14 design for changeability

7/27/2019 14 Design for Changeability

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Chapter 14

Design for Changeability

G. Schuh, M. Lenders, C. Nussbaum and D. Kupke1

Abstract Numerous markets are characterized by increasing individualization and

high dynamics. A companys ability to quickly adjust its production system to future

needs and conditions with minimum effort is a key competitive factor. Especially in

high-wage countries, two conflicts increasingly complicate the design of produc-

tion systems: the conflict between scale and scope on the one hand and the conflict

between a high planning orientation and maximizing value-added activities on the

other hand. For future production systems in high-wage countries, effective means

are needed to minimize the gaps resulting from this poly-lemma. This contribution

introduces a measurable target system to assess the degree of target achievementwith regard to these criteria. Based on this target measurement system, a new ap-

proach that introduces object-oriented-design to production systems is presented.

The central element of object-oriented design of production systems is the defini-

tion of objects, e.g. product functions, with homogeneous change drivers, which

are consistently handled from product planning up to process design. Both prod-

uct and process design are driven by interfaces between the defined objects and

their inter-dependencies. The findings show that a consistent application of object-

oriented design to production systems will significantly increase the flexibility in

implementing product changes, minimize engineering change and process planningefforts and support process synchronization to achieve economies of scale more effi-

ciently. Two case studies illustrate the implementation and impact of this approach.

Keywords Complexity, Production system, Production management, Object-orien-

ted design

1 WZL at RWTH Aachen University, Aachen, Germany

H.A. ElMaraghy (ed.), Changeable and Reconfigurable Manufacturing Systems, 251

Springer 2009


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252 G. Schuh et al.

14.1 Production Trends in High-Wage Countries

The majority of design problems are driven by trade-offs between numerous con-

flicting effects. If an improvement is achieved in one field, a change for the worse

in another field may arise. This is also true for product and production design

problems. Most traditional design approaches follow an analytical, target oriented

problem decomposition to structure and resolve these trade-offs. While analytic ap-

proaches are successful in stationary environments with good predictability, they

increasingly fail when dynamics grow to become the determining factor.

From an economic perspective, globalized and heavily segmented markets in-

crease dynamics for the production systems and lead to the requirement of a thor-

oughly differentiated product offering and changeable organization of production to

assure a sustainable business development (Wiendahl et al. 2007).

Regarding product and production design, companies today generally face twodilemmas: the dilemma between scale and scope on the one hand and the dilemma

between a high plan- and a high value-orientation on the other hand (Fig. 14.1)

(Schuh et al. 2007). In order to stay competitive, companies are forced to optimize

their production systems towards one position on the continuum of both dilemmas.

The dichotomy scale vs. scope is characterized by highly synchronized systems

and low flexibility (scale) on the one hand and by one-piece-flow and high flex-

ibility (scope) on the other hand. Low total unit cost can be achieved by design-

ing the production system for economies of scale. Economies of scale are particu-

larly achieved by the higher efficiency of strictly synchronized systems but implicatea limited changeability of the production system. Economies of scope are achieved

when high adaptivity is implemented. This means that the systems are designed in

order to enable several pre-defined degrees of freedom. However, additional invest-

ments or a higher number of manual tasks are required, leading to higher unit cost

in comparison with scale optimized production. Having moved away from job shop

production, numerous companies in high-wage countries maximize their economies

Fig. 14.1 Resolution of the

poly-lemma of production

(Schuh et al. 2007)


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Design for Changeability 253

of scale that is, utilize relatively expensive production means and resources to

an optimum degree. These companies try to cope with increasingly individualized

market and changing customer needs by way of customization and fast adaptations

to market needs, often at the cost of optimum utilization of production means and

resources. Thus, realizable economies of scale decrease. Resorting into sophisti-cated niche markets as a general strategy does not seem to be as promising anymore

(Schuh et al. 2007).

The dichotomy of value-orientation vs. planning-orientation is characterized

by less planning and standardized (work) methods (value-orientation) on the one

hand and by extensive planning, modeling and simulation (planning-orientation)

on the other hand. A planning-oriented production system can ensure optimum uti-

lization of production means and resources (e.g. batch sizes or logistics planning),

but at the cost of high planning efforts and most of all reduced flexibility. In compar-

ison to this, value-oriented production systems demand less planning effort beingbased on a continuous process cycle and focused on the value adding activities.

However, it is not guaranteed that optimum operating points will be identified.

Todays high relevance of scope and value-orientation for companies in high-

wage countries is caused by an increasing introduction of dynamics to production

systems. Whenever complex, individualized products undergo frequent changes,

high economies of scope and low planning-efforts promote successful adaptation.

Without a substantial influence of this kind of dynamic on a production system,

scope and value-orientation would almost not have any relevance for a production

system. Without this influences companies could straighten their production plan-ning oriented to well known conditions.

To achieve a sustainable competitive advantage for production in high-wage

countries, it is not sufficient to achieve a better position within one of the di-

chotomies scale vs. scope and planning-orientation vs. value-orientation. The

objective for future production systems has to be the resolution of both dichotomies,

the poly-lemma of the production (Schuh et al. 2007). The vision of the future pro-

duction system for high-wage countries is achieving an individualized and flexible

production system at the cost of todays mass production.

14.2 Introduction of a Target System

for Complex Production Systems

14.2.1 Holistic Definition of Production Systems

In order to master the resolution of the described poly-lemma of production sys-

tems, a suitable understanding of production systems is inevitable. According to theholistic definition underlying further research, the basic elements of a production

system are the product program (the product program is the sum of all product fam-


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254 G. Schuh et al.

Productprogram

Productarchitecture

Productionprocesses

Resourcestructure

Requirements Product variety Communality Capacities Added value

Market Network

Configuration space of a production system

Optimum

complexity

Optimum

diversity

Optimum

structure

Optimum

value

stream

Direct, influenceable main criteria (design fields): control elements / flexibility elementsElements of a production systems

Levers of complexity management

Productprogram

Productarchitecture

Productionprocesses

Resourcestructure

Requirements Product variety Communality Capacities Added value

Market Network

Configuration space of a production system

Optimum

complexity

Optimum

diversity

Optimum

structure

Optimum

value

stream

Direct, influenceable main criteria (design fields): control elements / flexibility elementsElements of a production systems

Levers of complexity management

Fig. 14.2 Elements of a production system according to holistic research definition

ilies), the product architecture, the production processes and the resource structures

(Schuh et al. 2007). They define the configuration space of a production system

(Fig. 14.2).

Product type, variant, quality and quantity are defined within the product pro-

gram, which will be offered (Bleicher et al. 1996). One of the main challenges is

to define optimum product diversity within the product program. The product ar-

chitecture is the sum of product structure and functional structure as well as the

transformation relationships between the two. Every physical element of the prod-

uct structure can be described with the attributes function, technological concept

and interface (Meier 2007). The goal is finding the optimum degree of complexity

in the product architecture to meet the manifold requirements. The core of a produc-

tion system is the production process itself because it constitutes the physical value

creation and has to be optimized in terms of value stream. The resource structures,

such as supply chain management and quality management, are further downstream

elements of a production system included within this definition. The improvement

of resource structures in terms of process optimizations is the main challenge in this

field.

14.2.2 Target System for Complex Production Systems

It is the target of the described production research to minimize the poly-lemma ex-plained in Fig. 14.1. In order to measure, manage and control the impact of changes

to a production system, a collectively exhaustive set of key performance indicators is


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256 G. Schuh et al.

It is the objective of any improvement measure of a production system to enhance

at least one or ideally several of the four basic goals while not deteriorating any of

the other goals at the same time.

14.2.3 Differentiation Between Complicated Systems

and Complex Systems

Nowadays, production systems are particularly affected by the increasing dynamics

of market requirements as already pointed out above. A new generic understanding

and categorization of the environment of production systems is necessary to distin-

guish system requirements into a time-dependent and a variety-dependent part. This

differentiation will allow a thorough differentiation between complex and (merely)complicated system elements (ElMaraghy et al. 2005).

Complexity is mainly characterized by two elementary system conditions: on the

one hand by the impossibility to interrelate all elements of a system to each other,

and on the other hand by the in-determination and unpredictability of a systems

behavior (Schuh 2005b).

The composition of a system is also determined by the number and variety of the

elements and their connections. System complexity depends on the changeability

of system parameters over the course of time. Four basic types of systems can be

distinguished (Fig. 14.4):

Simple systems: few elements, inter-dependencies, and behavior possibilities

Complicated systems: many elements and inter-dependencies; system behavior

is deterministic

Complex systems: few elements and inter-dependencies; high number of behav-

ior possibilities; entire controllability is not possible

Complex and complicated systems: many elements and inter-dependencies;

high changeability of system elements over time.

Fig. 14.4 Basic system typesaccording to differentiation

of variety and changeability

(Grossmann 1992)

Complicated

system

Complex and

complicated

system

Simple

system

Complex

system

Changeability, dynamics

Low High

Low

High

Variety

Complicated

system

Complex and

complicated

system

Simple

system

Complex

system

Complicated

system

Complex and

complicated

system

Simple

system

Complex

system

Changeability, dynamics

Low High


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Hence, complexity is a result of product and process variety influenced by external

dynamics. The complexity problem can be divided into static and dynamic parts,

which is helpful for the understanding and resolution of the complexity problem

(Reiss 1993).

The merely complicated part of a production system is characterized by a largenumber and variety of system elements, which have many inter-dependencies. How-

ever, the varieties and their inter-dependencies can be precisely described and are

thus not complex. Solving complicated but not complex tasks can be achieved

through an explanatory approach using models, methods, planning and simula-

tion. Whereas the complicated part is characterized by predictability and determina-

tion, the complex part of the production system is characterized by its unpredictable

and undeterminable nature. In short, complexity exists when surprise comes into

play.

14.3 Approach to Mastering Complexity in Production Systems

One of the key issues of future production systems design will be to identify the

optimum internal complexity corresponding to variety required externally. Every

production system is designed to master a certain (today possibly very low) share

of complexity i.e., system elements without precisely predictable states or condi-

tions as opposed to deterministic (complicated) system conditions.

14.3.1 Object-Oriented Design

The central approach to mastering complexity in production systems will be the

application of object-oriented design throughout the entire value chain from product

program to resource structures. Object-oriented design is focused on an interface

and interdependency driven design of systems.

An object-oriented method, especially for facility layout planning, has been de-

veloped at the Laboratory for Machine Tools and Production Engineering (Bergholz

2005). Using this approach, organizational units and processes shall be treated as en-

capsulated modules with defined interfaces so they can be configured in an object-

oriented way (Gottschalk 2006). Based on a temporary cross-linking of these mod-

ules, changeability can be achieved to face the dynamic challenges in the field of

production systems by a flexible adaptation of single modules simultaneously re-

sulting in robust structures.

Based on certain parallels, the theory and development of object-oriented soft-

ware engineering inspires facility layout planning (Bergholz 2005). The software

industry is affected by very fast hardware development cycles in combination with

rising software complexity. Hence, software industry is a very dynamic industry as


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258 G. Schuh et al.

well (Balzert 1998). Against the background of increasing customer requirements,

particularly large software systems must be capable of being reconfigured with little

time and effort. Software changes are to be minimized to keep development efforts

as small as possible. Despite external dynamics, a high level of system stability has

to be achieved. In software engineering, the principle of object orientation for thesupport of versatile software has been widely established (Oestereich 1998).

14.3.2 Object-Oriented Management of Production Systems

The described approach for object-oriented design of production systems consists

of four steps (Fig. 14.6). Steps one to three describe how to identify, analyze and

classify the complexity drivers and how to specify the production system. Step fourexplains how the complexity of production systems can be controlled by object-

oriented design.

The four steps are explained as follows:

1. Identify and classify the change drivers

In the first step, the reasons for dynamic changes are analyzed and the necessity

for changeability is determined. The changeability requirements of a production

system can be described by so called change drivers (Wiendahl et al. 2007).

Change drivers are characteristic of a specific production system and can there-

fore not be generalized. At high level aggregation, it is possible to differentiatethe following types of change drivers (Schuh et al. 2005a):

Product-related change drivers can be identified along the product struc-

ture, in most cases defined by the product assembly process (e.g. geometry

changes of certain parts)

Volume-related change drivers can be decomposed into few basic mech-

anisms: Adding of resources, integration and separation of processes into

resources, substitution (e.g. manually by automated) and optimization (e.g.

slow by fast tooling).

Technology-related change drivers can be classified into product- and process-

related change types (e.g. new joining technique).

Object-oriented design: Separation of merely complicated and really complex elements

Description of the production system: Define interdependencies and interfaces

Description of the production system: Detailing and evaluation of change profiles

Identify and classify the change drivers

4

3

2

1

Object-oriented design: Separation of merely complicated and really complex elements

Description of the production system: Define interdependencies and interfaces

Description of the production system: Detailing and evaluation of change profiles

Identify and classify the change drivers

4

3

2

1

Fig. 14.5 Four steps for object-oriented design of production systems


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System

Subsystem A

Subsystem BSubsystemC

A 1

A 2

A 3A 5

A 4 A 6

Elements

Change profiles

t

C3

B1

A4

A2

C1

A5

A3

A1

t

C2

A6

B2

t

System

SubsystemA

SubsystemB

SubsystemC

A 1

A 2

A 3A 5

A 4 A 6

Elements

Change profiles

t

C3

B1

A4

A2

C1

A5

A3

A1

t

C2

A6

B2

t

Fig. 14.6 Detailing of the production system and evaluation of change profiles (Schuh et al. 2005a)

For an object-oriented design (Step 4) it is important to identify these change

drivers and to classify them with regard to their attributes (entry frequency, cause

etc.). The analysis of change drivers reveals when, how often and why a system

has to change. In addition, it must be shown how accurate the predictions of

changes are.

2. Description of the production system: Detailing and evaluation of change pro-

files

In the second step, the production system is analyzed. Systems can be detailedinto multiple subsystems, whereas higher system levels always contain the lower

ones. The smallest parts in such decompositions are called elements (left half of

Fig. 14.7).

With regard to production systems, e.g. the structure of a factory, they can be

detailed in several production lines that again consist of several workstations

(Schuh et al. 2003).

The possible level of detail depends on the application case and planning status.

The intention of detailing is the identification of system elements whose inter-

dependencies and properties are focused on in the next steps.Based on the analyzed change drivers, the properties of the system elements

have to be examined. To minimize the system changes caused by change drivers,

it is important to figure out the dependencies of the change drivers and sys-

tem elements. Change drivers cause different change profiles (amplitude or fre-

quency of the changes, right half of Fig. 14.7). The elements can be classified by

allocation of the system elements to different change profiles. This classification

is important for object-oriented design (step four).

3. Description of the production system: Define inter-dependencies and interfaces

The third step focuses on the inter-dependencies between the identified elem-ents. The inter-dependencies between the individual elements will now be ana-

lyzed (Fig. 14.8).


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Fig. 14.10 Flexible automated changeable feeding system (Schuh et al. 2005a)

14.4.2 B: Release-Engineering in the Automotive Industry

Development processes in the automotive industry have many constraints result-

ing from many design changes of different, highly interdependent components overtheir life cycle. Insufficiently coordinated product changes are a substantial com-

plexity driver.

The decoupling of product structure elements into objects is the solution to man-

age the dichotomy between rising development efforts for product or component

changes and required economies of scale of the entire product.

The definition of object-oriented design within the product structure enables the

establishment of a release-oriented engineering (Release-Engineering), which is

based on significantly lower influences of inter-dependencies due to a bundling of

product changes in releases (Schuh 2005b).

The realization of the full potential of Release-Engineering requires a new way

of product modularization. Release units have to be optimized in terms of inter-

dependencies and their planned innovation frequencies. The formation of release

units can be divided into four stages:

Segmentation and clustering of components

Classification of inter-dependencies

Optimization of inter-dependencies

Definition of release units (objects within product structure) and release cycles.

In the first step, the product components have to be divided based on a modular

product structure. The accurate identification and classification of change drivers is


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264 G. Schuh et al.

Fig. 14.11 Abstract model for release units and parts inter-dependencies

crucial at this stage. Components are classified in predefined clusters according to

their innovation frequencies.

In a second step, the different inter-dependencies have to be classified to bundle

components. Therefore change profiles have to be detailed and evaluated whereas

the level of detail depends on the application case. The analysis of dependencies

between change drivers and system elements is the core part in this step.The third step consists of the optimization of inter-dependencies mentioned

above. Thereby, the product architecture has to be designed according to criteria

exceeding mere functional or spatial considerations by additionally analyzing inter-

dependencies in terms of different innovation and change cycles. An abstract model

can illustrate the bundling of parts to releases and the inter-dependencies between

these parts. The release unit as such is symbolized by a composition of individual

parts that are interlinked and illustrating interdependency (Fig. 14.11).

A differentiation has to be made between intended changes and reactive changes,

i.e. those that are provoked by an intended change but do not represent any added

value. In Fig. 14.11 the consolidation of three independent changes to one release

is shown. As a result, the number of intended changes remains the same (five, high-

lighted by a dark background) at the same time the quantity of reactive changes

(bright background) is reduced from ten to three. This example illustrates the poten-

tial of engineering in releases.

In a last step, objects and corresponding release cycles are defined according to

the inter-dependencies and actual change cycles by a separation of complex and

complicated system elements. The focus is placed on a prearrangement of change

cycles such that not each modification or change will be allowed or implemented

unless the time frame permits delays. As a result, changes appear bundled withineach release.


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The concept of release engineering was exemplified at a large first tier automotive

supplier that produces steering columns. In this case, the steering column module

consisted of 80 parts that were all subject to potential changes. The entire module

was marked by an average change index of 3.5 during a 9-month time span between

the release of means of production and SOP (start of production). Multiplied withits quantity of parts, it resulted in a total quantity of 280 part changes during the

described period. The exemplified steering column module for a particular type of

car is sold in 90 variants. For approximately 10 percent of all individual variants,

changes have to be executed. The 280 part changes multiplied by 10 percent times

90 variants result in a total of 2,520 changes that were subject to our considera-

tions. Roughly estimating a share of 60 percent for reactive changes (being caused

by other, intended changes), this number divides into 1 512 reactive changes and

1 008 intended changes. Assuming five intended changes on average per change

process, the company needs to carry out approximately 202 intended change stepsin 39 weeks. The described consolidation of changes to release being performed

every second week leads to a number of approximately 52 intended changes per

step, assuming a fixed number of intended changes. The reactive changes per step

summed up to approximately 30. Hence, the resulting quantity of executed reactive

changes adds up to 585 (vs. 1 512 changes before) and the total number of changes

now equals 1 170 (vs. 2 520 changes before). Looking at percentage changes, this

means a 61 percent and 54 percent reduction in reactive and total changes respec-

tively. Thus, Release-Engineering leads to a reduction of the addressed poly-lemma

in modern production systemsIn terms of an object-oriented method, release engineering increases develop-

ment efficiency by adopting this development principle from software engineering

and introducing it to the field of mechanical engineering. The synchronization of

changes and innovations enables the bundling of changes. As a result, unnecessary

change processes can be eliminated and large savings potentials regarding change

efforts can be uncovered and utilized.

14.5 Summary

Markets are characterized by an increasing individualization and high dynamics.

Consequently, companies have to be able to adjust their production system to actual

and future conditions quickly and with low effort. Therefore, companies have to

resolve the two dichotomies scale vs. scope and value-orientation vs. planning-

orientation to achieve a sustainable competitive advantage. In order to measure,

control and manage the impact of changes on a production system, a target system

was explained. These target system can be used to evaluate the degree of target

achievement further on and simplify the understanding of their inter-relationships

and their relevance for todays production systems.


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266 G. Schuh et al.

A central approach to mastering complexity in production systems is an object-

oriented method based on analogies to object-oriented software engineering. The

described approach for the object-oriented design consists of four steps. Step one

to step three describe how to identify, analyze and classify the dynamic drivers and

how to specify the production system. Step four explains how the complexity ofproduction systems can be controlled by object-oriented design.

The application of the approach for the object-oriented design has been shown

based on two examples.

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