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Production Planning & Control,Vol. 16, No. 7, October 2005, 634651
Stumbling blocks of PPC: Towards the holistic
configuration of PPC systems
H.-H. WIENDAHL*y, G. VON CIEMINSKIz and H.-P. WIENDAHLz
yInstitute of Manufacturing and Management (IFF),
University of Stuttgart, Nobelstrasse 12, 70569 Stuttgart, Germany
zInstitute of Production Systems and Logistics (IFA),
University of Hannover, Scho nebecker Allee 2, 30823 Garbsen, Germany
Manufacturing companies often complain about the difficulties they face in meeting theircustomers logistic requirements. Many blame the perceived inadequacies of their productionplanning and control (PPC) software for their performance deficits. The paper illustrateswhy this is only a partial view of the causes of the shortcomings. PPC software is just oneof six configuration aspects of the entire PPC system. The authors argue that the configurationof the PPC aspects objectives, processes, objects, functions, responsibilities and tools has to becarried out methodically and consistently in order for the PPC system to function properly.The analysis of examples of so-called stumbling blocks of PPC, inadequate configurationsof one or several of the aspects, supports this claim. The paper closes with the proposal of achecklist that the authors suggest as a first approach to ensure the consistent configuration ofPPC systems.
Keywords: Production planning and control systems; Configuration aspects of PPC systems;Stumbling blocks; Configuration and operation of PPC systems; Actors in PPC
1. Introduction
It is almost 30 years since Orlicky (1975) first described
the material requirements planning (MRP I) algorithm.
To this day the algorithm remains the kernel of many
production planning and control (PPC) systems. Despite
30 years of progress in PPC theory and practice, and
the definition of additional key functions, a large
number of manufacturing companies remain unsatisfied
with the degree of fulfilment of their logistic objectives.
Recent surveys prove that companies still miss theirlogistic targets by a wide margin (Fraunhofer IPT
Institute 2003, Wiendahl 2003a). This applies to the log-
istic performance measures of productionwork-in-
progress levels, throughput times and schedule
reliabilityin the same way as to those of stores:
inventory levels, service levels and delivery delays.
A historical review reveals various causes of the
unsatisfactory logistic performance and, considering
these, the solutions that a holistic configuration of
PPC systems requires. In the past, critical evaluations
of PPC methods identified the limited capabilities of
computer hardware as the principal cause for the insuffi-
cient fulfilment of logistic objectives. These hardware
limitations only allowed a step-by-step development
of PPC algorithms. Due to this, the manufacturing
resource planning (MRP II) algorithm that followed
MRPI is characterised by the successive execution ofits functions. As real situations in manufacturing
companies seldom conform to the rigid assumptions
that are underlying this algorithm, there were calls for
a more realistic consideration of practical conditions.
PPC research therefore concentrated on the develop-
ment of new functions and algorithms (Plossl 1985,
Vollmann et al. 1997) and neglected the analysis of
the required preconditions such as an organisational
framework for PPC (Kraemmerand et al. 2003).*Corresponding author. Email: [email protected]
Production Planning & ControlISSN 09537287 print/ISSN 13665871 online # 2005 Taylor & Francis
http://www.tandf.co.uk/journals
DOI: 10.1080/09537280500249280
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Over time, the remarkable progress of computer tech-
nology facilitated the application of more powerful
planning software such as enterprise resource planning
(ERP), supply chain management (SCM), advanced
planning and scheduling (APS) or manufacturing execu-
tion systems (MES) (Stadtler 2002). All of these systems
carry out a considerably larger number of functionsthan their predecessors. They apply sophisticated
mathematical algorithms to solve multi-variable
optimisation problems and can thus consider numerous
planning restrictions simultaneously. Due to the
immense complexity of the implementation of these
large systems they often fail to produce the substantial
logistic performance improvements the companies
are hoping for (Davenport 1998). In contrast, other
businesses preferred simple PPC approaches. The
increased popularity of just-in-time principles and
Japanese management methods made companies avoid
the application of software and focus on organisational
aspects instead. They achieved remarkable performancegains, e.g. by the introduction of Kanban control cards
(Soder 2004). The contrast between highly sophisticated,
computerised PPC systems whose logistic performance
is insufficient and simple, rules-based control mechan-
isms that achieve astonishing results made researchers
and industrialists realise that the problems of PPC
cannot be solved by more powerful software alone.
There seem to be other causes of the described perfor-
mance deficits, which had been neglected so far.
The standard textbooks on PPC offer detailed
descriptions of the theoretical foundations of the PPC
functions, mainly mathematical models and algorithms
(Plossl 1985, Fogarty et al. 1991, Hopp and Spearman
2000, Vollmann et al. 1997). However, instructions on
the design and implementation of PPC systems are
uncommon or not very detailed. Fogarty et al. (1991)
emphasise that the choice of a logistic strategy should
reflect the nature of the customer demands. The logistic
strategy in turn determines appropriate manufacturing
strategies and the corresponding feasible planning and
control methods. Vollmann et al. (1997) stress the
importance of mapping the planning and control
processes specifically for the purpose of implementing
PPC software to support the planning functions. The
same authors provide a selection of the prerequisitesof the system implementation. Otherwise, there are
only case studies on MRP or ERP system implementa-
tions available that provide some indication on the
critical success factors of PPC systems (see, for example,
Akkermanns and van Helden 2002, Wiers 2002).
In general management literature, important
approaches are being discussed that aim to ensure the
fulfilment of business objectives. Publications on PPC
almost completely ignore these discussions, especially
as far as the role of operational employees is concerned.
Kaplan and Norton (1996) propose the balanced score-
cards as a method to link business strategies to specific
aspects of performance. Miles and Snow (1978) deter-
mine what types of business organisations lead to
above-average levels of performance. Maslow (1987)
and Huczynski and Buchanan (1991) explain the impor-tant influence that human motivation and employee
involvement have on the performance of a business.
Storey and Sisson (1993) discuss the effects of
performance-related pay on the performance of a com-
pany and provide instructions on the effective design of
remuneration systems. In order to ensure that PPC
systems contribute to high levels of logistic performance,
these general methods and approaches have to be
adapted for the specific field of production management.
Publications that transfer these approaches to the field
of PPC have only recently been published (Wa fler 2003,
Wiendahl and Westka mper 2004, Nyhuis 2004).
According to the authors experience it is not only theneglect of above-mentioned important factors but also
the lack of awareness of the correlations between sepa-
rate factors that affect the configuration of PPC systems
and lead to undesirable logistic performance deficits.
These so-called stumbling blocks of PPC are errors in
the configuration of a PPC system as a whole. The
symptoms of these stumbling blocks, insufficient fulfil-
ment of logistic objectives, a lack of transparency and
excessive efforts required, are easily identifiable. Often
though those responsible for PPC on the operational
level are not able to simply remove the stumbling
blocks. On the one hand the interdependencies between
their causes make a final analysis more difficult; on the
other hand, the changes required by the situation can
exceed the competencies of the operational staff
involved. In most cases, only the managing directors
can remove the causes of the stumbling blocks.
Therefore, the objective of this article is to create a
framework for the identification, analysis and removal
of classic stumbling blocks of PPC:
. Section 2 defines the key terms of PPC. The PPC
system, configuration aspects of PPC and
stumbling blocks of PPC.
.
Section 3 describes typical stumbling blocks ofPPC. The descriptions first identify their respective
symptoms, analyse their causes and present
possible solutions to remove the stumbling blocks.
The practical examples included in the discussion
of each stumbling block are based on the experi-
ences the authors gained in industrial projects.
The projects focus on the configuration of PPC
concepts, the selection of suitable software tools
and the implementation of both in practice.
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. Section 4 outlines a framework for the holistic
configuration of a PPC system. It lays the founda-
tions for a coherent and customised composition of
the planning and control functions of manufactur-
ing companies.
. The conclusions in section 5 draw the insights
together in the form of a questionnaire. The holisticconfiguration of a PPC system should consider the
issues that the questionnaire raises in order to
avoid the formation of stumbling blocks.
This merges the aspects of the functions and data of
PPC as well as its processes and responsibilities in an
integrated model that provides a basis for the holistic
configuration of PPC systems.
2. Key terms of PPC
The PPC system is the central logistic control mechan-ism that matches a companys output and logistic
performance to the customer demands. The task of the
PPC system is to plan, initiate and control the product
delivery of a manufacturing company as well as to
monitor and, in case of unforeseen deviations, i.e.
disturbances or order changes, to re-adjust the order
progress or the production plans.
2.1 PPC system
In the context of this paper, the term PPC system
denotes the entirety of functions and tools used for the
planning and control of the logistic processes in a
manufacturing company. The scope of application of a
PPC system includes the three value added processes,
Source, Make and Deliver, in accordance to the termi-
nology of the supply chain operations reference (SCOR)
model (Supply Chain Council 2004) (cf. figure 1a). The
input and output stores of a company are thus subject
matter of a PPC system in the same way as production.
The PPC system crosses company boundaries: It allowsfor the requirements of customers and suppliers since,
following supply chain management principles, the
management of the storage processes takes the delivery
performance of the suppliers as well as the demand
behaviour of the customers into account. According
to this definition, the term PPC system comprises
more than just the PPC software. The software is only
the tool to plan and control the logistic process chain
as well as the storage of production master data and
feedback data.
2.2 Configuration aspects of a PPC system
On the basis of this definition, six configuration aspects
of a PPC system can be distinguished (cf. figure 1b):
. The logistic objectives of a company are situated
at the heart of the PPC system. If necessary, these
have to be differentiated for different departments
of the company.
. The PPC processes determine the logical and
chronological order of PPC planning and control
activities. Thus they define the workflow of order
processing in terms of the information flow along
the logistic process chain. The activities related to
the material flow follow the same logic, but are not
directly a subject matter of the PPC system.
Value-adding processes
Source Make Deliver
(a) (b)
Object Responsibility
ProcessFunction
Objective
Figure 1. Definition of a production planning and control system. (a) Scope of application and (b) configuration aspects.
636 H.-H. Wiendahl et al.
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. The PPC objects are the planning objects of
PPC. The most important objects are the articles
(finished products, components or raw materials),
resources (machinery and personnel) and orders
(customer orders, spare parts orders, sample
orders, etc.).
. The PPC functions define the activities that arerequired to plan and control the logistic processes
in the stores and in production. The fundamental
activities are the definition of local objectives and
targets, forecasting and decision-making, providing
feedback on order progress as well as continuous
improvement.
. PPC responsibilities determine the positionsand
therefore the members of staffthat are in charge
of certain PPC activities. Conventional PPC
systems ignore this organisational view as they
operate on the assumption that responsibilities
are organised by a central entity (see for example
Hackstein 1989, Vollmann et al. 1997).. The five configuration aspects described above
constitute the logical core of a PPC system. The
purpose of the tools for planning and control is
to support the operational order processing by
(semi-)automated PPC activities. This creates stan-
dards for the operational activities and relieves staff
of time-consuming routine tasks. More time there-
fore becomes available for the required planning
and control decisions.
These configuration aspects serve as a theoretical
basis to analyse and remove the stumbling blocks
of PPC.
2.3 Stumbling blocks of PPC
The presence of stumbling blocks of PPC becomes
apparent through symptoms such as the insufficient
fulfilment of logistic objectives, a lack of transparency
of order processing or an unnecessarily high effort of the
staff involved in carrying out PPC activities. The term
stumbling block exclusively applies to internal mistakes
in the configuration of the six aspects defined above.Factors related to the external environment such as
unreliable suppliers or literally chaotic customers are
not considered. The PPC system itself does not have
any control over these factors. Nevertheless, the external
factors represent requirements that have to be consid-
ered when designing the PPC system.
An analysis of the relationships between causes and
effects is required in order to detect and remove the
stumbling blocks.
Ideally, the symptoms can be traced back to a single
cause. In this case, only one configuration aspect is
affected and the mistake in the configuration is easily
detected and removed. An example is the entry of
incorrect planned capacity values into PPC software.
If, for instance, the capacity of a bottleneck work
system has wrongly been set at 18 hours per workingday instead of the correct value of 16 hours, production
overloads arise. This stumbling block can be
easily removed by a simple correction of the planned
capacity value.
In cases where several cause-and-effect relationships
influence or even amplify each other, the removal of
stumbling blocks becomes more complex. Here, several
of the configuration aspects are affected. Even though
their symptoms are as apparent as for the simple
stumbling blocks, their removal is a lot more difficult:
It is necessary to, first, identify the relationships between
the different causes. Secondly, the causes in different
configuration aspects have to be changed simultaneouslyand in a co-ordinated way. Typically, this exceeds the
competence of the operational actors so that their
managers have to understand and remove the stumbling
block.
3. Typical stumbling blocks of PPC
The following examples describe the stumbling blocks
with several causes that are most commonly found in
industrial practice. Each explanation is divided into the
description of the symptoms and the analysis of their
causes. Measures that are used for the removal of the
stumbling blocks follow. The examples are based on real
situations in industrial companies.
3.1 Stumbling block missing positioning in system of
logistic objectives
The first example of a stumbling block of PPC highlights
the importance of defining consistent objectives and of
communicating the responsibilities for fulfilling the
objectives clearly to the staff that plan production
operations or carry them out.In PPC, one can often find conflicts between the
logistic objectives work-in-progress level (WIP level),
utilisation, throughput time and schedule reliability
because they are neither compatible nor locally or
temporally constant (Wiendahl 1995). Accordingly,
one should never maximise or minimise the value of
just one objective, but consider the simultaneous
effects of measures on all logistic objectives. The nature
of these conflicts has been recognised for some time
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(Gutenberg 1951, Plossl 1991). Nevertheless, many com-
panies are not aware of their consequences. Frequently,
production managers are trying to optimise the utilisa-
tion of work systems concurrently to the throughput
time. Detailed investigations demonstrate that such an
approach is not target-oriented because ultimately no
single objective of the optimisation can be defined.Substituting the minimum-cost objective for the logistic
objectives does not resolve the conflict. Instead, compa-
nies should start by setting strategic objectives derived
from the market environment (Ketokivi and Heikkila
2003). Typical examples of such objectives are Reduce
throughput times by 50% or Maintain a delivery relia-
bility of 95%. These objectives serve as the priorities,
which dominate the trade-off that has to be reached with
the remaining logistic objectives. The production oper-
ating curves are a proven methodology for the analysis
of the interdependencies between logistic objectives and
their consequences for PPC. They quantitatively
describe the dependence of the objectives utilisation,throughput time and schedule reliability on the WIP
levels in production and can easily be computed
(Nyhuis and Wiendahl 2003). Figure 2 shows that the
best possible target values for the different logistic objec-
tives do not coincide at the same WIP level of a work
system. A classical example of this phenomenon is the
conflict between short order throughput times and
high work system utilisation that was already
mentioned. Whereas short work system throughput
times can only be achieved at low WIP levels, high
WIP levels are required in order to guarantee a high
utilisation. This in turn leads to excessive throughput
times. The situation requires a trade-off between
the logistic objectives. Companies can achieve this by
positioning their logistic processes at certain operating
points on the production operating curves.
The conflict between objectives described above
only represents a stumbling block if those responsible
ignore it in their day-to-day job. In a typical example,
the managing directors of a medium-sized manu-
facturer of construction components required shortthroughput times to achieve short delivery times.
At the same time, they demanded a high utilisation
of expensive machinery in order to obtain a fast
return on investment. The production operation curves
clarify the conflict that the production department
faced as a result (cf. figure 2): On the one hand,
the objective of short throughput times requires a
low WIP level in production (WIPTTPmin). On the
other hand the objective of a high utilization
necessitates a high WIP level (WIPUmax). The inconsis-
tent directives of the directors are the cause for two
stumbling blocks:
. In day-to-day business, concrete decisions concern-
ing orders have to be taken. Conflicting manage-
ment directives fail to determine the most
important logistic objective. As a result a guideline
for these decisions is missing.
. As the management directives described above are
contradicting in themselves the target values that
are derived from them have to be as well.
Therefore it is impossible for operational planners
to take rational decisions.
The production operating curves are helpful tools to
analyse and remove both stumbling blocks:
. Initially, the curves explain the interdependencies
between the logistic objectives and facilitate their
relative prioritisation (step 1 of the logistic posi-
tioning).
. The remaining target values follow from the value
set for the most important objective. For example,
the desired throughput time determines both the
target utilisation as well as the target WIP level
(step 2 of the logistic positioning).
Taking a strategic decision, the directors regarded
short throughput times as the most important objec-
tive. However, in order to implement the new manage-ment directives, further boundary conditions had to be
considered. The machine operators still tried to
maintain high WIP levels at the work systems so
that they always see a work load in front of their
machines and can reduce setup times by changing the
sequence of orders. Obviously, this strategy also
supports a high work system utilisation. At the same
time it adversely affects throughput time and schedule
reliability.
WIP level
Utilisation
Maximum
SchedulereliabilityMaximum
Minimum
Throug
hputtim
e
WIPUmaxWIPTTPmin0
WIPTTPmin: WIP level at targetthroughput time
WIPUmax : WIP level attarget utilisation
Figure 2. Logistic operating curves as a model of theinterdependencies between logistic performance measures.
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In order to maintain the desired prioritisation of the
logistic objectives, management should take the follow-
ing actions:
. Offer qualification in production logistics to all
relevant employees (including shop floor operators)
and communicate the new priorities of the logistic
objectives.
. Verify the conformance of the logistic objectives
with the interests of the employees. In particular,
management has to ensure that compensation
schemes effectively support the objective of short
throughput times.
The following section describes how those involved
influence production planning and control, and
how their decisions impact on the fulfilment of logistic
objectives.
3.2 Stumbling block divergent stakeholder interests
The second stumbling block confirms the importance of
the consistency between the logistic objectives and the
PPC staff who have the responsibility for meeting the
targets. It also stresses the fact that staff has to be
qualified in order to carry out PPC functions.
In an empirical study on the implementation of ERP
systems, Amoako-Gyampah (2004) came to the conclu-
sion that different levels of the management hierarchy
have different perceptions of the system to be intro-
duced. It is therefore essential that the managing
directors not only provide all future users with adequate
training in the application of the new system, but that
it is equally important they make efforts to convince
staff members of the benefits of the change and of the
necessity to utilise the new system to achieve enhanced
business objectives.
The report by Wiendahl et al. (2002, 2005) on the
introduction of a Kanban control is a prominent exam-
ple for the potential for conflicts between such business
objectives and the individual objectives and interests of
production employees. In this case, production manage-
ment wanted to reduce throughput time and WIP levels
significantly. The central planning department wasresponsible for the design of the Kanban system and
the setting of its parameters. On the basis of customer
demands and target replenishment times the planners
also calculated the number of Kanban cards required.
The production department was briefed about the
changes and a subsequent trial run passed without
problems. The company therefore regarded the
implementation of the new production control system
as a success.
It came as a surprise that the production was not able
to sustain the aspired improvements for more than a
short time after implementation of the new control
system. Rather, both the values of WIP and throughput
times soon rose to old levels again. The detailed analysis
of the production department that was initiated as a
consequence, revealed insufficient consultation with theproduction operators.
The operators pursued the objectives job security
and stable order processing by stockpiling orders for
uncertain times in the future. This leads to unnecessary
safety stocks, permanent changes to the order sequence
and decreasing schedule reliability.
Obviously the pull principle that is underlying the
Kanban control does not conform to these interests of
the production operators: Kanban enforces temporary
idle times for most work systems. In order to counteract
this, the operators added copied Kanban cards to the
Kanban control loops to raise WIP to the previous
levels. Thus, they apparently resolved the conflictsbetween the objectives of the company and their own
individual objectives. Production management only
realised that the unwanted modifications had been
made and understood the exact causes of the modifica-
tions after the analysis of the Kanban control system.
The example highlights the prerequisites for a
sustained successful implementation of the new control
system; thorough qualification of all staff involved and
an incentive system that emphasises the objectives of
due-date oriented order processing (in order to avoid
order sequence modifications) and flexible working
hours (in order to guarantee processing on demand)
rather than promoting the conventional objective of
high resource utilisation.
3.3 Stumbling block missing responsibility
for inventories
The third stumbling block illustrates the consequences
of a lack of coordination of the responsibilities for the
PPC processes and objects. They result in an insufficient
fulfilment of the logistic objectives.
Often, there is no clear dividing line separating onearea of responsibility from another. Typical symptoms
are high inventory levels of purchased components and
finished products, or recurrent discussions on the
binding effect of orders and their reliable fulfilment.
The company described in this section produces
make-to-order machines of medium complexity. Depen-
ding on the customer requirements, this may include
engineer-to-order operations. A detailed analysis
was initiated by the managing directors who were
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dissatisfied with the high inventory levels of purchased
components and finished products, and the uncertainties
caused by sudden changes of due-dates or engineering
changes.
Figure 3a shows parts of the order processing chain.
Figure 3b indicates the problems resulting from an
unclear definition of interfaces: The production isresponsible for the material flow from the start of the
production order (i.e. printing of order documentation)
to the final operation (i.e. input to store). This includes
the responsibility for throughput times and WIP
levels. Subsequently, the finished products are handed
over to the sales department, either to be delivered
immediately or to be stored in the finished product
store. The purchasing department has the responsibility
for all purchased components. However, there is no
responsibility defined for the target inventory levels for
finished products. The company neither deemed it neces-
sary to define nor to regularly monitor them, because
final assembly should not take place before there is acustomer order. This should have prevented finished
products from being stored.
Recurring appeals to cut inventory levels remained
without effect. Instead, purchased component and
finished product inventory levels were steadily growing.
In addition, staff in the shipment area complained about
too small dispatch and storage spaces. The root cause
analysis showed:
. Initially, customers insist on the machines being
delivered as soon as possible. Near completion of
the order, they tend to postpone the delivery date
when they realise that the machine is not needednow, e.g. because of building delays.
. The actual start date of production is delayed
relative to the planned start date. The reasons are
product engineering changes due to changes in
customers requests or design modifications by the
engineering department.
Two issues have to be solved to improve the
interfaces:
1. Placing of orders (information flow): Does the
person who acquires new or altered information
directly benefit or have a quantifiable advantage
from passing it on? Would it be to his/her
disadvantage if he/she did not pass it on?
2. Delivery of orders (material flow): Does the
supplier have a direct, quantifiable benefit from a
timely delivery to his/her successor? Would a late
delivery be to his/her disadvantage?
In our example, a handover deadline was fixed for the
transfer of products to the shipment area, which iswithin the responsibility of the sales department. The
resulting deadlines are realistic, because the calculation
of the order flow includes a capacity check.
. From a production point of view, the sales depart-
ment places fixed orders. The fact that products
are handed over without transferring inventory
responsibility to the sales department is the reason
why the sales department experiences neither an
advantage nor any disadvantage if it fails to pass
on the postponement of customer due dates.
. Likewise, from a sales point of view, the promise
made by production seems to be binding. Butproduction has no fulfilment risk: delivering
Throughput time production order Idle time Idle time
Finishedproducts
... ...
Parts fabrication order I
Assembly order
OP 4
Time
Printing order documentation Input to store
OP 1
Shipment
Parts fabrication order II
Responsibility Production
Start-up
ResponsibilityPurchasing
Purchasing
ResponsibilitySales
(a)
(b)
Purchasedcomponents
Purchasing Production Sales
placesfixed order
deliverson time
placesfixed order
deliverson time
Figure 3. Stumbling block missing responsibility for inventories. (a) Status as planned and (b) actual status.
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goods on time means production is cleared of its
responsibility, without having to worry about
any penalties when orders are completed behind
schedule.
A possible solution may be to add the finished
product store to productions responsibility. This initi-
ates the necessary improvements out of self-interest.
An analysis of the interface between production
and purchasing shows similar results: The required due
date for purchased components is calculated by back-
ward scheduling, before passing it on to the suppliers
with a safety lead time. Production takes no responsi-
bility for inventory levels from the planned start but
only after the order is actually started. This is why
production is merely interested in passing on informa-
tion regarding production orders being pulled ahead
but not about orders postponed. Frequently, the pro-
blem is solved by transferring the responsibility for
material dispatch and material inventory responsibilityto production.
3.4 Stumbling block inconsistent responsibilities
for functions
If the responsibilities for PPC objects, functions and
objectives are defined inconsistently, top management
is obliged to spend a high effort on resolving unneces-
sary disputes as the following example exemplifies.
One of the principal tasks of management is to clearly
define the responsibilities and assign the functions
within a company. It is generally accepted that appro-
priate objectives have to be defined so that responsibil-
ities within the organisation are consistent and therefore
the functions be carried out reliably (Kaplan and
Norton 1996). Unfortunately, reality often rather
reflects the informal organisation, i.e. the power struc-
ture among the persons concerned.
In a company with 300 employees, the right way to
fulfil functions and to accomplish the given objectives
was the subject of heated discussions among the three
departments of dispatch, production and logistics:
Dispatch is responsible for order release, productiontakes on capacity control and sequencing at the
work systems, and logistics is responsible for promising
delivery dates, thus being partially in charge of order
generation. Each department has its own system of
objectives, the priorities differ: The primary objective
of dispatch are short throughput times, the principal
goal of production is a high utilisation, while the top
priority of logistics is a high schedule reliability.
All these objectives were quantified by targets. The
resulting conflicts are illustrated by the following
disputes:
. Dispatch aims to release orders at the latest
possible moment to meet the objective of short
throughput times. Whenever demand is low,
intense debates with production are unavoidable.Production wants orders to be released much
earlier to maintain a high utilisation.
. To meet the objective of high schedule reliability
and ensure that customers receive their products
on time, logistics strives for realistic delivery
promises. It sets the planned start and finish dates
as well as the sequence of orders in accordance with
these promises. As soon as demand rises, however,
the available capacities are not sufficient to keep the
promised delivery dates. Hence, production is
urged to raise capacity. If this is not possible, the
dispatch department is asked to release orders at
an earlier point in time.. Usually, the parties concerned are not able to reach
an agreement. Therefore, often top management is
asked to solve the conflict and decide upon which
orders to release or which to speed up. Necessarily,
the set objectives are missed.
A helpful framework to remove this stumbling
block is Lo ddings (2004) model of manufacturing
control. Its basic idea is to combine the functions of
manufacturing control with the objectives of the
PPC system. Thus, it becomes possible to assess whether
the responsibilities for functions and objectives are
consistently defined. He defines the following fourfunctions (cf. figure 4a):
. Order generation determines the planned input and
output, as well as the planned order sequence.
. Order release determines when orders are released
to the shop floor (actual input).
. Capacity control determines the available capacity
in terms of working time and the number of staff
assigned to work systems, and thus affects the
actual output.
. Sequencing determines the actual sequence of order
processing for a specific work system, and thus
affects schedule reliability.These functions affect the three manipulated variables
input, output and order sequence. The discrepancies
between two manipulated variables lead to the observed
variables of manufacturing control (cf. figure 4b):
. The start deviation results from the difference
between planned input and actual input.
. The WIP level results from the difference between
actual input and actual output.
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. The backlog results from the difference between
planned output and actual output.
. The sequence deviation results from the discre-
pancy between actual and planned sequence.
The observed variables affect the objectives of PPC
described above, i.e. throughput time, WIP level,
utilisation and schedule reliability.
Figure 4b shows the interdependencies connecting
functions, manipulated variables, observed variables
and objectives to each other. The functions define the
manipulated variables, the observed variables resultfrom the discrepancies between two manipulated
variables, and the logistic objectives are determined by
the observed variables.
As a basic principle, conflicts arise when one de-
partment takes the responsibility for a specific ob-
jective when the accomplishment of this objective is
also affected by another department. These conflicts
obviously cannot be resolved by the persons involved.
Figure 5 illustrates how the responsibilities for
objectives and functions are defined by the described
company:
.
The first conflict arises between the production andthe dispatch departments: Although order release
(via actual input) and capacity control (via actual
output) affect the objectives of throughput time
and utilisation, the responsibility for objectives
and functions is not united under one authority.
Accordingly, situations, in which the achievement
of an objective depends on the decisions of the
other department, require a higher authority to
make the final decision.
. The second conflict arises between the production
and the logistics departments: Production affects
the objective of schedule reliability via capacity
control (actual output) and sequencing, whereas
logistics impacts the objective via order generation.
Again the responsibility for objectives and func-
tions is not united under one authority. This inevi-
tably leads to a permanent conflict as described
in the above paragraph and requires a higher
authority to solve each case. For production to
call for an earlier order release to ensure utilisation
even complicates the matter, as a third party, i.e.
dispatch, has to be considered.
To remove this stumbling block the responsibility for
the complete order processing chain must be put into
the same pair of hands. An order management centre
could fulfil this role. Alternatively, it is possible to
divide the order processing chain into sub chains, in
which the responsibilities for objectives and functions
are combined.
3.5 Stumbling block insufficient quality of feedback data
The insufficient quality of feedback data reported in
the following case is a symptom of the lack of
integration of all PPC functions in the tools for planning
and control.
Data quality has recently been identified as one of the
important factors in the configuration of PPC system
(Xu et al. 2002). All purposeful and successful planning
2
13
4
Ordergeneration
Orderrelease
Capacitycontrol
Sequencing
Production
(a) (b)
Disposition
Ordergeneration
Plannedinput
Plannedoutput Backlog
Schedule reliability
Utilization
WIP level
Throughput time
Startdeviation
ActualInput
WIPlevel
Actualoutput
Capacitycontrol
Orderrelease
Plannedsequence
Sequencedeviation
Actualsequence Sequencing
Observed variable
ObjectiveDirection
Manipulated variableFunction
Difference
Figure 4. Model of (a) functions and (b) logistic interdependencies in manufacturing control. Adapted from Lo dding (2004).
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and control depends on a complete, consistent and
current data basis for all planning, control, execution
and performance measurement activities (Wiendahl
et al. 2003a). Besides the production master data, the
production feedback data are especially important for
this purpose:
. Feedback data represent the inputs for the logistic
performance measurement carried out at the end ofa production planning period. Deviations between
the planned and actual values of logistic perfor-
mance measures lead to new control decisions or
the adjustment of target values (see section 3.6).
. For day-to-day business the continuous logistic
performance monitoring is more important.
The deviations between planned and actual order
progress detected by this function have to be
corrected by immediate control measures in order
to make sure that promised or planned due-dates
can be maintained despite order changes or
inevitable disturbances.
There is a range of possible causes for the insufficient
quality of feedback data, of which the IT structure in a
manufacturing company is one of the more significant
reasons. In a survey carried out by the Fraunhofer
Institute for Systems and Innovation Research in 2001,
60% of the companies responded that there is no
hardware connection between the production data
acquisition (PDA) software and the remaining IT
structure (Beckert and Hudetz 2002). A timely and fast
intervention of production control in production is thus
impossible.
At times there is a complex structure of mutual
dependencies that is underlying the symptoms. This is
exemplified by the following example: In the manufac-
turing company considered, the feedback data were
characterised by inconsistencies that resulted from a
substantial delay in recording the data in the PDA
software (only 75% of operations showed a positivethroughput time). However, the actual processing
times matched the standard processing times relatively
accurately. After the introduction of new planning
software the problem disappeared within a period of
six weeks.
A preliminary analysis showed that the feedback data
were only used for the controlling of costs but not for
the ongoing monitoring of the order progress. A second
manual feedback systemlocal inspections by the
foremenprovided the feedback information required
to control the order progress in time. As the feedback
data were not immediately incorporated in the nextproduction plan, the operators did not recognise the
benefit of the plausible and immediate provision of
feedback data. The regular appeals by the production
managers to increase the quality of the feedback data
therefore did not have any effect.
The PPC cycle shown in figure 6 provides a basis for a
detailed analysis of the situation. It consists of a logical
sequence of the activities of production planning and
control. Based on insights from decision theory, the
LogisticsOrder
generation*
Dispath
Production
Throughput time
Utilization
Plannedoutput
Backlog Actualoutput
WIP level
Actualinput
Orderrelease
Dispatch
Capacitycontrol
Production
Sequencing
* promised delivery date
Actualsequence
Sequencedeviation
Plannedsequence
Logistics Schedule reliability
Function
Difference
Objective
Direction
Observed variable
Manipulated variable
Responsibility
Stumbling block
Figure 5. Stumbling block inconsistent responsibilities for functions.
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requirements planning and one for the capacity require-
ments planning and scheduling. Therefore there are two
relevant types of stumbling blocks:
1. Inconsistent parameters: The scheduling parameters
at different levels of aggregation are inconsistent
(e.g. the offset of a manufactured component is
equal to 3 weeks, the sum of the throughput times
of all operations included in the manufacturing
order is equal to 4 weeks).
2. Unrealistic parameters: The values of the schedul-ing parameters are normally not maintained at the
planned values in reality (e.g. the mean planned
throughout time of manufacturing orders is equal
to 5 days whereas the actual mean throughput time
is equal to 7 days).
Manufacturing companies often underestimate the
significance of correct parameter setting. The scheduling
parameters are merely estimated or derived from
historic data. In this way, a tool manufacturer used a
mean planned throughput time value of 27 working days
for scheduling manufacturing orders. This value was
based on the experience of the production foreman.The actual mean value of the throughput time for the
manufacturing orders was equal to 32.5 working days.
The differences between plan and actual mean values
occurred due to the production bottleneck: a long
operation throughput time of a coating process.
The prerequisite for realistic planned values is
the knowledge of the actual values. The lack of a
performance monitoring function constitutes an obvious
stumbling block in this context. The company consid-
ered did lack this function:
. The feedback dataorder master data and due
dateshave to be recorded at all work systems
on the shop floor (step Collect in the PPC cycle
in figure 6). Subsequently, order throughput times
and other logistic performance measures can be
calculated from these.
. Subsequently, logistic performance measurement
has to determine the accuracy of the planningparameters. This is achieved by comparing the
throughput time parameters set for the scheduling
function of the PPC software with the actual values
measured in production. If necessary, the param-
eters have to be adjusted bearing in mind the
logistic objectives (step Learn in the PPC cycle
in figure 6).
. Only the introduction and regular execution of
the PPC cycle guarantees the accuracy of the
throughput time parameters. The procedure
described equally applies to all other PPC planning
parameters.
Adjusting parameters may lead to another stumbling
block: For the purpose of replenishing the finished
products store, the order dispatch function assumed a
throughput time of 27 working days. Backward sched-
uling runs generated the required production orders
based on this assumption. Thus, the difference of
5.5 days between the planned and the actual
throughput time affected the schedule reliability. The
OPOP
Dispatch level123
IA
B
1
2
3
1 3
Throughput time operation 2
OP2
B
Throughput time production order B
Offset dispatch level 2Time
Time
Time
Material requirementsplanning:BOM explosion and
offsetting
Capacity requirementsplanning:throughput scheduling
Function Parameter
Replenishment time/offset dispatch level
Planned orderthroughput time
Planned operationthroughput time
Aggregation level
Product (mean) purchasing time of entirepurchasing process (external/internal)
Dispatch level (BOM level)
may include one or moreproduction orders
Production order (mean) throughput time ofproduction order
equal to replenishment time ifdispatch level includes only oneproduction order
Operation (mean) throughput time of operationof production order
estimated or calculated(inter-operation time + operation time)
Figure 7. Classical scheduling parameters of PPC.
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production was running into backlog. For this reason,
companies have to be aware not to enter the
vicious circle of production control when modifying
planning parameters. The next section explains
how to act correctly when these modifications become
necessary.
3.7 Stumbling block lack of logistic understanding
Due to a lack of logistic understanding, many manufac-
turing companies fail to make the correct connections
between decisions taken in the PPC functions and
their effect on the degree of fulfilment of the logistic
objectives.
How a production system deals with logistic issues
and how this affects planning and control has been the
subject of discussion for some time, especially in view
of the familiar shortcomings of the MRP approach andthe lack of logistic understanding on the part of the
users of PPC.
The vicious circle of production control is a particu-
larly illustrative example of how little is known about
the actual interdependencies between manipulated and
observed variables (cf. figure 8). In the USA this circle
was first described by Mather and Plossl (1978), while
Kettner (1981) and Wiendahl (1995) explained its
consequences to the German audience. The vicious circle
sets out from the mistaken conclusion that schedule
reliability is poor because the planned throughput
times are too short. This is shown in the throughput
diagram in figure 9a. When increasing the values of
the parameters in the backward scheduling run, the
orders will be released to the shop floor much earlier.
As orders cannot be started in the past, the input curve
takes a leap (one-off load surge), making the WIP levels
at the work systems and hence the length of the orderqueues grow (cf. figure 9b). This implies, on average,
longer waiting times and longer throughput times of
orders, along with an increased variation of throughput
times (Wiendahl 2002).
As a result, the schedule reliability is decreasing
and completing important orders on time is only
possible by means of rush orders and costly expediting
exercises. The vicious circle is spiralling upward to
stabilise at a level where the amount of work pieces
stored as work-in-progress exceeds the storage capacity
(Wiendahl 1995).
The correct logistic analysis would be as follows: The
backlog is the actual cause of the due-date deviation of
orders (cf. figure 10a). This backlog cannot be reduced
by increasing the planned throughput times, but by
temporarily increasing capacities or outsourcing work.
Figure 10b shows the effects of this intervention: From
the present day the backlog will gradually decrease.
As a result, adherence to the planned due dates is
improving, and from a certain point in time planned
and actual output are matched. However, such reactions
call for flexible capacities (Wiendahl 2002).
Outsourcing work for some time basically has the
same effect. However, compared to an increase of
capacity the impact will be delayed (cf. figure 10c).
Throughout
times and their
variation
increase
Length of
queues
increasesPlanned
throughput
times are
increased
Load on
work systems
increases
Orders
are released
earlier
Insufficient
delivery
reliability
Figure 8. Stumbling block lack of logistic understandingcauses vicious circle of PPC. Adapted from Plossl and Kettner.
Present day
Actual output
Input
(planned/actual)Planned
output
TimePresent day
Time
Planned
output
New planned
throughput time
(a)
(b)
Load
surge
Planned input
= Actual input
Due-date deviation
(too late)
Planned
throughput time
Planned
throughput time
New actual
throughput time
Due-date deviation
(too late)Actual
output
Workcontent
Workcontent
Actual
throughput time
Figure 9. Inadequate logistic reaction to interrupt viciouscircle of PPC. Throughput diagrams for (a) initial situationand (b) for an increase in planned throughput times.
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A similar effect may be achieved by deferring make-to-stock orders (orders not related to a customer request)
or rejecting customer orders, though the latter might
have a negative effect on the market.
3.8 Stumbling block inadequate logistic guidelines
The stumbling block described below shows the
consequences of a lack of consistency between the
PPC functions and the process, which the functions
are meant to control.
An important instance of wrong PPC parametersetting is the formulation of inadequate logistic guide-
lines. In this case, the planned throughput times entered
in the PPC software are realistic and match the mean
value of the production throughput times. However,
the variation of the actual throughput times is higher
than the planned tolerance. Hence, the available
planning functionality (throughput time planning
based on mean values) and the actual throughput
time performance (high variation of throughput times)
do not conform. This inconsistency shows analogies to
fluid mechanics (Wiendahl 2003b):
. Throughput time planning based on mean values
assumes that the order stream resembles a steadily
flowing river (a so-called laminar flow of orders).
Only when throughput time variation is very low,
schedule reliability is sufficient.
. If the order stream resembles a mountain torrent
(comparable to a turbulent flow of orders),
the focus has to be on the individual order. The
individual planning of throughput time ensures
schedule reliability despite strongly varying
throughput times.
Such a situation allows for two alternatives:
. On the one hand, logistic turbulences might
be inevitable. Individual throughput times are
necessary and the software must be adapted
accordingly.. On the other hand, the steady-river scenario is
feasible. Orders are processed according to the
FIFO rule (or maximum slack). A low variation
of throughput times ensures the planned schedule
reliability.
The relationship between logistic requirements
and logistic capabilities determines the choice of a
logistic guideline. The requirements depend on the
allowed due-date deviation (tolerance requirements),
the demand fluctuation (flexibility requirements) and
the delivery time (speed requirements), cf. figure 11
(Wiendahl et al. 2002, 2003b):
. Tolerance requirements: Is the planning tolerance
set for a value such as throughput time, smaller
than the actual variation?
. Flexibility requirements: Do the fluctuations in
demand exceed capacity flexibility?
. Speed requirements: Do heterogeneous delivery
times require heterogeneous throughput times?
If the requirements exceed the capabilities, it is
necessary to apply individual throughput times for
each order. Practical experience shows that missing one
of the three requirements is sufficient to increase the var-
iation of throughput times. In most cases, this is due
to varying order priorities or sequence changes meant
to avoid setup times. Accordingly, sufficient planning
tolerances, little demand fluctuations and homogeneous
delivery times allow for order throughput times to be
based on mean values. The same applies vice versa:
Heterogeneous delivery times, considerable fluctuations
in demand and tight planning tolerances call for the
individual planning and control of orders.
Planned input= Actual input
Planned Input= Actual input
Present day
Present day
Time
Time
Actual output
Backlog
Planned output= Actual output
Planned output
Backlog
(b)
(a)
TimePresent day
Outsourcing
(c)
Planned input= Actual input
Planned output= Actual output
Workcontent
Workcontent
Workcontent
Backlog
Figure 10. Adequate logistic reactions to interrupt viciouscircle of PPC. (a) Initial situation, (b) temporary increase incapacity and (c) temporary outsourcing.
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Following a flow-oriented guideline makes it easier to
forecast the throughput time and thus to determine the
delivery date. Traditional PPC methods support this
approach, too. However, strong fluctuations in demand
and unforeseen events make it difficult to providecapacity according to need. This is why it places high
demands on flexible capacities and predictive perfor-
mance monitoring to achieve the ideal of a steady
order stream.
4. Configuration of the production planning
and control system
Many industrial companies are dissatisfied with the
degree to which they fulfil their logistic objectives:
throughput times and inventory levels seem to varyuncontrollably; promised due-dates can only be adhered
to by use of costly expediting exercises. For this reason,
there are controversial views about the potential of PPC
software in academia and practice.
The examples of stumbling blocks of PPC presented
above show that the ever-present demand for improved
software with more powerful algorithms is not always
justifiable. Rather, it is the inconsistent configuration
of the aspects of PPC that affects the fulfilment of
logistic objectives. A holistic (re-)configuration of the
PPC system has to consist of the following three stages:
. Initially management has to determine the logistic
strategy, i.e. the logistic performance that it wants
to offer to the customers. This includes the prior-
itisation of external logistic objectives and the
trade-off between internal logistic target values.
Manufacturing companies have to ensure that the
logistic strategy matches their manufacturing vision
which predetermines the design of its production
systems (Riise and Johansen 2003). In fact, compa-
nies should ideally formulate manufacturing and
logistic strategies simultaneously and also design
production systems and the related PPC system in
parallel.
. The technical concept of the PPC system has to be
built on the basis of the logistic strategy. The basiclogistic configuration has to ensure that the
configuration aspects of PPCprocesses, objects,
functions and responsibilitiesare consistent with
each other as well as the achieved prioritisation of
logistic objectives. The selection of suitable produc-
tion planning and control methods and algorithms
facilitates a partially or fully automated materials
and capacity dispatch. The analyses of the stum-
bling blocks of PPC offer instructions on how to
Minimum delivery time
Mean throughput time
Criterion: Time
Planning tolerance
Variation of throughput times
Criterion: Tolerance
Demand fluctuation
Capacity flexibility
Criterion: Quantity
Delivery/lead time
Lead time
Time
Units/day
Capacityflexibility
Demandfluctuation
Distributionof lead times
Quantity
Requireddelivery
time
Variation ofthroughput times
Quantity
Planningtolerance
Figure 11. Criteria for choice of logistic guideline.
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avoid inconsistencies of the configuration aspects
of the PPC system.
. The third stage is the implementation concept of
the PPC system. This includes the selection of
PPC software that is capable of supporting the
technical concept, the setting of all relevant para-
meters in the PPC software and the development ofa suitable implementation strategy that includes
the qualification of all staff. Case studies confirm
the necessity of a role-specific training-on-the-job
implementation (Wiendahl and Westka mper 2004).
It is not sufficient to configure a PPC system once on
implementation. As a rule, changes to the internal and
external situation of the company require a periodic
verification in accordance with the PPC cycle shown in
figure 6. This ensures that the current configuration, the
methods used and the parameters set are still suitable.
Two types of changes can be distinguished:
. Abrupt changes, such as the introduction or with-
drawal of competitive products, the development of
new technologies or other changes to the market
environment are relatively easy to detect. In such
cases, the need for action is obvious. From a logis-
tic perspective there is no need for new methods or
tools for detecting such changes. Timely indicators
of market or technological changes are desirable.
These, however, are research issues for general
management disciplines.
. Creeping changes are much more difficult to detect.
Step-by-step adjustments of market volumes,
delivery or replenishment times hardly attract theattention of those responsible. However, for the
configuration of PPC systems this type of change
is much more critical because it necessitates
the continuous verification and adjustment of the
chosen configuration in parallel to day-to-day
business. It can be compared to the sharpening of
tools that a good craftsman regularly carries out.
5. Conclusions
The discussion of the stumbling blocks presented above
highlights the importance of a holistic configuration of
PPC systems. Although section 4 outlines the main
phases of a methodical PPC configuration process,
a fail-safe procedure has not been developed in
detail yet. However, as focussed questionnaires are a
way of assessing the appropriateness of management
and production system designs (Barnes and
Rowbotham 2003), the following questions can be
recommended as part of a quick-check to assess the
suitability of a chosen configuration. The questions are
separated into five sections:
Objectives and stakeholder interests:
. Have the logistic objectives been defined and are the
objectives consistent? Is their degree of fulfilment
being monitored?. Is someone responsible for the fulfilment of the
objectives?
. Have the logistic objectives been matched to
customer demands and are they consistent with
the performance targets for the employees on all
hierarchical levels (the stakeholders)?
Logistic guideline and PPC methods:
. Does a logistic guideline exist?
. Do the planning and control methods used match
the logistic guideline?
. Is there a mechanism that ensures the consistency
of logistic guideline, logistic positioning and theplanning and control methods used? Is someone
responsible for this mechanism?
Order processing chain and responsibilities:
. Have the separate process steps of the order
processing chain been defined?
. Has the responsibility for each step been assigned?
. Have the interfaces between the responsibilities
been defined unambiguously?
. Do those who have to fulfil the logistic objectives
have an adequate level of authority for making
decisions?
Data quality and parameter setting:
. Is there a mechanism that ensures the accuracy of
master data and feedback data? Is someone
responsible for this mechanism?
. Are the values of the planned throughput times
consistent across all three scheduling levels of the
PPC system (long-range and intermediate-range
planning, and short-term control)?
. Is there a mechanism for continuously checking,
and adapting if necessary, the accuracy of PPC
parameters? Is someone responsible for this
mechanism?Qualification of employees and logistics audit:
. Do all staff involved in the logistics function under-
stand the fundamental interdependencies between
the logistic objectives, the manipulated variables
and the observed variables? Is there a regular
refresh activity?
. Does a logistics audit form part of the quality
management system?
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From a practical point of view, the answers a com-
pany provides to the questions above directly indicate
areas that the company has to improve in order to
achieve a holistic PPC configuration and to avoid the
stumbling blocks described.
From a scientific point of view, further research has to
be carried out in order to adapt the organisational andhuman aspects of existing performance management
theories to the field of production management and
integrate them into the framework for configuring
PPC systems.
Acknowledgements
This article reports on research activities of the pro-
ject Modellbasierte Auftragsmanagement-Gestaltung
(Model-based Configuration of the Order Management
Process) that is funded by the German Research
Foundation (DFG) under registration WI 2670/1.
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Wiendahl, H.-H., Situative Konfiguration des Auftragsmanage-ments im turbulenten Umfeld. Heimsheim, 2002 (Jost-Jetter:Stuttgart).
Wiendahl, H.-H., Roth, N. and Westka mpfer, E., Logisticalpositioning in a turbulent environment. CIRP Ann. Manuf.Tech., 2002, 1(51), 383386.
Wiendahl, H.-H., Marktanforderungen verstehen,Stolpersteine erkennen. Flexible atmende Produktion:Auftragsschwankungen in den Griff bekommen. InManagement Circle Seminar, Munich, 1718September, 2003a.
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Wiers, V.C.S., A case study on the integration of APS andERP in a steel processing plant. Prod. Planning & Control,2002, 6(13), 552560.
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Hans-Hermann Wiendahl studied Industrial Engineering at the Technical University in Berlin.He has worked at the Fraunhofer Institute for Manufacturing Engineering and Automation(IPA) and at the Institute for Industrial Manufacturing and Management (IFF), University ofStuttgart, since 1996 where he held positions as researcher, department manager and now tech-nical manager Order Management. He completed his PhD under the supervision of ProfessorWestka mpfer and is now working on his habilitation thesis. His main research interests are inproduction management, especially PPC, as well as in the selection and implementation of ERPand MES systems. He was responsible for numerous research and industrial projects and haspublished on these subjects extensively.
Gregor von Cieminski holds a degree in Manufacturing Sciences and Engineering from theUniversity of Strathclyde in Glasgow. He is a research assistant at the Institute of ProductionSystems and Logistics (IFA) at the University of Hannover. As a member of the
production management research group his interests are in the fields of logistic modelling ofproduction processes and supply chain management. He has published several articles on thesesubjects in scientific journals and conference proceedings.
Hans-Peter Wiendahlstudied Mechanical Engineering at the Engineering School in Dortmund, atthe RWTH in Aachen and MIT (USA). Under the supervision of Professor Opitz, he completedhis PhD in 1970 and his habilitation thesis in 1972. Until 1979 he was manager of planning andquality at Sulzer Escher Wyss GmbH in Ravensburg before becoming the head of paper machin-ery design for the same company. He became professor and head of the Institute of ProductionSystems and Logistics (IFA) at the University of Hannover in 1979 and held this position until2003. His main research interests are in production management, factory planning and produc-tion systems. He is the author and publisher of numerous books and articles on these subjects.
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