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- Herausgeber: Wiley-VCH GmbH
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- Sprache: Englisch
Practice-oriented coverage of production planning and control processes for goods and services, written for any industry
Production Control in Practice explores the operational control of production and inventory processes in organizations across industries, covering both tangible and intangible products and offering viable, efficient solutions to characteristic production control problems, such as what goods to produce when and how. A number of examples/stylized applications are included to help readers understand and apply the discussed concepts and theories to their own organizations.
This book distinguishes between the control of production units and the control of goods flow between these units and the market and discusses various coordination and material supply control mechanisms relevant to supply chains. It also presents a typology of production situations found in practice, using a structured approach to discussing the relevant control decisions for each situation.
This book is unique because (basic) control decisions are discussed for the different characteristic Decoupling Point Control and Production Unit Control situations from a holistic point of view, taking into account both mathematical considerations as well as various situational factors.
Sample topics covered in Production Control in Practice include:
- Terminology and concepts used in production control, including complexity, uncertainty, and flexibility
- Types of release triggers, covering just-in-time versus just-in-case and push versus pull in logistics
- Horizontal and vertical decomposition, and time series-related forecasting for stationary demand versus demand with trend
- Order size, covering optimal batch size in case of fixed order size, relaxation of assumptions, and single period considerations
- MRP systems, covering Material Requirements Planning (MRP-I) and Manufacturing Resource Planning Systems (MRP-II)
With excellent coverage of the subject across different products and industries and several examples to help readers follow along, Production Control in Practice is an ideal reference for bachelor students from universities of applied sciences and academic bachelor students, as well as practitioners in related disciplines.
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Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
Preface
Part I: Production Control in General
1 Production Control – A Logistic Control Function
1.1 Logistics
1.2 Logistics Planning and Control
1.3 Logistic Concepts in Production
1.4 Terminology for Production Control
References
2 Horizontal and Vertical Decomposition
2.1 Horizontal Decomposition
2.2 Vertical Decomposition
2.3 Types of Release Triggers
2.4 An Example of Decomposition
References
3 Planning and Control in Production Units
3.1 Production Control in General
3.2 Basic Forms of Production
References
4 Framework for Logistic Planning and Control in Production Systems
4.1 General Framework
4.2 Position of this Book
References
Part II: Planning and Control of Decoupling Points
5 Decoupling Point Control
5.1 Decoupling Point Control – An Introduction
5.2 Performance Measures for Decoupling Point Control
5.3 Demand and Forecasting
5.4 Order Size
Appendix 5.A The Wagner-Whitin Algorithm
Appendix 5.B Example Impact Advanced and Optimal Approach for Determining Batch Sizes
Appendix 5.C Newsvendor Problem
References
Notes
6 Reorder Point Decoupling Point Control Systems
6.1 General Discussion of Reorder Point Systems
6.2 When to Order?
6.3 How Much to Order?
Appendix 6.A Table of the One‐Sided Standard Normal Distribution
Appendix 6.B Table Standard Normal Loss Function
Appendix 6.C Reorder Level Determination in Case of a General Distribution
References
Notes
7 MRP Decoupling Point Control Systems
7.1 General Discussion of MRP Systems
7.2 When to Order
7.3 How Much to Order?
7.4 Discussion on MRP‐Related Issues
Appendix 7.A MRP formulas
References
8 Systems Using Echelon Stock (ESC, LRP)
8.1 General Discussion of Systems Using Global Norms
8.2 When and How Much to Order?
8.3 Discussion on Echelon Stock Systems
References
Note
9 Choosing an Appropriate DPC System
9.1 General Considerations
9.2 Advantages/Disadvantages of the Different DPC Systems
9.3 Which Decoupling Point Control System to Use?
References
Notes
Part III: Production Unit Control
10 General Discussion of Production Control Decisions
10.1 Priority Control
10.2 Capacity Allocation
10.3 Work Order Release/Work Order Detail Planning (Scheduling)
References
11 Production Control for Deterministic, Static Production Situations (Scheduling)
11.1 Sequencing Orders Without Delivery Date (Throughput Time Oriented)
11.2 Sequencing Orders with a Delivery Date (Reliability Oriented)
11.3 Relaxing Assumptions
References
12 Flow Process Production
12.1 General Description
12.2 Main Control Attention Points of Flow Process Production
12.3 Production Control Decisions for Flow Process Production in MTS Situations
12.4 Production Control Decisions for Flow Process Production in MTO Situations
12.5 Application
References
13 Mass Assembly Production
13.1 General Description
13.2 Main Control Attention Points of Mass Assembly Production
13.3 Production Control Decisions for Mass Assembly Production
13.4 Application
References
Note
14 Small Series Production
14.1 General Description
14.2 Main Control Attention Points of Small Series Production
14.3 Production Control Decisions for Small Series Production
14.4 Application
Appendix 14.A Short‐Term Capacity Adjustment
Appendix 14.B Flexible Batching
Appendix 14.C The Effect of Workload Control in Case There Is a Relationship Between Productivity and Workload
References
Notes
15 (Repetitive) Project‐Based Production
15.1 General Description
15.2 Main Control Attention Points of Project‐Based Production
15.3 Production Control Decisions for Project‐Based Production
15.4 Application
References
Index
End User License Agreement
List of Tables
Chapter 5
Table 5.1 Example difference P1 and P2.
Table 5.2 Input of the example.
Table 5.3 Results of using the Silver‐Meal heuristic for the example with th...
Table 5.4 Example situation with a maximum batch
Q
(propD is the proportion ...
Table 5.5 Example newsvendor problem.
Table 5.A.1 Input data for the example.
Table 5.A.2 Replenishment costs for the different strategies.
Chapter 6
Table 6.B
L
(
Z
) is the standard loss function, i.e. the expected number of lo...
Chapter 11
Table 11.1 The processing time of six jobs at workstations A and B.
Table 11.2 The completion time of each of the six orders at each workstation...
Table 11.3 The processing times of five orders at each of the workstations A...
Table 11.4 Processing times of the jobs at machine A and machine C.
Table 11.5 The completion time of the original problem given sequence (2, 4,...
Table 11.6 The aggregate processing times of the jobs at “machine” A + B and...
Table 11.7 The completion time of the original problem given sequence (4, 1,...
Table 11.8 The preparation time for each of the six orders that are waiting ...
Table 11.9 The planned start times for loading for each of the six orders th...
Table 11.10 Determination of the first order that is delivered too late with...
Table 11.11 Determination of the first order that is delivered too late with...
Table 11.12 Determination of the first order that is delivered too late with...
Table 11.13 Example of routings and processing times for a certain job shop....
Chapter 12
Table 12.1 Differences between two kinds of process‐wise production.
Table 12.2 Demand information.
Table 12.3 Set up times for the different types of cans (in minutes).
Table 12.4 Production speed per type of can (in cans per minute).
Table 12.5 Demand per item (vegetable/can) (cans per week).
Chapter 13
Table 13.1 The different tasks for working up a loan application, their aver...
Table 13.2 Number of machines and processing times per bag (in seconds) for ...
Table 13.3 Characteristics of the breakdowns at line 1 (times given in hours...
Chapter 14
Table 14.1 Transition matrix.
Table 14.2 The effect of due date determination rules on the delivery perfor...
Table 14.3 The effect of different priority rules in case orders consists of...
Table 14.4 The effect of priority rules on delivery reliability in case a co...
Table 14.5 The effect of priority rules on delivery reliability for the diff...
Table 14.6 The transition matrix for the routings of the products in the non...
Table 14.7 The average processing times (in minutes per product) for each of...
Chapter 15
Table 15.1 Example action plan.
Table 15.2 Optimistic, most likely, and pessimistic estimates for the durati...
Table 15.3 The expectation and standard deviation of the activity processing...
Table 15.4 The ESTs, LSTs, and slacks for the activities, and the EOTs, LOTs...
Table 15.5 Project action plan for project 1.
Table 15.6 Project action plan for project 2.
List of Illustrations
Chapter 1
Figure 1.1 Logistics.
Figure 1.2 Examples of transformation processes.
Figure 1.3 Control cycle.
Figure 1.4 Basic decision elements of logistic planning and control.
Figure 1.5 MO/PCOI‐view on production systems.
Figure 1.6 Logistic concept.
Figure 1.7 A schematic example of a production process.
Chapter 2
Figure 2.1 Three logistic sub‐functions.
Figure 2.2 Release and sequencing decisions in a process.
Figure 2.3 Example of a production order.
Figure 2.4 Decoupling points.
Figure 2.5 Customer order decoupling point.
Figure 2.6 Decoupling point control versus unit control.
Figure 2.7 Three basic release decisions.
Figure 2.8 Controlled stock versus buffer.
Figure 2.9 On order versus on stock.
Figure 2.10 “Just‐in‐Time.”
Figure 2.11 Throughput time distribution.
Figure 2.12 Throughput time distribution and (planned) lead time.
Figure 2.13 “On Order” situation in real‐life situations.
Figure 2.14 Push versus pull versus plan‐based.
Figure 2.15 Logistic structure of the sunroof example.
Figure 2.16 Detailed logistic structure of the sunroof example.
Chapter 3
Figure 3.1 Example Bill of Materials.
Figure 3.2 High capacity complexity.
Figure 3.3 Basic forms of production.
Figure 3.4 Batch operation time.
Chapter 4
Figure 4.1 Vertical decomposition extended for operator capacity.
Figure 4.2 MRP II framework.
Figure 4.3 BWW framework for logistic planning and control of production....
Chapter 5
Figure 5.1 “On Order” versus “On Stock.”
Figure 5.2 When and how much to order.
Figure 5.3 Four basic methods of reordering.
Figure 5.4 Example of customer service levels in an “on‐stock” situation.
Figure 5.5 Four components of demand.
Figure 5.6 Example average and standard deviation forecast error in case of ...
Figure 5.7 Single linear regression.
Figure 5.8 Example demand pattern stationary demand.
Figure 5.9 Example moving average.
Figure 5.10 Weighted moving average.
Figure 5.11 Exponential smoothing.
Figure 5.12 Quality measures for moving average with
n
= 4.
Figure 5.13 Likely distribution of non‐systematic forecasting errors: Normal...
Figure 5.14 Demand pattern in case of a trend.
Figure 5.15 Forecasting error when using moving average in case of demand wi...
Figure 5.16 Actual demand versus forecast based on moving average with
n
= 6...
Figure 5.17 Range of correlation coefficient (shows strength and direction o...
Figure 5.18 Correlation coefficient for several examples.
Figure 5.19 Example showing linear regression as a forecast for demand with ...
Figure 5.20 Base level
a
(
t
) and step
b
(
t
) are to be forecasted using exponen...
Figure 5.21 Example using double exponential.
Figure 5.22 Stock pattern in case of fixed
Q
and regular
D
.
Figure 5.23 Cost curves for
D
(yr) = 1000,
C
ord
= €30, and
C
hold
= €100.
Figure 5.24 Inventory levels for child item if
Q
c
=
n
·
Q
p
.
Figure 5.B.1 Example impact advanced and optimal approach for
Q
c
and
Q
p
.
Figure 5.B.2 BOM for the example.
Chapter 6
Figure 6.1 Basic “on stock” situation.
Figure 6.2 Basic situation when reordering.
Figure 6.3 Physical stock, available stock, and inventory position.
Figure 6.4 Classification of inventory control systems.
Figure 6.5 Basic logic (
s
,
Q
) system.
Figure 6.6 Stock in time for a (
s
,
Q
) system.
Figure 6.7 Example of a two‐bin system.
Figure 6.8 Example Kanban card.
Figure 6.9 Basic logic of the (
R
,
s
,
Q
) system.
Figure 6.10 Available stock in time for (
s
,
Q
) system for normal distributed...
Figure 6.11 Example distribution of demand during lead time.
Figure 6.12 P1 and P2 for the example.
Figure 6.13 Dependency of P2 on
Q
in the example.
Figure 6.14 Dependency of the number of stockouts on P1 and
Q
in the example...
Figure 6.15 (
R
,
s
,
Q
) system when inventory drops below
s
just after the rev...
Figure 6.16 Example with lumpy demand and undershoot.
Figure 6.17 Basic logic of the (
s
,
S
) system.
Chapter 7
Figure 7.1 Bill of materials.
Figure 7.2 Logic MRP‐I using time‐offsetting and BOM‐relation.
Figure 7.3 MRP‐II framework.
Figure 7.4 BOM for product FP.
Figure 7.5 Production process for product FP.
Figure 7.6 Basic MRP calculation for product FP (abbreviations: see Appendix...
Figure 7.7 MRP schedule adjusted for inventory and scheduled receipts (abbre...
Figure 7.8 MRP schedule adjusted for batch sizing rules (abbreviations: see ...
Figure 7.9 MRP schedule one period later (abbreviations: see Appendix 7.A)....
Figure 7.10 Important exception messages.
Figure 7.11 Distribution network with three tiers.
Figure 7.12 Example of MRP‐I in distribution context (abbreviations: see App...
Chapter 8
Figure 8.1 Three‐stage linear supply chain.
Figure 8.2 Example Echelon stock.
Figure 8.3 Two‐stage linear supply chain.
Figure 8.4 LRP schedule for example of Section 7.3.
Figure 8.5 Example of a two‐stage divergent supply chain.
Chapter 9
Figure 9.1 Categories based on lead time characteristics.
Figure 9.2 Categories based on demand characteristics.
Figure 9.3 Categories based on cost characteristics.
Figure 9.4 ABC‐analysis, based on sales volume.
Figure 9.5 Example of demand pattern for different values of
vc
.
Figure 9.6 ABC–XYZ categories.
Figure 9.7 General guidelines for stock control using ABC–XYZ categories.
Chapter 10
Figure 10.1 The control functions at the operational level that are relevant...
Chapter 11
Figure 11.1 Illustration of the consequences of switching the production seq...
Figure 11.2 Illustration of the consequences of switching the production seq...
Figure 11.3 Illustration of step 3 in the Wilkinson and Irwin procedure
Chapter 12
Figure 12.1 Examples of continuous process‐wise production.
Figure 12.2 Graphical representation of start times and end times of the pro...
Chapter 13
Figure 13.1 Examples of mass assembly or flow production.
Figure 13.2 Takt time, processing time, and throughput time in case processi...
Figure 13.3 Precedence relation diagram for handling loan applications at CR...
Figure 13.4 Flow‐production with buffers.
Figure 13.5 Flow‐production using parallel stations (Throughput time (= 4 × ...
Figure 13.6 Combining several parallel flow production lines.
Figure 13.7 Example of a flow line with two work centers and a buffer with s...
Figure 13.8 Transition diagram.
Figure 13.9 Effect of disturbance on the content of the buffer.
Figure 13.10 Illustration of the effect of failures at the first station.
Figure 13.11 Approximation method for flow lines with more than two stations...
Figure 13.12 A schematic example of a U‐shaped production line.
Chapter 14
Figure 14.1 Some examples of (parts of) small series production situations....
Figure 14.2 Schematic example of a job shop production situation.
Figure 14.3 Probability density function of a negative exponential distribut...
Figure 14.4 Graphical representation of Erlangs formula in case the inter‐ar...
Figure 14.5 A schematic overview of the determination of the lead time.
Figure 14.6 The effect of a capacity check on the standard deviation of the ...
Figure 14.7 The effect of constant and workload‐dependent slack on the stand...
Figure 14.8 The average and standard deviation of the lateness for different...
Figure 14.9 Ratio of the average SPT waiting time and the average FIFO (or F...
Figure 14.10 The average queue length as a function of the number of alterna...
Figure 14.11 The relationship between arousal and performance.
Figure 14.12 A graphical representation of (Operation) Due Date determinatio...
Figure 14.B.1 Average work order throughput time as a function of
Q
min
,
Q
max
Figure 14.C.1 The shape of the relationship between workload and productivit...
Chapter 15
Figure 15.1 Some examples of products from project‐based production situatio...
Figure 15.2 Global goods flow concerning a project.
Figure 15.3 The AON network corresponding to the action plan given in Table ...
Figure 15.4 The AOA network corresponding to the action plan given in Table ...
Figure 15.5 The AOA network in case of activity A precedes activity D, activ...
Figure 15.6 The AOA network corresponding to the action plan given in Table ...
Figure 15.7 The AON network for the example project is given in Table 15.1....
Figure 15.8 Example of translation from project plan to detailed capacity pl...
Figure 15.9 AON representation of the network for project 1; the critical pa...
Figure 15.10 Total project duration for project 1 (10 days); the red lines a...
Figure 15.11 AON representation of the network for project 2; the critical p...
Figure 15.12 Total project duration for project 2 (7 days).
Figure 15.13 The required capacity profile for both projects using an early
Figure 15.14 The schedule that respects both deadlines and minimizes tempora...
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
Begin Reading
Index
End User License Agreement
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Production Control in Practice
A Situation‐Dependent Decisions Approach
Henny Van OoijenCorné Dirne
Authors
Prof. Dr. Henny Van Ooijen
Eindhoven University of Technology
Tielseweg 5
4116 EB Buren
The Netherlands
Prof. Dr. Corné Dirne
Fontys University of Applied Sciences
Rondom 1
5612 AP Eindhoven
The Netherlands
Cover Image: © akinbostanci/Getty Images
All books published by WILEY‐VCH are carefully produced. Nevertheless, authors, editors, and publisher do not warrant the information contained in these books, including this book, to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.
Library of Congress Card No.:
applied for
British Library Cataloguing‐in‐Publication Data
A catalogue record for this book is available from the British Library.
Bibliographic information published by the Deutsche Nationalbibliothek
The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at <http://dnb.d-nb.de>.
© 2024 WILEY‐VCH GmbH, Boschstraße 12, 69469 Weinheim, Germany
All rights reserved (including those of translation into other languages). No part of this book may be reproduced in any form – by photoprinting, microfilm, or any other means – nor transmitted or translated into a machine language without written permission from the publishers. Registered names, trademarks, etc. used in this book, even when not specifically marked as such, are not to be considered unprotected by law.
Print ISBN: 978‐3‐527‐35344‐6
ePDF ISBN: 978‐3‐527‐84590‐3
ePub ISBN: 978‐3‐527‐84589‐7
oBook ISBN: 978‐3‐527‐84588‐0
Preface
In the 1980s–1990s of the past century Bertrand, Wortmann, and Wijngaard published the book “Productiebeheersing en Materials Management” (in Dutch), which was unique in its approach to the discussion of production control (see further on). This book is no longer edited, but from a lot of sources, we heard that the material, and the way it is discussed, are still very interesting and relevant. Therefore, we decided to “upgrade” this book. It is extended, updated, and written in English. Moreover, we tried to make it as practical as possible. Therefore, we will not discuss the latest, most sophisticated research concerning the different decision functions since these are often difficult to understand, or to implement, for practitioners. Moreover, here holds: the first blow is half the battle, that is, with only simple methods already a lot (cost) benefits are obtained. The target audience is students at a bachelor level and practitioners with some experience working in the field of (production) logistics.
In our daily life, we can observe lots of transformation processes. We can group them into:
(a) Transformation of form or content
(b) Transformation of time
(c) Transformation of place
In this book, we will discuss the transformation of the form (production) and the transformation of time (inventory) with an emphasis on operational control. We will concentrate on transformation processes that take place in production organizations or professional service organizations (insurance companies, banks, etc.). In these organizations, we deal with the production of tangible or intangible products and the stocking of raw materials, intermediate components, and products produced. We will mainly use terminology from industry, but the concepts can easily (with some creativity) be translated into professional service organizations.
We decompose the complex production control problem in supply chains into several less complex subcontrol problems. This leads to a decoupling point control (material coordination) problem and one or more production unit control (capacity coordination) problems.
We distinguish several characteristic control situations, and for each of them, we discuss the control aspects where we will use the same format for discussion for all the goods flow and production situations: first a general discussion of the control situation, next a general discussion of the relevant decision functions and then a detailed discussion of each decision function for the control situation we consider. This is one of the unique points of this book. The fact that we distinguish several characteristic situations and discuss for each of them the relevant decisions led to the inclusion of “situation‐dependent” in the subtitle.
The books we know on production control discuss this from a technical point of view (LP, queuing theory, dynamic programming, etc.) or a functional point of view (aggregate planning, materials requirement planning, etc.). The kinds of production systems considered are limited, often only transfer lines (or flow lines) and assembly systems are discussed. This book is different from other books on Production Planning or Production Control in the sense that especially the (basic) control decisions are discussed for the different characteristic Decoupling Point Control and Production Unit Control situations that we distinguish. These control decisions are not discussed, for instance, from a mathematical point of view, but are based on the main decisions that have to be taken in the situation considered. This is another unique point of this book. That is why we added a “decisions approach” in the subtitle.
The book consists of three parts: production control in general, decoupling point control for the flow of goods between units, and production unit control.
In the first part, we will discuss general aspects of production planning. We will discuss the terminology used in this book and the way we look at production control. For the latter, we will discuss our typology of production situations found in practice leading to several characteristic production situations, and we discuss how we decompose the complex production control problem in supply chains.
In the second part, we will discuss the different coordination and material supply control mechanisms that are relevant to supply chains. We first start by discussing some general aspects and then give a typology of the different control mechanisms. Moreover, we discuss the decisions that, in general, have to be taken. Next, each control mechanism is discussed in more detail in a structured way.
In the third and last part, we discuss each of the production situations from our typology and the way production should be controlled. We do this in a structured way taking in Part I distinguished control decisions as a starting point. At the end of each section, we illustrate the way of production control using a (stylized) practical example.
Much of the material on which the book is based is relatively old, but since most of the decision functions are already extensively discussed and/or exactly solved, new research on these functions does not necessarily bring new insights. A few decision functions (like for instance the work order release function) don't have unique “solutions” and are therefore still the subject of research. Where relevant, we extended the discussion of control decisions with newly developed material. Again, the main contribution of this book is the structured way in which the different production control decisions in the different characteristic situations are discussed.
The book is meant for a broad range of readers: bachelor students from universities of applied sciences, academic bachelor students, and practitioners. Parts of the book discuss in more detail the determination of results or technicalities of methods; these have a blue background and are especially meant for academic bachelor students.
We are grateful to Will Bertrand, Hans Wortmann, and Jacob Wijngaard for paving the road for us with their book, for the lessons we learned from them during the time we were colleagues, and for their permission to use (part of) their material.
Henny Van Ooijen
Buren, The Netherlands
Corné Dirne
Eindhoven, The Netherlands
Part IProduction Control in General
In this part, we will discuss the subject of this book and we will give some basic concepts and terminology. Production Control can be discussed from a different number of viewpoints: quality, economics, technology, logistics, etc. In this book, we will take the viewpoint of logistics. We start in Chapter 1 with a discussion of the logistic aspects of planning and control, both in the general sense and in the context of production. In Chapter 2, the complicated control problem will be decomposed in two ways: a vertical decomposition and a horizontal decomposition, leading to several (hierarchical) control problems that are much easier to handle. Moreover, in this section, we will also discuss the different release triggers. Next, in Chapter 3, we discuss planning and control aspects in Production Units, and subsequently, in Chapter 4, a general framework for (logistic) planning and control in productions and the position this book (using this framework) will be highlighted.
Content
1. Production Control – A Logistic Control Function
1.1 Logistics
1.2 Logistics Planning and Control
1.3 Logistic Concepts in Production
1.4 Terminology for Production Control
1.4.1 Concepts Used in Production Control
1.4.2 Complexity, Uncertainty, and flexibility
References
2. Horizontal and Vertical decomposition
2.1 Horizontal Decomposition
2.2 Vertical Decomposition
2.3 Types of Release Triggers
2.3.1 Just‐in‐Time Versus Just‐in‐Case
2.3.2 Push Versus Pull in Logistics
2.4 An Example of Decomposition
References
3. Planning and Control in Production Units
3.1 Production Control in General
3.2 Basic Forms of Production
3.2.1 Process‐Wise Production
3.2.2 Mass Assembly/Flow Production
3.2.3 (Repetitive) Small Series Production (Also Called Job‐Shop)
3.2.4 (Repetitive) Project‐Wise Production
3.2.5 Throughput Time Production Units
References
4. Framework for Logistic Planning and Control in Production Systems
4.1 General Framework
4.2 Position of this Book
References
1Production Control – A Logistic Control Function
According to an earlier definition of American Production and Inventory Control Society (APICS), production control is defined as:
[....] the task of predicting, planning and scheduling work, taking into account manpower, materials availability and other capacity restrictions, and cost to achieve proper quality and quantity at the time it is needed, and then following up the schedule to see that the plan is carried out, using whatever systems have proven satisfactory for the purpose.
(MacKay and Wiers ([2004]))
As such, production control can be regarded as a logistic planning and control (LPC) function within a production environment. Therefore, we will first discuss logistics in the general sense in Section 1.1. Next, in Section 1.2, we will concentrate on basic decision elements in planning and control for logistics. Then in Section 1.3, we will discuss some specific characteristics of LPC in production, followed in Section 1.4 by an introduction of basic terminology.
1.1 Logistics
The term “Logistics” originates from the logistics on the battlefields, i.e. those activities that take care of the supply and removal of troops, equipment, and materials to and from the battlefields (see, for instance, https://www.merriam‐webster.com/dictionary/logistics). The basic function of logistics is to make sure that the transformation process can perform its function effectively and efficiently by providing that process with the proper information, materials, and resources (“capacity”). In Figure 1.1, the material flow is shown as a double‐lined arrow, going from left (input of materials) to right (output of finished products); information is shown as a single line, whereas for resources triple‐lined arrows are used.
Figure 1.1 Logistics.
The idea of “logistics” may be applied to any type of transformation process. The transformation process can be a production process, turning the incoming materials (“raw materials”) into outgoing products, using machines controlled by operators (capacity resources) and specifications (“information”) determined by engineering. However, a transformation process can also be a maintenance process where a machine that went down (incoming material) is repaired, possibly using spare parts (also incoming materials). The repair can be done by a mechanic using tools and possibly other machines (capacity resources), based on maintenance instructions (=information).
The output of a transformation process doesn't have to be tangible. Also, in professional service organizations like banks or insurance companies transformation processes take place: in general not regarding the transformation of form, but the transformation of information which leads to intangible output. Within a production context, an engineering process is an example of a transformation process with intangible output. The incoming “material” would be information (so nonphysical). That information is turned into product and process specifications by engineers (capacity resources). Supporting information will be used, such as standard solutions or background information stored in databases. In hospitals, patients are the incoming “materials.” Doctors, nurses, operating theaters, beds, and labs are the capacity resources used to turn sick patients into outgoing ex‐patients (hopefully cured …). Finally, transportation processes can be regarded as transformation processes, the transformation being the change of location of the goods transported. Then clearly the goods to transport are the materials, using transportation documents while trucks, drivers, trains, etc. are the capacity resources.
Examples of transformation processes are given in Figure 1.2.
Figure 1.2 Examples of transformation processes.
Source: https://depositphotos.com/.
The logistic function aims to make sure that:
the objects on which the transformation is performed, are available (objects such as materials, assets to be maintained, and patients);
the resources required to perform the transformation are available (capacity resources such as machines, tools, operators, and transportation resources);
the supporting information is available (like instructions for the transformation).
Objects, information, and resources often are physical by nature, but that's not necessarily true for all of them (cf. the example of engineering). For instance, software can be regarded as a resource required for a particular transformation, or particular documents may be available digitally before a process may start. It's not only the availability of objects, information, and resources that matter but also the removal of these items after the transformation has taken place. Making sure the output of the process (the “products”) is made available for the next step is an important issue in logistics. Moreover, also getting the resources back in time and having them available for other processes is an important logistical task, either because these resources may not yet be at the place of the next process they will be used for, or because the resource cannot be used directly for a new process and will be unavailable during a certain period (e.g. because the resource needs “re‐conditioning”). Sometimes even the carrier of information has to be returned to be available next time.
It will be clear that logistics is a very broad term. In many instances, publications, etc., it is often interpreted in relation to warehousing and/or transportation. In this book, we will concentrate on transformation processes that take place in production organizations (transformation of form), and thus logistics has to be interpreted with regard to physical production processes. Therefore, we will mainly use terminology from industry in this book.
1.2 Logistics Planning and Control
Logistic planning and control is all about making decisions on the availability and the supply of the materials, information, and capacity resources at which place and in what quantity to get the transformation process going. The two parts of logistics planning and control are:
Planning
: determining which jobs (“orders”) should be done and setting targets on when and who should be doing what, etc.
Control
: starting the actual jobs, monitoring their progress, and if necessary intervening. This is also known as the
control cycle
(see
Figure 1.3
).
Figure 1.3 Control cycle.
We will see later that usually more than one plan is made. These plans may all differ in time horizon (e.g. a plan for the next shift versus a plan for next year), system boundaries (one workplace versus an entire factory), and units used (“truck ZF20/13 with options X, U, and Z, planned to be produced on time 10:15” versus “120 trucks on day 15”).
If we look in more detail at LPC, we can distinguish the following essential decisions (see Figure 1.4):
Actual
planning
: setting targets for the transformation process considered, like due dates (when should the process be done) and efficiency targets.
Acceptance
of a job offer: a job may not be acceptable from a logistic point of view because the targets set are not possible to meet (like a too‐tight due date), the materials are not (all) available, or the capacity resources required are not available (at least not within the required time frame). Only accepted jobs should be considered for release.
Release
of a job chosen from all the waiting accepted jobs: this requires some kind of prioritizing of the waiting jobs. Together with the release of the job, the materials used, information needed, and the capacity resources required should be released (if that is not done yet). Jobs that have been released are called “work in progress” (WIP), and the materials connected to that job are usually stored in a buffer at the workstations.
Progress monitoring
of the released jobs: during the progress of the transformation process, jobs may run behind schedule (or ahead of schedule). Depending on the reaction time available and the measures that might be taken, an intervention might be considered. Such an intervention can be an adjustment of the number of capacity resources available (like hiring extra temporary operators) or a rescheduling of the due dates. Also, a feedback link to the release of new jobs might be considered. It might even be a change in the job specifications, for instance, in the number of products to be produced. Monitoring requires some kind of progress measurement.
Figure 1.4 Basic decision elements of logistic planning and control.
Releasing new jobs, information, materials, and capacity resources (or not) and intervening in the progress of jobs that have already been released (or removing capacity and materials from the process) is the most direct way the logistic function may influence the logistic performance of the transformation process. In other words, LPC combines “jobs,” “materials,” “information,” and “resources” to allow the transformation process to start (and finish).
1.3 Logistic Concepts in Production
Logistic Planning and Control (LPC) in the case of production processes ( production planning and control) is the main subject of this book. Before we explain the position of LPC in a production context, it is worthwhile to describe a production process as an aspect of a production system as In 'Veld has introduced in his System Approach (Veeke et al. [2010]). Any production system can be described in terms of the PCOI aspects (van Assen [2016]; Dijkstra et al. [1997]; Ribbers and Verstegen [1992]):
Process
: the actual activities of the system, including the interrelations between these activities (like material flows) and the resources used to perform the activities.
Control
: the planning and control of the activities of the process, usually in terms of quality, timeliness, and costs.
Organization
: the division of tasks, responsibilities, and competencies in the system among people and functions (“who does what”).
Information
: the provision and gathering of information to, in, and from the system. This information is needed for all three other aspects of the system: to support and monitor the process, to assist in decision‐making and distribute decisions made, and to exchange facts, knowledge, and statuses between people and functions.
Any production system operates in an environment. Crucial parts of the environment of a production system are the consumer markets buying/using the products (“outputs”). These markets are the “reason for being” for the production system. The output is related to the performance the system delivers. The choices made on what to achieve in such a context from a business perspective, translated into targets for the production system, may be considered the goals of the system as defined by van Assen ([2016]). Other markets, then the consumer markets, that the production system has to take into account, especially from a logistic point of view, are the supplier markets providing materials and resources (“inputs”). We will call this view on production systems the MO/PCOI‐view, which is short for “Markets‐Output‐Process‐Control‐Organization‐Information” (see Figure 1.5). Using this model on production systems, LPC can be considered as an aspect system of the “control” part of the production system. It focuses on the planning and control of the timeliness of the process. The logistic performance is usually expressed in terms of having the right amount of the right products at the right place at the right time. It consists of two basic elements:
Delivery reliability
: the degree to which the agreed delivery specifications (in time, place, and quantity) are met.
Delivery time
: the time required to deliver the required items (so: how fast is delivery).
Figure 1.5 MO/PCOI‐view on production systems.
Source: van Assen ([2016]).
Promising a short delivery time is only wise if we're pretty sure that we'll be able to keep this promise and thus meet the due date. Otherwise, it might be better to enlarge the promised delivery time somewhat. So having a short promised delivery time usually only leads to satisfied customers if the promised delivery time is met.
Besides delivery performance, often the following two aspects are considered as well when determining the total logistic performance:
Flexibility of delivery
: the degree to which agreements made (like due dates) can be changed afterward without loss in delivery reliability or extra costs.
Logistic costs
: all costs associated with the supply of materials and capacity resources, such as inventory cost, cost of storage, and ordering cost.
In real‐life situations, measuring only the delivery performance as mentioned above doesn't give an accurate and complete image. Usually, the extra costs caused by these decisions are considered. We will discuss the specific logistic costs later. This view on logistics is also known as the “logistic concept” (see Figure 1.6). The main focus of this book is the “control” part of this concept.
Figure 1.6 Logistic concept.
Source: Adapted from Ribbers and Verstegen ([1992]).
At this point of the discussion, it is important to understand that the logistic performance of a production process is “only” a part of the total performance of that process. Usually, the performance of a transformation process is based on three considerations:
the quality of the product and process (
Quality
).
the logistic performance (
Delivery
).
the efforts that are taken to do so (
Costs
).
In this book, the focus is on logistic performance, including that part of the costs that are logistic related. The logistic performance of any production system is always the result of the choices made in the design of that system. As explained, these choices concern all four PCOI aspects of a production system. In this book, we will limit the discussion to the choices made concerning the control aspect of the system. Studying LPC of a production system requires an understanding of all aspects of the system involved. In other words, in any real‐life situation, the following logic can be followed to understand the actual situation at hand:
describe the processes, including materials, information, and resources used;
describe the LPC structure, including all planning and control decisions;
describe the division of tasks and responsibilities;
describe the supporting IT systems, including the data available.
1.4 Terminology for Production Control
As already said, we will concentrate on transformation processes that take place in production organizations (transformation of the form) and thus logistics has to be interpreted with regard to physical production processes. In this section, we will define some crucial concepts used in production control (Section 1.4.1) and discuss some general characteristics of a production situation (Section 1.4.2).
1.4.1 Concepts Used in Production Control
If we consider a physical material transformation process, the transformation steps can be, for instance, bending, sawing, drilling, casting, welding, etc. which are called operations and are performed at work centers consisting of one or more (more or less) identical machines. The sequence in which the different operations are performed often is called routing. The routings of different products can be quite different in some production departments, whereas in other production departments, they are identical. If we have a nonphysical process, the sequence in which the different operations like for instance application, classification, calculation, and sending a mail are performed is called workflow. A schematic representation of a production process is given in Figure 1.7.
Figure 1.7 A schematic example of a production process.
A job is a task or combination of tasks that has to be executed at a certain work center for a certain order.
An order is a general term that may refer to such diverse items as a purchase order, shop order, customer order, planned order, or schedule. In this book, we interpret it as a document that contains all the necessary information to produce a series of a (semifinished) product in the production department. Often several jobs have to be executed for one order. Releasing an order means that all the necessary materials, information, and/or tools have been collected and that a department can start working on the first job of that order.
The time necessary for an operation is called the processing time. Often an order occupies a resource longer than the processing time. For instance, at the beginning of the operation the order has to be administrated, the resource has to be set up and at the end of the operation, it might be that the product needs to be cooled down. All that time, the resource cannot be used for another order and we will call this “extended” processing time the service time.
We will call the actual time between the arrival of the order (at a work center) and the completion time of this order (at the work center) the (work center) throughput time, whereas the planned time between arrival (at the work center) and completion (at the work center), often needed for planning purposes, is called (work center) lead time. The lead time determines the Due Date, and the throughput time determines the Completion Date. The difference between these two dates, Completion Date – Due Date, is called the lateness; max(0, lateness) is called the tardiness, and ‐min(0, lateness) is called the earliness.
Remark: Often cycle time or lead time is used instead of throughput time. This can be confusing since cycle time is often used in certain industries (like process industries) with quite another meaning. In this book, we will use these words as described above and thus lead time is used for the planned time and throughput time for the actual time.
Delivery time is the time between the acceptance of a customer order and the delivery of this order to the customer. The transformation process is driven by work orders that are derived from customer orders, where a customer can also be the next stock point or department. Depending on the characteristics of the resources, customer orders might be merged into one work order or split into several work orders.
In Figure 1.7 we see several triangles before the operations. These triangles represent waiting lines (that lead to waiting times) that may occur since to perform the operation a decision is required or resources are required that are limited available. For instance, if at a certain work center, we need a drilling machine and we only have one drilling machine we can only start with a newly arriving order if the drilling machine is idle, otherwise this order has to wait. This leads to the situation that the time between the arrival of the order at a work center and the completion time of the order at this work center, which is called the (work center) throughput time, is larger than the processing time. In many instances, the waiting times are much larger than the operation times which implies that the throughput time mainly consists of waiting time.
1.4.2 Complexity, Uncertainty, and Flexibility
Production control in general can be very complex. Therefore, for developing a (specific) control concept, it is important to know how the production situation can be described in terms of:
complexity
uncertainty
flexibility
Ad a.: Complexity is among others caused by the variety of the products, variety in demand, variety in operations, variety in routings, variety in number of operations per routing, etc. High complexity requires a lot of coordination and therefore one of the main points for a concept for production control is that it should be directed to reduce the complexity. This can be done by decomposition: divide the total production control problem into several subproblems each with its own objective and decision‐making autonomy. An example of this is the decomposition between production unit control and decoupling point control (also called goods flow control), which will be discussed later on. Other examples are the decomposition between control at an aggregate level and detail level and the decomposition between Sales and Production.
Ad b.: Uncertainty is caused by unpredictability and dynamics. We can make a distinction between uncertainty at the demand side and uncertainty at the process side. Uncertainty at the demand side can be caused by the kind of customers (end user; dealer; …), the kind of product (consumer product; professional product; …), etc., and uncertainty at the process side can be caused by the reliability of the machines, fluctuation in processing times, reliability of the suppliers, quality of the materials/ components, etc. These uncertainties influence the desired control concept for a certain production situation. For instance, if there are long‐lasting machine breakdowns, the control is quite different than in case there are more or less frequent variations in the processing times.
Ad c.: Flexibility is important to counteract disturbances. Forms of flexibility are:
multi‐skilled operators
machines that have small setup times and that easily can be changed
commonality (using the same components in several different configurations)
short lead times of components
overcapacity
outsourcing
inventories (makes it possible to react quickly to changes in for instance demand)
overtime, etc.
If there is a lot of flexibility, the effect of uncertainties can easily be downplayed so they don't have a large effect on the desired control concept. Making the (potential) flexibility effective might involve substantial coordination, which might affect the desired control concept.
References
van Assen, M.F. (2016).
Operational Excellence
. (in Dutch). Koninklijke Boom uitgevers.
Dijkstra, L., Dirne, C.W.G.M., Govers, C.P.M. et al. (1997).
Samenwerking in ontwikkeling: productontwikkeling door uitbesteder én toeleverancier
. (in Dutch). Kluwer Bedrijfsinformatie.
MacKay, K. and Wiers, V.C.S. (2004).
Practical Production Control: A Survival guide for Planners and Schedulers
. J Ross Publishing and APICS.
Ribbers, A.M.A. and Verstegen, M.F.G.M. (1992).
Toegepaste logistiek
. (in Dutch). Kluwer.
Veeke, H.P.M., Ottjes, J.A., and Lodewijks, G. (2010).
The Delft Systems Approach – Analysis and Design of Industrial Systems
. Springer‐Verlag London Ltd.
2Horizontal and Vertical Decomposition
Production planning problems are in general too complex to resolve as a single problem. If it is possible to make a monolithic mathematical model of the problem, then this in general will be very complex and very large. Moreover, we then have a centralized model which (implicitly) assumes that there is central control and a high‐level owner of the model/problem in the organization. However:
Models never capture the complete richness of the production situation.
Detailed data and figures (needed to solve some of the short‐term problems), which might give a false sense of security, do not mean much to higher‐level managers.
Central planning takes away control from lower levels, leading to a situation where opportunities to control are not aligned with responsibilities.
As discussed in the previous chapter, one way to cope with the complexity of a problem is to decompose it into several less complex subproblems. In this chapter, we will discuss two ways of decomposing the problem, i.e. horizontal and vertical decomposition. For the production control problem, one way to do this is to distinguish several production units (PUs) along the supply chain. To reduce the control complexity, these units should be self‐supporting, that is all the operations that are necessary for the transformation of the incoming material/components of that unit into outgoing material/components can be performed by that unit. This we will call horizontal decomposition and will be discussed in Section 2.1. Another way of decomposing the control problem is by aggregation or detailing decisions (in terms of time, units, etc.). This we will call vertical decomposition and will be discussed in Section 2.2. Decoupling point control (DPC) initiates orders to be released to the PUs; production unit control (PUC) takes care of the execution of these orders once they are released. The release function is at the border of DPC and PUC; therefore, we will discuss the basic logic of triggers for production (“release triggers”) in Section 2.3. Finally, in Section 2.4, we will give an example of a decomposition.
2.1 Horizontal Decomposition
For any company in a supply chain, the logistic function can be split up into the following three sub‐functions (see Figure 2.1):
Supply logistics: responsible for the timely supply of raw materials for the production process.
Production logistics: responsible for the timely production of the products.
Distribution logistics: responsible for the timely delivery of the products to the customer.
Figure 2.1 Three logistic sub‐functions.
Sometimes the term “material management” is used for the logistic issues on materials in supply and production as distinguished from the logistic issues concerning the capacity resources. In other words, material management:
includes both supply and production.
focuses on the materials needed for the processes.
Usually, issues dealing with materials (“goods flow”) indeed differ from the logistic issues dealing with resources. For instance, in many cases, the capacity resources for production like machines and operators are already available when a customer order arrives; the supply of these resources has been taken care of in the past (machines were bought in the past, and operators may have a long‐term contract). For materials that might be different in most cases, the materials required will be bought after or just a short moment before the customer places the order. That is why “supply logistics” often only refers to the supply of materials, not to the supply of resources.
Jobs are defined in detail by creating (production) orders. Materials only start flowing when an order for a job requiring those materials is released. In most production processes, more than one release decision is taken (see Figure 2.2). At the start of the process, a release decision is taken to release the order to the process (“order release”). All the required order information is gathered, and a check is done on whether the materials used in the process are available. The orders define the number of products to be created, the materials to be used, the jobs to be performed, etc. An example is shown in Figure 2.3. Usually, targets are also set, like the due date of the order (the moment the order should be finished). When the right moment in time has arrived, the order will be released to be processed. What would be “the right moment” depends heavily on the process and circumstances at hand; we will discuss different order release situations later in this book.
Figure 2.2 Release and sequencing decisions in a process.
The order release decision determines which orders should be completed by the process and the need for capacity from the workstations for the next period. Usually, at the order release, each order will get a planned due date, i.e. the moment the order is supposed to be finished by this process. That due date can, for instance, be used to prioritize jobs at individual workstations. With the order release, it is possible to change the priorities of orders based on, for instance, the urgencies in the total set of orders. Also, the choice can be made not to release the order to this process but to choose an order based on the availability of capacity of the first work center of the order (as in “outsourcing”). The order release decision acts as a buffer between the process at hand and possibly previous processes. It decouples the process from the environment. That is why the position where this decision is taken is also called a decoupling point. Decoupling points subdivide larger processes into several subprocesses (see Figure 2.4); they limit the “size” of orders, i.e. the number of workstations to be visited by the order (also known as the length of the routing). That makes it possible to change the content of an order and the priorities before releasing the order for the next subprocess (“order 2” and “order 3” in Figure 2.4).
Figure 2.3 Example of a production order.
Source: https://timsaxblog.wordpress.com/2016/10/27/production-order-documentation-in-ax-2012/ / WordPress.
Figure 2.4 Decoupling points.
At each decoupling point, two types of checks should be done:
Is the order indeed an order to be done by the next subprocess, and are all requirements met for the job to be done? If so, the order can be accepted (“
acceptance
”).
Is the workload of the next subprocess not too high, and/or are all materials and capacity resources required available within the intended lead time? If so, the order actually can be released (“
release
”).
Within the subprocesses, the logistic planning and control will be easier (assuming that these processes are not confronted with impossible demands from the “outside world”). After all, it's only this subprocess one must consider, and not also all the other subprocesses. This is called “horizontal decomposition.” The subsystems performing these subprocesses are called (production) units.
One specific decoupling point is the customer order decoupling point (CODP) (Hoekstra and Romme [1992]) or order penetration point (Sharman [1984]; Olhager [2003]). That decoupling point specifies which part of the process is triggered by a real (customer) order and which part is triggered by planning considerations (see Figure 2.5).
Figure 2.5 Customer order decoupling point.
For instance:
For processes where products are bought in a retail shop or supermarket, the CODP is positioned at point 1.
For processes where products are bought at webshops like
Amazon.com
or
Bol.com
, the CODP is positioned at point 2.
If products are assembled from standard parts, but according to customer specifications (like cars), then the CODP is positioned at point 3.
For processes where products are made completely on customer order (so these products may be customer‐specific), but using raw materials that are in stock, the CODP is positioned at point 4. That might be the case where the supply of these raw materials may take a long time (because of the location of production of these materials or because of the scarcity of the materials). Or it might be worthwhile to buy more raw materials than needed for one customer order because of price reductions at high volumes.
It's also possible to have processes where everything, including the supply of materials, is done on customer order (point 5, “purchase to order”).
A CODP is a specific decoupling point: at this point, a distinction can be made between the part of the process that's done planning‐based and the part that's done customer order‐based. The advantage of having a CODP “downstream” (to the right in Figure 2.5) is that the customer order delivery time can be very short since only limited activities need to be performed after the order has been placed. It's like buying a product in a retail shop; the delivery time would be practically zero. All processes in front of the CODP are done planning‐based, giving opportunities for optimizing the usage of capacity resources, and thus increasing efficiency (Olhager [2003]). Clearly, this can only be achieved with known products and predictable demand (little flexibility in case the demand changes). Having the CODP “upstream” (to the left in Figure 2.5), the advantage might be that processes are only really performed when there is a customer demand (so no products have to be stored waiting for a customer to arrive), and that a distinction can be made between common parts (used in all products) and customer‐specific parts (like options). Since processes only start when there is a customer order, there is considerable flexibility concerning the products that can be demanded. Depending on the demand characteristics, the disadvantage of an “upstream” CODP might be a lower efficiency. So placing the CODP is a trade‐off between efficiency, flexibility, and delivery performance.
