founding blocks for collaboration.

In this context, it can be tempting to have more confidence in external reference sources than in one’s own beliefs. If, in this book, you are looking for a list of performance measurements randomly grouped together à la Jacques Prévert that you can stick onto your production systems, it would be best to put the book back on the real or virtual shelf from which you picked it up. If, on the contrary, you are prepared to undergo a journey through the world of performance which will make you think first about the finality of performance measurement, then about its constituent elements, without denying its subjective nature, then this book is for you. If you are curious about the reasons why a concept exists, about looking beyond its label, then the authors will give you the keys to a process of deep thinking which will lead you through all the different definition steps of the performance measurements that you require.

In this book, there will be no narrow-minded vocabulary, which would erase any doubts you may have but would effectively cut you off from your partners... While a large number of authors make the observation that performance evaluation, an exercise which by nature ought to be multidisciplinary, has been monopolized by various schools of thought that communicate little with each other, here the authors are instead seeking to build bridges rather than barriers. Additional clarification of the concepts used will therefore be provided, using a “pointillist” approach which leads to analysis of the interactions between the different aspects of production.

As you turn the pages, you will be taken back to user requirements, you will think about the finalities of the industrial system, about the links to be established between its performance measurement system and its control system, and also its improvement issues. You will clarify the links between objectives, goals and finalities, criteria, variables, values, etc. You will see that subjective performance evaluation is possible, and finally you will think about measurement of objective achievement...

Enjoy the journey!

Bernard GRABOTProfessorEcole Nationale d’Ingénieurs de Tarbes

1

Folan, P., Browne, J., A review of performance measurement: Towards performance management,

Computers in Industry,

56, pp. 663–680, 2005.

1The Industrial System

1.1. Introduction

Once upon a time there was a system and an actor. The system functioned and evolved within its environment. The actor, responsible for this operation and this evolution, spent their time observing the system, as a whole, as different parts. They attributed objectives to it, planned actions whose implementation they then managed, expressed the level of performance achieved, and started over with their observation cycle.

So, the tale of objectives begins with a relationship between an actor, a system observer and the system in question. The actor observes the system. Arising from this observation, a representative model is born, brought on by the presence of the actor acting for the system’s structure and operation. Intentions then occur to the actor, for all or part of the system. Therefore, we have the system, the actor, the state of the system observed by the actor, and so the actor’s intention acts as the decision-maker for the system or part of the system. In particular, the actor defines the goals and objectives to be achieved by the system (or part of it).

Thus, the notion of objective emerges from the relationship between the actor and the system. This relationship, both objective and subjective, real and tangible, is based on a large number of aspects that are probably interacting with each other. This is why we will borrow systems theory’s principles and language to comprehend this relationship. Flexible and all-encompassing, systems theory will then allow us to identify links between the various aspects of a system, in particular the entities, the finality, the structure and the behavior... and, consequently, the goals and objectives, all this in a given context and for a given observer.

So, let us begin by recalling some elementary principles of systems theory. Placing ourselves in an industrial context, we will then describe, using the systemic language, what we intuitively call the “industrial system”. By industrial system, we mean all the operations and all the equipment, used in industrial activities1. The two latter parts of this description will be dedicated to objective-related information and then to objectives themselves. A representation of the emergence process of the objective, as proposed by the systems theory model, will then round off this exploratory chapter.

But before we get to the heart of the matter, let us take ourselves back to January 2009 and pause to look at the story of Mr. C.C., executive of the RB company and newly appointed associate manager for the “Hydraulic Cylinder Production” line.

1.2. The RB company’s “Hydraulic Cylinder Production” line

Resulting from the 2001 merger of companies R and B, the RB2 company has a Business Turnover of 4.9 billion euros and 26,000 employees, spread across 41 sites around the world. The RB company is the world leader of the industrial automation and mobile application markets. The company produces “hydraulic equipment” (proportionately 80% of the Business Turnover), “pneumatic equipment” (proportionately 15%) and “linear guidance parts” (proportionately 5%). The RB company designs, produces, distributes and carries out maintenance on all its products.

More precisely, at the company’s Belleville site automation components are produced; mainly “Cylinders” and “Distributors”. The technologies used are respectively pneumatic and hydraulic. This production therefore includes four product families, in other words “Metal air distributors”, “Plastic air distributors”, “Pneumatic cylinders” and “Hydraulic cylinders”. Since the site has had ISO 9000 certification for the last 15 years or so, production is organized into processes. Four “value-added” processes in particular take place on this site, corresponding to the lines allocated to the four product families which are manufactured on it.

In particular, with its 22 machines, six activities and 30 operations, the “Hydraulic Cylinder Production” line is dedicated to production of “Hydraulic Cylinders”. With a production volume of “80 units per day” and a range of more than 106 possibilities, the “Hydraulic Cylinders” are produced in very small batches (mean average size of 1.6 cylinders), complying with classification systems which are broken down into 15 to 20 components depending on the options chosen, with a diameter of between 16 mm and 250 mm and stroke lengths ranging from 1mm to 3000 mm. With opening hours of the order of 10 hours per day and a delivery time of “around 3 weeks”.

In line with the example set by the RB company, the Belleville site is organized in a functional manner. As the company subscribes to continuous improvement philosophy and development, its organization and working methods are revised regularly. Having recently moved from the Methods and Industrialization department to the Production and Continuous Improvements department on this site, Mr. C.C. takes over responsibility for the “Hydraulic Cylinder Production” line in January 2009, and has invited us along to experience the first 6 months of his new position at his side, time enough to observe him: observing the line, declaring his objectives, and drawing up the results of some of the actions put in place.

More precisely, Mr. C.C. does indeed have ideas about the operation and improvement of performance of the line. However, in order to be able to specify how his plans will be implemented, Mr. C.C. would like to take the time to observe his system and to understand its inner workings. To do this, Mr. C.C. will spend much time, during the last quarter of 2008, in discussion with Mr. M.N., associate manager of the line since it was set up. To this end, Mr. M.N. begins by broaching the subject of the Overall Equipment Effectiveness – OEE, the Non-compliance rate and the Throughput time.

1.2.1. The Overall Equipment Effectiveness – OEE

Classic productivity indicator, the Overall Equipment Effectiveness – OEE was defined in the 1980s in Japan as being associated, on an elementary level, with the productivity of a “piece of equipment” within the productive system (machine, production cell, line) [MUC 08]. The Overall Equipment Effectiveness – OEE is computed for predetermined amounts of time, generally a day, a week or a month and applies to both a “Piece of Equipment” and “All Equipment” in the system.

The Overall Equipment Effectiveness – OEE is computed as a ratio between the useful time and the Planned production time associated with, respectively, the “Piece of Equipment” or “All Equipment” under consideration. The Planned production time is obtained from the Open time of the productive system, from which all the planned stops within the observation period have been removed. The Useful time is computed from the Planned production time by cutting out, this time around, all the unplanned stops (unplanned stops, loss of performance and quality losses) as shown in Figure 1.1, extracted from the standard NF-E60 182 [AFN 02]. To a great extent now standardized, computation of the Overall Equipment Effectiveness – OEE is therefore based on a generic model which identifies all the related types of planned stops and unplanned stops, for the part of the system under observation.

Figure 1.1.Details of the time periods used to compute the Overall Equipment Effectiveness – OEE (inspired from [AFN 02])

For the “Hydraulic Cylinder Production” line, the Planned production time is known and the unplanned stops are standardized. The latter are manually recorded daily, by staff. The Overall Equipment Effectiveness – OEE is computed weekly. A “65.0%” value of this rate represents the expected improvement of the line.

1.2.2. The Non-compliance rate

Intuitive, the Non-compliance rate relates to the compliance of “Manufactured products”. This rate is an overall computation, on the basis of the ratio between the Quantity of products affected by a compliance problem (i.e. some kind of non-compliance) and the Produced quantity [WEB 12].

As soon as a compliance problem is detected on the “Hydraulic Cylinder Production” line, the staff member – detector – inputs it manually. Given the line production data, more than 1500 articles are likely to pose a compliance problem, each day. The line’s Non-compliance rate is given to never surpass “1.20%”.

1.2.3. The Throughput time

The Throughput time can be defined as follows: “the amount of time required for a product to pass through a manufacturing process, thereby being converted from raw materials into finished goods” [BRA 14]. Computation of the Throughput time is based on observation of both the value-added time corresponding to line activities and the no value-added time encompassing waiting time, transport and product storage. More specifically, in companies using discontinuous production processes, value-added operations on products generally represent a very low proportion of the time spent by the products on the production lines. Most of the time, the product waits “in fact for the whole batch to be finished, for transport to another machine, for a compliance control check... This relationship between value-added time and waiting time can be of the order of 1/10000.In companies with ‘just-in-time production’ this relationship is of the order of 1/100 and, in the best case scenario, of the order of 1/10”* [MAR 13].

Computation of the Throughput time for the “Hydraulic Cylinder Production” line is based on readings made by company employees, who swipe the barcode of each manufacturing order, respectively before and after each value-added operation. These readings are taken respectively in seconds, minutes, hours or days, depending on the type of operation in question. An arithmetical average of the Throughput times for the various “Hydraulic Cylinders” produced by the line is then computed, generally for a period of 1 month, which generally represents 1500 to 2000 “Hydraulic Cylinders”. The nominal value of the Throughput time for the line is “8 days”.