View
4
Download
0
Category
Preview:
Citation preview
Advanced Planning and Scheduling inManufacturing and Supply Chains
ThiS is a FM Blank Page
Yuri Mauergauz
Advanced Planning andScheduling inManufacturing and SupplyChains
Yuri MauergauzSophus GroupMoscowRussia
ISBN 978-3-319-27521-5 ISBN 978-3-319-27523-9 (eBook)DOI 10.1007/978-3-319-27523-9
Library of Congress Control Number: 2016933485
# Springer International Publishing Switzerland 2012, 2016This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part ofthe material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmissionor information storage and retrieval, electronic adaptation, computer software, or by similar ordissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in thispublication does not imply, even in the absence of a specific statement, that such names are exemptfrom the relevant protective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in thisbook are believed to be true and accurate at the date of publication. Neither the publisher nor theauthors or the editors give a warranty, express or implied, with respect to the material containedherein or for any errors or omissions that may have been made.
Printed on acid-free paper
This Springer imprint is published by Springer NatureThe registered company is Springer International Publishing AG Switzerland
Additional material to this book can be downloaded from http://extras.springer.com.
Preface to the English Edition
Despite the relatively large number of books related to production planning
published in English, up to now information constituting the subject of Advanced
Planning and Scheduling has not been gathered together. This situation inspired the
author to present an English translation of his Russian-language book.
This book was conceived as a guide to modern methods of production planning,
based on fairly new scientific achievements and various rules of thumb of practical
planning. Most of the calculation methods are illustrated with numerical examples.
Attached to the English edition is a set of programs for calculating production
schedules and an example of an ERP system operating in the cloud.
The author expresses his profound gratitude to Federica Corradi Dell’Acqua of
Springer publishers. Her systematic support allowed this project to be implemented.
Moscow, Russia Yuri Mauergauz
v
ThiS is a FM Blank Page
Preface to the Russian Edition
At the end of the last century, a large new field of knowledge developed. Nowadays,
it is called “industrial engineering” and is a creative application of the methods and
principles of various scientific disciplines to achieve and maintain a high level of
productivity and profitability in modern industrial enterprises.
The application of industrial engineering is inextricably linked with the use
of quantitative methods using information that circulates in the production system,
and such methods often have complex mathematical justification. Historically,
the concept of industrial engineering started to be used after wide application
of methods known as “operations research”. Another name for these methods is
“management science”, now more commonly called “industrial engineering”.
Since the foundation of industrial engineering is quite sophisticated mathemati-
cal techniques, its application possibilities are determined largely by the available
computing power. Originally, computers were created to solve complex scientific
problems. Subsequently, this equipment started to be used to develop automated
control systems including production management systems.
The introduction of personal computers changed dramatically the possibilities
and the main focus of application of computer technology. The main objective
of computerization in the late twentieth century was automation of accounting
of a variety of resources and operations with them, i.e. information storage. The
automated control systems of enterprises were mainly designed to collect and
integrate data referring to production and sales. Therefore, the development of
industrial engineering at that time was mostly of a scientific and theoretical nature.
In the early twenty-first century, however, the situation changed dramatically.
First of all, against the background of rising resource prices, the issue of production
efficiency is becoming more and more important. In addition, it was found that,
despite their great diversity, the number of accounting problems is limited and most
problems had already been solved, while the increasing capabilities of computer
technology allow more complex problems to be solved. As a result, researchers
and production managers began to turn to the problems of enhancing production
management.
There was a sharp increase in the number of articles in the field of industrial
engineering and a rapid increase in the number of relevant scientific journals.
Today, worldwide, there are at least 30 international English-language journals in
vii
which thousands of scientific articles on industrial engineering are published
annually. In addition, there are a number of national engineering journals, and
in some countries, such as Spain and Iran, they are published with simultaneous
translation into English.
The field of industrial engineering includes management aspects such as the
location of enterprises, determining the range of products, selection of necessary
processes, organization of production divisions, etc. Many of these management
objectives refer to pre-production, but not its realization. The effective implemen-
tation of production is only possible with organized and comprehensive sound
planning, which is actually the final component of industrial engineering.
Until the end of the last century, production planning was mainly based on the
knowledge and experience of the planners themselves who used quite elementary
methods of calculation for different purposes. The use of computer technology, for
the most part, was limited to calculation of the number of products and resources
required.
Due to the complexity of the mathematical description of plans, their optimiza-
tion appeared to be possible after the introduction of powerful personal computers
at the beginning of this century. The relevant methods were used to create a number
of new production control systems, known as APS and MES. In general, the new
planning methods based on complex mathematical models are called Advanced
Planning and Scheduling (AP&S). This book is intended for readers whose
activities are related to production planning, though in different business areas.
First of all, the book is intended as a reference guide for operating production
managers. As the workload of these specialists does not allow them to engage in a
consistent and detailed study of the various methods, the book is designed so that
almost every section, and sometimes even an individual paragraph, can be read
independently of the other sections. At the same time, wherever possible when
describing a method, reference is made to the preceding discussion of the method,
to allow deeper examination of the material.
To make the presentation of each section independent of the previous text,
most of the methods and examples use the same designations of variables and
parameters, and these designations are listed in Appendix A. In those cases where
the designation does not coincide or is not referred to in Appendix A, it is defined in
the text. Each example is accompanied by the method reduced to a final calculation.
The author hopes that this structure will be convenient for developers of production
planning software as well as for production managers.
Not all planning methods described in this book are useful in practice. This
applies to a number of problems and their solutions, which provide a scientific basis
for comparison and a reference sample for other methods, which in turn may be
used in practice.
On the other hand, the book is constructed to provide the opportunity to study
the material consistently. The book is divided into two parts, the first of which
is dedicated to detailed description of models of planning, and the second part
describes the processes carried out on the basis of these models. Some of these
viii Preface to the Russian Edition
models are quite complex, and at first acquaintance their study can be skipped. This
construction is to facilitate learning by researchers, postgraduates, and students.
The challenge in writing this book was the selection of materials and the
sequence of their presentation. An enormous number of different methods of
production planning have been developed. In particular, G. Halevi’s reference
book on production planning methods dated 2001 describes 110 methods, which,
of course, vary to a large extent in the degree of distribution and application. This
book includes those models and planning processes which by the time of writing
were in focus in the scientific literature. It was assumed that production planning
itself is closely connected to the planning of inventory because the result of the
manufacturing process is stock buildup.
The contents of the book, for the most part, are based on the results of scientific
papers contained in a number of English-language guides, monographs, and articles
written at the end of the twentieth and beginning of the twenty-first century. The
author has also tried whenever possible to use the available, albeit few, modern
Russian-language works. Materials relating to the period of development of com-
puter systems in the Soviet Union in the 1970s and 1980s have also been used. The
structure and nature of any presentation always depends largely on the author’s
position. In this case, when considering methods of production planning, special
attention is paid to its regularity and dynamics, i.e. a periodic recurrence and at the
same time the need to introduce various changes, including urgent ones.
Different scientific disciplines are used in themethods of production planning. Each
discipline has its own set of traditional symbols. In this book, itwas important to ensure
consistent use of symbols, so one designation system was chosen as basic. Therefore,
the nomenclature of symbols accepted in scheduling theory is used throughout; in
other cases, some symbols may be different from the conventional ones.
The author is grateful to Professor A.L. Ryzhkowhose comments and suggestions
helped to improve the presentation significantly.
Moscow, Russia Yuri Mauergauz
Preface to the Russian Edition ix
ThiS is a FM Blank Page
Annotation
Advanced Planning and Scheduling (AP&S) in Productionand Supply Chains
The book consists of two parts, the first of which considers construction of refer-
ence and mathematical planning models, production bottleneck models, and multi-
criteria models; examples of such models are provided. The methods of forecasting
and aggregate demand are discussed; background information about the storage and
data processing methods for planning are provided.
The second part analyses various models of stocks planning and the rules for
calculating safety stocks; it also describes the stocks dynamics in the supply chain.
Various methods of batch sizing are detailed. Production planning is studied at
several levels: planning of shipment to customers, calendar scheduling, and opera-
tional planning. Operational planning is considered separately for one-stage and
multi-stage problems as well as for different multi-criteria problems. For some
problems of multi-criteria, scheduling by the methods described in the book special
software is developed.
The book can be used as a reference for modern planning methods as well as a
teaching aid. It is intended for employees of planning and production services,
specialists in enterprise information management systems, and researchers and
graduate students involved in production planning. The book can be used by students
at technical colleges as a guide when writing course papers and graduate theses.
A description of a collection of production schedule programs and an example of
the ERP system operating in the cloud is included in the book.
Moscow, Russia Yuri Mauergauz
xi
ThiS is a FM Blank Page
Contents
Part I Modeling
1 Reference Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1 Modelling of Business Process . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Concept of Reference Model . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.1 Reference Models in Supply Chains . . . . . . . . . . . . . . 6
1.2.2 Reference Modelling Methodology . . . . . . . . . . . . . . . 7
1.3 Production Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3.1 Basic Types of Production . . . . . . . . . . . . . . . . . . . . . 9
1.3.2 Production Scale and Strategy . . . . . . . . . . . . . . . . . . 13
1.4 Advanced Planning in IT Systems . . . . . . . . . . . . . . . . . . . . . . 15
1.4.1 Planning in IT Systems . . . . . . . . . . . . . . . . . . . . . . . 15
1.4.2 Popularity and Effects of Advanced Planning . . . . . . . 19
1.5 IT System Interaction Standards . . . . . . . . . . . . . . . . . . . . . . . 21
1.6 Quality Parameters in Supply Chains . . . . . . . . . . . . . . . . . . . . 24
1.6.1 Markets and Their Main Properties . . . . . . . . . . . . . . . 25
1.6.2 Quality Parameters and Different Supply Chain
Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
1.6.3 Balanced Scorecard . . . . . . . . . . . . . . . . . . . . . . . . . . 28
1.7 Utility of Quality Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 31
1.7.1 Concept of Utility . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
1.7.2 Typical Utility Functions . . . . . . . . . . . . . . . . . . . . . . 34
1.7.3 Utility Functions in Business Process Quality
Evaluations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2 Mathematical Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.1 Simplest Planning Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.1.1 Classical Supply Management Model . . . . . . . . . . . . . 43
2.1.2 Continuous Linear Optimization Model . . . . . . . . . . . . 45
2.2 Correlations Between Mathematical and Reference Models . . . . 52
2.2.1 Main Criteria and Constraints . . . . . . . . . . . . . . . . . . . 52
2.2.2 Standard Classification of Planning Optimization
Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
xiii
2.2.3 Production Scale and Plan Hierarchy in Classification . . . 55
2.3 Priority Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
2.3.1 Simple Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
2.3.2 Some Useful Theorems . . . . . . . . . . . . . . . . . . . . . . . 62
2.3.3 Combined Priority Rules . . . . . . . . . . . . . . . . . . . . . . 62
2.4 Production Intensity and Utility of Orders . . . . . . . . . . . . . . . . 64
2.4.1 Production Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . 65
2.4.2 Dynamic Utility Function of Orders . . . . . . . . . . . . . . 70
2.5 More Complex Models of Linear Optimization . . . . . . . . . . . . 74
2.5.1 Integer Linear Optimization Model . . . . . . . . . . . . . . . 74
2.5.2 Integer Linear Optimization Models with Binary
Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
2.6 Fixed Job Sequence Models . . . . . . . . . . . . . . . . . . . . . . . . . . 78
2.6.1 Branch-and-Bound Method with Minimum Cumulative
Tardiness Tw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
2.6.2 Branch-and-Bound Method with Maximum Average
Utility V . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3 Production Bottlenecks Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
3.1 Theory of Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
3.1.1 Fundamentals of Theory of Constraints . . . . . . . . . . . . 89
3.1.2 Bottleneck Operation Planning . . . . . . . . . . . . . . . . . . 92
3.1.3 Planning for Buffers, Ropes, and Non-bottleneck
Machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
3.1.4 Simple Example of Theory of Constraints
in Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
3.1.5 Theory of Constraints in Process Manufacturing . . . . . 98
3.1.6 Review of TOC Applications . . . . . . . . . . . . . . . . . . . 100
3.2 Theory of Logistic Operating Curves . . . . . . . . . . . . . . . . . . . . 101
3.2.1 Production (Logistics) Variables . . . . . . . . . . . . . . . . . 101
3.2.2 Some Notions Used in Queuing Theory . . . . . . . . . . . . 105
3.2.3 Plotting Logistic Operating Curves . . . . . . . . . . . . . . . 107
3.2.4 Main Properties of Logistic Curves . . . . . . . . . . . . . . . 110
3.3 Application of Logistic Operating Curves . . . . . . . . . . . . . . . . 110
3.3.1 Logistic Positioning . . . . . . . . . . . . . . . . . . . . . . . . . . 110
3.3.2 Bottleneck Analysis and Improvements . . . . . . . . . . . . 111
3.3.3 Evaluation of Overall Production Performance . . . . . . 112
3.4 Optimal Lot Sizing for Production Bottlenecks . . . . . . . . . . . . . 116
3.4.1 Lot Sizing Heuristic . . . . . . . . . . . . . . . . . . . . . . . . . . 116
3.4.2 Analysis of Heuristic Solutions . . . . . . . . . . . . . . . . . . 119
3.5 Hierarchical Approach to Machinery Load Management . . . . . . 122
3.5.1 Principles of Workload Control Concept . . . . . . . . . . . 123
3.5.2 Example of Application of Controlled Load Approach . . . 124
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
xiv Contents
4 Multi-criteria Models and Decision-Making . . . . . . . . . . . . . . . . . . 127
4.1 Basic Concepts in Multi-criteria Optimization Theory . . . . . . . 127
4.1.1 Definition of Multi-criteria Optimization Problems . . . 127
4.1.2 Pareto Optimality . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.1.3 Main Methods of Solving Multi-criteria Planning
Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.1.4 Analytical Method of Constructing a Trade-Off Curve . . . 136
4.2 Optimized Multi-criteria Lot Sizing . . . . . . . . . . . . . . . . . . . . . 138
4.2.1 Lot Sizing Based on Costs and Equipment . . . . . . . . . 138
4.2.2 Analytical Lot Sizing with Two Criteria: Setup Time
and Cost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
4.3 Example of Multi-scheduling Problem . . . . . . . . . . . . . . . . . . . 143
4.3.1 Special ε-Neighbourhood of Efficiency Points . . . . . . . 144
4.3.2 Solving Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
4.4 Methods of Decision-Making Theory in Planning Problems . . . 150
4.4.1 Some Information from the Decision Making Theory . . . 150
4.4.2 Example of the Planning Problem Requiring Decision
Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
4.4.3 Decision-Making Based on the Guaranteed Result
Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
4.4.4 Optimistic Decision-Making . . . . . . . . . . . . . . . . . . . . 157
4.5 Applications of Complex Decision-Making Methods . . . . . . . . 158
4.5.1 Hurwitz Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
4.5.2 Savage Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
4.5.3 Shifted Ideal Method . . . . . . . . . . . . . . . . . . . . . . . . . 160
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5 Data for Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
5.1 Composition of the Data Used for Planning . . . . . . . . . . . . . . . 163
5.1.1 Archives of Design-Engineering Documentation and
Orders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
5.1.2 Reference Data and Standards . . . . . . . . . . . . . . . . . . 167
5.1.3 Databases of Transactional IT Systems . . . . . . . . . . . . 169
5.1.4 Decision Support Databases . . . . . . . . . . . . . . . . . . . . 170
5.1.5 Knowledge Bases . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
5.2 Data Storage and Management . . . . . . . . . . . . . . . . . . . . . . . . 174
5.2.1 Relational Databases . . . . . . . . . . . . . . . . . . . . . . . . . 174
5.2.2 Concept of Object-Oriented Databases . . . . . . . . . . . . 176
5.2.3 Database Management Systems . . . . . . . . . . . . . . . . . 177
5.2.4 Tiered Data Storage . . . . . . . . . . . . . . . . . . . . . . . . . . 178
5.2.5 Distributed Databases . . . . . . . . . . . . . . . . . . . . . . . . . 179
5.2.6 Service Oriented Architecture of IT Systems . . . . . . . . 181
5.2.7 On-Line Analytical Processing . . . . . . . . . . . . . . . . . . 183
5.3 Information Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
Contents xv
5.3.1 Internal Data Communication . . . . . . . . . . . . . . . . . . . 186
5.3.2 Data Transfer Between Enterprises . . . . . . . . . . . . . . . 187
5.3.3 Information Exchange in Different Types of
Cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
5.3.4 Information Exchange Automation . . . . . . . . . . . . . . . 191
5.3.5 Use of Cloud Environment . . . . . . . . . . . . . . . . . . . . . 194
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
6 Demand Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
6.1 Demand Modelling Based on Time Series Analysis . . . . . . . . . 199
6.2 Main Methods of Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . 201
6.2.1 Moving Average Method . . . . . . . . . . . . . . . . . . . . . . 201
6.2.2 Exponentially Smoothing Forecasting . . . . . . . . . . . . . 203
6.2.3 Trend Adjusted Exponential Smoothing . . . . . . . . . . . 204
6.2.4 Trend and Seasonality Adjusted Exponential
Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
6.3 Demand Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
6.4 Aggregated Demand Forecasting . . . . . . . . . . . . . . . . . . . . . . . 210
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
7 Examples of Advanced Planning Models . . . . . . . . . . . . . . . . . . . . . 215
7.1 Joint Operation Model of APS System and ERP System
from SAP R/3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
7.1.1 Main Business Process Attributes in Various
Industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216
7.1.2 Software Modules for Planning Solutions . . . . . . . . . . 218
7.1.3 Planning Modules Interaction . . . . . . . . . . . . . . . . . . . 219
7.2 Reference Model of Production Planning for Instrument
Engineering Plant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221
7.2.1 Initial Planning Status Analysis . . . . . . . . . . . . . . . . . 221
7.2.2 Decision Support Database . . . . . . . . . . . . . . . . . . . . . 223
7.3 Mathematical Model in Chemical Industry . . . . . . . . . . . . . . . . 226
7.3.1 Analytical Structure of Model . . . . . . . . . . . . . . . . . . . 226
7.3.2 Objective Function and Constraints . . . . . . . . . . . . . . . 229
7.3.3 Some Results of Modelling . . . . . . . . . . . . . . . . . . . . . 233
7.4 Rapid Supply Chain Reference Model in Clothing Industry . . . . 234
7.5 Schedule Model for a Machine Shop . . . . . . . . . . . . . . . . . . . . 237
7.5.1 Schedule Model with Specified Processing Stages . . . . 238
7.5.2 Optimality Criteria and Constraints . . . . . . . . . . . . . . . 239
7.6 Multi-stage Logistics Chain Model . . . . . . . . . . . . . . . . . . . . . 241
7.6.1 Some Notions in Logistics Chain Modelling . . . . . . . . 241
7.6.2 Dynamic Logistics Chain Optimization Model
in Multi-stage Production . . . . . . . . . . . . . . . . . . . . . . 241
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
xvi Contents
Part II Planning Processes
8 Single-Echelon Inventory Planning . . . . . . . . . . . . . . . . . . . . . . . . . 247
8.1 Inventory Types and Parameters . . . . . . . . . . . . . . . . . . . . . . . 247
8.2 Inventory Management Models . . . . . . . . . . . . . . . . . . . . . . . . 248
8.2.1 Model with Fixed Quantity of Order . . . . . . . . . . . . . . 249
8.2.2 Model with Fixed Reorder Cycle . . . . . . . . . . . . . . . . 250
8.2.3 Two-Tier Inventory Management Model . . . . . . . . . . . 251
8.2.4 Benchmarking of Inventory Management Models . . . . 253
8.2.5 Kanban Inventory Management Model . . . . . . . . . . . . 254
8.3 Inventory Management Model Under Uncertainty . . . . . . . . . . 256
8.3.1 Customer Service Level . . . . . . . . . . . . . . . . . . . . . . . 256
8.3.2 Shortages Permitted Inventory Management Model . . . 257
8.3.3 Demand Distribution Functions . . . . . . . . . . . . . . . . . 258
8.3.4 Newsvendor Problem . . . . . . . . . . . . . . . . . . . . . . . . . 260
8.4 Inventory Management Using Logistic Operating Curves . . . . . 262
8.4.1 Storage Curves and Their Applications . . . . . . . . . . . . 262
8.4.2 Finished Product Inventory Sizing to Optimize the
Overall Production Performance . . . . . . . . . . . . . . . . . 264
8.5 Safety Stock Sizing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
8.5.1 Calculation of Safety Stock with Random Demand . . . 266
8.5.2 Sizing of Safety Stock with Two Random Variables . . . 267
8.5.3 Sizing of Safety Stock with Three Random Variables . . . 269
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270
9 Supply Chain Inventory Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . 273
9.1 Stock Distribution Planning in the Chain . . . . . . . . . . . . . . . . . 273
9.1.1 DRP Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
9.1.2 Regular Maintenance of DRP Tables . . . . . . . . . . . . . . 276
9.1.3 Parallel Multi-product Planning . . . . . . . . . . . . . . . . . 278
9.1.4 Inventory Dynamics at Long Lead Cycles . . . . . . . . . . 279
9.2 Supply Chain Fluctuations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
9.2.1 Bullwhip Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
9.2.2 Bullwhip Effect Factors . . . . . . . . . . . . . . . . . . . . . . . 284
9.2.3 Methods of Reducing Supply Chain Fluctuations . . . . . 286
9.3 Application of Logistics Operating Curves in Supply Chains . . . 289
9.4 Inventory Echelon Accounting . . . . . . . . . . . . . . . . . . . . . . . . 292
9.4.1 Inventory Echeloning . . . . . . . . . . . . . . . . . . . . . . . . . 292
9.4.2 Sequential Supply Chain . . . . . . . . . . . . . . . . . . . . . . 293
9.4.3 Supply Chain with Distribution . . . . . . . . . . . . . . . . . . 297
9.4.4 Dependency Between Echelon Stock and Number
of Links of One Level in the Supply Chain . . . . . . . . . 299
9.5 Inventory Planning in Spare Parts Supply Chains . . . . . . . . . . . 300
9.5.1 METRIC Method in Spare Parts Supplies . . . . . . . . . . 301
Contents xvii
9.5.2 Inventory Planning for Central Spare Parts Storage Using
(R,Q) Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
9.6 Coordinated Planning Between Two Supply Chain
Members . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
10 Planning of Supplies to Consumers . . . . . . . . . . . . . . . . . . . . . . . . . 313
10.1 Sales and Operation Planning . . . . . . . . . . . . . . . . . . . . . . . . . 313
10.1.1 Interrelation Between Various Planning Directions with
Sales and Operations Plan . . . . . . . . . . . . . . . . . . . . . 313
10.1.2 Sales and Operation Planning Methods . . . . . . . . . . . . 315
10.2 Sales and Operation Plan Optimization Using Linear
Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318
10.2.1 Single Aggregated Product Group Optimization . . . . . . 319
10.2.2 More Complex Case of Optimization of Sales and
Operations Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322
10.3 Customized Reservation of Products . . . . . . . . . . . . . . . . . . . . 326
10.3.1 Business Process of Response to New Orders . . . . . . . 326
10.3.2 Arrangement of Orders . . . . . . . . . . . . . . . . . . . . . . . . 327
10.3.3 Running ATP Process . . . . . . . . . . . . . . . . . . . . . . . . 329
10.4 Agreement of Order Specifications with Customers . . . . . . . . . 331
10.4.1 Problem Criteria and Their Evaluation . . . . . . . . . . . . 331
10.4.2 Selection of Ordered Product Analogues . . . . . . . . . . . 332
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338
11 Lot Sizing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339
11.1 Classification of Lot-Sizing Problems . . . . . . . . . . . . . . . . . . . 339
11.1.1 Lot Properties and Main Problems . . . . . . . . . . . . . . . 339
11.1.2 Lot-Sizing Problems with No Capacity Limits . . . . . . . 341
11.1.3 Lot-Sizing Problems with Limited Capacities and Large
Planning Periods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342
11.1.4 Lot-Sizing Problems with Limited Capacities and Small
Planning Periods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
11.2 Constant Demand Lot-Sizing Problems . . . . . . . . . . . . . . . . . . 344
11.2.1 Models with Gradual Inventory Replenishment . . . . . . 345
11.2.2 Model Applicable to the Machinery Industry If No Cost
Information Is Available . . . . . . . . . . . . . . . . . . . . . . . 347
11.2.3 Three-Parameter Models for Machinery Industry . . . . . 349
11.2.4 Lot Sizing at Discounted Prices . . . . . . . . . . . . . . . . . 351
11.3 Lot Sizing at Variable Demand and Limited Planning
Horizon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
11.3.1 Exact Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
11.3.2 Heuristic Silver–Meal Algorithm . . . . . . . . . . . . . . . . 356
11.3.3 Part Period Balancing . . . . . . . . . . . . . . . . . . . . . . . . . 359
11.3.4 Groff’s Heuristic Rule . . . . . . . . . . . . . . . . . . . . . . . . 360
xviii Contents
11.3.5 Period Order Quantity . . . . . . . . . . . . . . . . . . . . . . . . 362
11.4 Lot Sizing with Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . 363
11.5 Multi-product Deliveries and Orders . . . . . . . . . . . . . . . . . . . . 366
11.5.1 Optimal Multi-product Lot Sizing . . . . . . . . . . . . . . . . 366
11.5.2 Multi-product Deliveries over Multiple Periods . . . . . . 368
11.5.3 Power-of-Two Policies for Multi-product
Deliveries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 370
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
12 Production Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
12.1 Master Production Planning . . . . . . . . . . . . . . . . . . . . . . . . . . 373
12.1.1 Master Planning as Product Tables . . . . . . . . . . . . . . . 374
12.1.2 Group Master Planning . . . . . . . . . . . . . . . . . . . . . . . 379
12.1.3 Master Production Plan Optimization . . . . . . . . . . . . . 381
12.2 Material Requirement Planning . . . . . . . . . . . . . . . . . . . . . . . . 383
12.2.1 Production Lot Duration . . . . . . . . . . . . . . . . . . . . . . . 384
12.2.2 Optimal Production Lot Sizing . . . . . . . . . . . . . . . . . . 386
12.2.3 Analysis of the Material Requirement Plan . . . . . . . . . 390
12.3 Project-Based Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391
12.3.1 Critical Path Method . . . . . . . . . . . . . . . . . . . . . . . . . 391
12.3.2 Cost Optimization at Various Project Stages . . . . . . . . 394
12.4 Stability of Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398
12.4.1 Quantitative Evaluation of Planning Stability . . . . . . . 399
12.4.2 Methods of Planning Stability Improvement . . . . . . . . 401
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404
13 Shop Floor Scheduling: Single-Stage Problems . . . . . . . . . . . . . . . . 405
13.1 Single-Machine Scheduling with Minimized Overdue
Penalties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405
13.1.1 Schedule with the Minimum of Delayed Jobs . . . . . . . 406
13.1.2 Scheduling with Minimum Weighted Tardiness
per Each Job . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406
13.1.3 Schedule Optimization with Earliness/Tardiness . . . . . 409
13.2 Common Shipment Date Scheduling . . . . . . . . . . . . . . . . . . . . 410
13.2.1 Fixed Date Schedule Optimization . . . . . . . . . . . . . . . 410
13.2.2 More Complex Cases of Scheduling with Fixed Date . . . 412
13.2.3 Selection of Optimal Midpoint Date for Shipping . . . . 413
13.3 Some Other Scheduling Problems for Jobs with Fixed
Processing Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
13.3.1 Schedules for the Case of Several Jobs, the Part of
Which Has the Preset Sequence . . . . . . . . . . . . . . . . . 415
13.3.2 Scheduling of Jobs with Different Arrival Time . . . . . . 417
13.3.3 Scheduling of Jobs with Different Arrival Time and
Different Shipment Time . . . . . . . . . . . . . . . . . . . . . . 418
13.3.4 Job Sequence-Based Setup Time Scheduling . . . . . . . . 419
Contents xix
13.4 Periodic Scheduling with Lots of Economic Sizes . . . . . . . . . . 421
13.4.1 Equal-Time Schedules for All Products . . . . . . . . . . . . 421
13.4.2 Variable-Time Schedules for Different Products . . . . . 423
13.5 Group Technology in Schedules for a Single Machine . . . . . . . 426
13.5.1 Group Scheduling for Series Batches . . . . . . . . . . . . . 427
13.5.2 Group Scheduling for Parallel Batches with Minimum
Tardiness Criterion . . . . . . . . . . . . . . . . . . . . . . . . . . 430
13.5.3 Group Scheduling for Parallel Batches with Maximum
Average Utility Criterion . . . . . . . . . . . . . . . . . . . . . . 432
13.6 Parallel Machine Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . 440
13.6.1 Identical Parallel Machine Scheduling . . . . . . . . . . . . . 440
13.6.2 Schedules for Parallel Unrelated Machines . . . . . . . . . 442
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445
14 Shop Floor Scheduling: Multi-stage Problems . . . . . . . . . . . . . . . . 447
14.1 Synchronized Flowshop Production . . . . . . . . . . . . . . . . . . . . . 447
14.1.1 Discrete Product Lines . . . . . . . . . . . . . . . . . . . . . . . . 448
14.1.2 Lines for Process Production . . . . . . . . . . . . . . . . . . . 449
14.1.3 Flexible Flow Lines . . . . . . . . . . . . . . . . . . . . . . . . . . 450
14.2 Automated Assembly Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . 452
14.2.1 Scheduling for Unpaced Assembly Lines . . . . . . . . . . 453
14.2.2 Scheduling for Paced Assembly Line . . . . . . . . . . . . . 456
14.2.3 Scheduling for Mixed Assembly Lines . . . . . . . . . . . . 460
14.3 Unsynchronized Flowshop Production . . . . . . . . . . . . . . . . . . . 462
14.3.1 Modelling for Unsynchronized (Discontinuous)
Flow Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463
14.3.2 Optimization for Two-Machine Group Flow Lines . . . . 466
14.3.3 Campbell, Dudek, and Smith Algorithm . . . . . . . . . . . 468
14.3.4 Nawaz, Enscore, Ham Algorithm . . . . . . . . . . . . . . . . 469
14.4 Job-Shop Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 470
14.4.1 Shifting Bottleneck Algorithm . . . . . . . . . . . . . . . . . . 471
14.4.2 Job-Shop Production Scheduling Using Dynamic List
Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483
15 Multi-criteria Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485
15.1 Just-in-Time Production Scheduling . . . . . . . . . . . . . . . . . . . . . 485
15.1.1 Starting Group of Jobs with Fixed Sequence . . . . . . . . 485
15.1.2 Scheduling for Identical Parallel Machines with
Common Shipment Date . . . . . . . . . . . . . . . . . . . . . . 489
15.2 Multi-objective Algorithms for Some Simple Production
Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490
15.2.1 Scheduling for Two-Machine Flowshop Production . . . 490
15.2.2 Schedule for Parallel Uniform Machines . . . . . . . . . . . 493
15.2.3 Some Other Problems and Solving Challenges . . . . . . . 499
xx Contents
15.3 Scheduling Based on Cost and Average Orders Utility . . . . . . . 501
15.3.1 Sequenced Job Scheduling with Sequence-Dependent
Setups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502
15.3.2 Group Scheduling for Parallel Batches Based on
Maximum Average Utility and Minimum
Setup Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511
15.4 Application of Decision Theory Methods . . . . . . . . . . . . . . . . . 515
15.4.1 Application of Savage Principle for
Decision-Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516
15.4.2 Application of Hurwitz Principle for
Decision-Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . 518
15.5 Decision-Support Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519
15.5.1 Decision-Support System for Hybrid Flow Lines . . . . . 519
15.5.2 Some Other Decision-Support Systems . . . . . . . . . . . . 521
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523
Appendix A: Symbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525
Appendix B: Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527
Appendix C: Classification Parameters of Schedules . . . . . . . . . . . . . . . 529
C.1 Parameters in Field α . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529
C.2 Parameters in Field β . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530
C.3 Parameters in Field γ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530
Appendix D: Production Intensity Integral Calculations . . . . . . . . . . . . 533
Appendix E: Scheduling Software Based on Order Utility Functions . . . 537
E.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537
E.2 Description of Work with File1.xls . . . . . . . . . . . . . . . . . . . . . . . . 537
E.3 Description of Work with File2.xls . . . . . . . . . . . . . . . . . . . . . . . . 543
E.4 Description of Work with File3.xls . . . . . . . . . . . . . . . . . . . . . . . . 545
E.5 Description of Work with File4.xls . . . . . . . . . . . . . . . . . . . . . . . . 548
E.6 Description of Work with File5.xls . . . . . . . . . . . . . . . . . . . . . . . . 550
E.7 Description of Work with File6.xls . . . . . . . . . . . . . . . . . . . . . . . . 553
E.8 Description of Work with File7.xls . . . . . . . . . . . . . . . . . . . . . . . . 556
E.9 Description of Work with File8.xls . . . . . . . . . . . . . . . . . . . . . . . . 557
Appendix F: Using Clobbi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561
F.1 General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561
F.2 Description of Planning Possibilities in the System . . . . . . . . . . . . . 563
F.3 Description of Service Operation . . . . . . . . . . . . . . . . . . . . . . . . . . 564
F.4 Clobbi Service Advantages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 566
F.5 Online Registration of Manufacturing Events . . . . . . . . . . . . . . . . . 568
F.6 Clobbi Commercial Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569
Contents xxi
ThiS is a FM Blank Page
About the Author
Yuri Mauergauz is an Assistant Professor and a consultant of Sophus Group,
Moscow, Russia. He gained his PhD from the St. Petersburg Navy Institute in
1970. He has worked at machine-building plants and research institutes and also
taught at the Urals and Odessa technical universities. He has published around
80 research papers and 3 books dedicated to the application of computer engineering
in production planning.
xxiii
Recommended