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Automation Strategies - Requirements on the Strategy Process

Automation Strategies
– Requirements on the Strategy Process
M. Winroth1*, K. Säfsten1, J. Stahre2
*Corresponding Author
1Department of Industrial Engineering and Management
School of Engineering, Jönköping University, Sweden
2Department of Product and Production Development
Chalmers University of Technology, Gothenburg, Sweden
Automation is a way to improve competitiveness. Previous studies have shown that best results of automation
decisions are reached if decisions are integrated in the company’s manufacturing strategy. Automation deci-
sions comprise much more than just the very choice to automate and many aspects need to be taken into ac-
count. In this article, we describe new demands that are raised on the strategy process when automation is in-
tegrated in the manufacturing strategy. Furthermore, the implementation of automation strategies calls for a
number of issues to take into consideration.
Automation strategies, manufacturing strategies, process
Automation is often regarded as the main solution to im-
prove efficiency in manufacturing and consequently to im-
prove companies’ competitiveness. This has become im-
portant due to prevailing trends of outsourcing and reloca-
tion to low-cost countries. In order to support the achieve-
ment of a company’s overall objectives, the decisions on
automation need to be in congruence with these objectives.
The fulfillment of objectives is supported by formulation and
implementation of strategies decomposed at different levels
within a company. In this paper, focus is on decisions and
strategies that determine if, and how, automation should be
adopted by a company, i.e. the automation strategies.
Within the manufacturing area, a number of important as-
pects concerning automation are handled. Decisions are
however generally made in absence of more developed
automation strategies. Automation strategies are used in
terms of guidelines for implementation, rather than long-
term plans for appropriate use of automation. Furthermore,
automation strategies are often treated as human factors’
engineering problems, with focus on the human perspective
of automation, such as task allocation [1]. On the other
hand, when automation is treated within Advanced Manu-
facturing Technology (AMT) literature, focus is mainly on
the technical solutions without considering the human as-
pects [2].
Based on previous results, we argue that decisions con-
cerning automation should be treated as one of several
decisions in a manufacturing strategy, i.e. the automation
strategy is part of the functional manufacturing strategy [3].
A manufacturing strategy is a functional strategy, together
with for example marketing, R&D, and accounting strate-
gies. The functional strategies, in co-operation, support the
business strategy of a company [4]. Manufacturing strategy
can be divided into strategy content and strategy process
[5]. Both these areas have been thoroughly investigated in
the manufacturing strategy literature.
Within manufacturing strategy theory, automation deci-
sions are very briefly described and the choice is automa-
tion or not automation. This is however a very simplified
picture. Within the DYNAMO1-project, we have described
the possibility to choose the most suitable level of automa-
tion, LoA, which however calls for an improved decision
support model.
In this article, we show that there is a need for a more
profound view on automation in order to achieve high effi-
ciency in manufacturing and we propose a further devel-
opment of the manufacturing strategy theory in order to
better cover automation tasks. Furthermore, planning and
implementation of automation should start in the traditional
manufacturing strategy field in order to cover all the impor-
tant issues that need to be taken into account.
The results presented in this article are based on theoretical
and empirical studies. A literature review was performed,
surveying to what extent automation strategies are de-
scribed and applied in different areas.
The empirical material was collected through multiple case
studies at a number of companies as well as through a
Delphi study [6]. The case studies consisted of a series of
interviews at companies from different industrial sectors,
such as automotive industry, covering systems integrators
as well as suppliers, furniture industry, metal machining
subcontractors, and suppliers of automated manufacturing
systems. The interviewees were people involved in devel-
opment of the production process, such as managing direc-
tors, production managers, industrial engineers, and main-
tenance personnel.
The Delphi study was carried out by a questionnaire pub-
lished on the Internet. The respondents represented man-
aging directors, production managers, and managers of
engineering departments and the company sizes were
normally between 100 and 500 employees. The companies
represented different sectors of the manufacturing industry.
85 respondents were contacted and they also indicated that
they were willing to participate in the study. The question-
1 DYNAMO – Dynamic Levels of Automation, project fi-
nanced by the Swedish Foundation for Strategic Research
naire was published on the Internet and an e-mail was sent
to the 85 respondents all around Sweden asking them to
log into the website and answer the questionnaire. 62 peo-
ple responded to the survey. Questions asked were about
the view on automation, where are the decisions made and
which facts are they based upon, the use of a special
automation strategy, and also a number of questions deal-
ing with the usefulness of dynamic levels of automation.
Some questions had response alternatives and others were
open. The responses were collected through SPSS Dimen-
sion. The survey was run twice and 44 responded the sec-
ond time. Some new questions were added, but a few ques-
tions were regarded as Delphi questions with the aim to
reach consensus. In the case of Delphi questions, the an-
swers from the previous round were fed back to the re-
spondents, asking them if they wanted to stick with their
previous answers or if they wanted to revise them.
3.1 Level of automation
Automation is often regarded as either an ‘on or off’-
decision, i.e. the system is either considered to be entirely
manual or fully automated. However, in the DYNAMO-
project a more conscious view on automation has been
developed, where the level of automation, LoA, is a matter
of task allocation between the human being and the equip-
ment [7]. The tasks are separated into two categories,
information & control tasks and mechanical tasks. Some
companies talk about semi-automation, which often is
referred to the humans performing some tasks, such as
changing work piece or pushing the button to start each
operation. The LoA-scale gives however a less rigid de-
scription of the issue. Finding the right LoA is very impor-
tant, since an increase in LoA initially gives positive effects
and improved productivity, but gradually the limit of the
company’s capability is reached in different aspects, thus
reducing the system availability.
A pan-European Delphi study has been carried out by the
ManVis project [8]. This survey indicates that experts want
to adopt a less rigid approach to automation, as a contrast
to the often prevailing view that it is a matter of either full
automation or totally manual manufacturing.
The barriers “technical feasibility”, “education and qualifica-
tion”, and “economic viability” doubled between the first
and second rounds. Two thirds of the experts had financial
doubts about the realization of this approach. After the
second round the experts were still skeptic, however
somewhat less than the first round. The interpretation from
the ManVis researchers was that the experts are aware
about the tough prize competition, but on the other hand
they do not consider automation as the most successful
solution to all companies in all situations. The final conclu-
sion on this part of the study is that employment will de-
crease as an outcome of the realization of this statement.
3.2 Part of manufacturing strategy
Winroth et al [9] studied the decision making process at
manufacturing companies and the result shows that the
most important issue is not who makes the decision on
automation but why and the importance of that the decision
is based on a solid ground of facts about the company’s
manufacturing capabilities. Thus, automation is a part of
manufacturing strategies and as such it has implications for
all the decision categories.
The best result of automation efforts is achieved if the
decision is well supported at all levels concerned and that
it is in line with the company’s overall objectives. One good
example is the Swedish spring manufacturer, Lesjöfors,
who had a green-field opportunity a few years ago. Les-
jöfors AB, Sweden, is one of Europe’s leading manufactur-
ers of springs. Their product areas are industrial springs,
strip springs, automotive springs, and gas springs. In year
2003 they had about 400 employees and an annual turn-
over of just over 570 MSEK (2005 figures: 450 employees
and 600 MSEK). The annual growth has been around 15
% for the past ten years. The present plant is fairly new
since the old one was destroyed by fire in year 1996. The
rebuilding of the plant is described in [10]. The main key to
success, according to their own opinion, has been a com-
bination of good industrial engineering and business de-
velopment. Important success factors are considered to be
in-house product development and good control of the
manufacturing process, which includes tool manufacturing
and methods planning. Their competitive priorities are
short development time, flexibility, and reliable deliveries.
The start of the new factory was in fact an opportunity to
create something really well-planned. The analysis work in
connection with the planning of the new plant included
areas such as:
Customer segment, qualifiers and winners
Product mix, processing position
Technical resources and their main characteris-
Production flow analysis
Decision management
The product range was categorized and a product profiling
was performed, where products and markets, manufactur-
ing, and different possible process choices were matched
against each other. The result was that the plant was or-
ganized in four different production flows, which are well-
suited for each category of products. The delivery precision
and reliability have improved considerably compared with
the old plant. Other consequences are reduced lead time,
from four to five weeks to ten days, the productivity has
more than tripled, the capacity doubled, and the production
area has been reduced to half.
The Lesjöfors case is an example when the automation
decisions were linked to the manufacturing strategies,
which in this case led to a successful outcome.
4.1 General on manufacturing strategies
Hill [11] put manufacturing as one of five functional strate-
gies, equally important: research & development, market-
ing, manufacturing, accounting & finance, and human
resources. Manufacturing strategy is formulated as:
‘The way the company uses the manufacturing resources
to gain competition advantages over its competitors’.
Platts et al [12] used another definition of manufacturing
‘Manufacturing strategy is defined by a pattern of deci-
sions, both structural and infrastructural, which determine
the capability of a manufacturing system and specify how it
will operate, in order to meet a set of manufacturing objec-
tives which are consistent with the overall business objec-
A manufacturing strategy should include not only issues
regarding process choice, such as the make-or-buy deci-
sion, process choice, and capacity. Manufacturing strategy
formulation should also embrace infrastructure decisions,
such as work organization, quality assurance, and manu-
facturing planning and control.
According to Hill [11], manufacturing managers also should
stop being so reactive and take a more active part in the
strategic debate. A sign of the attitude towards manufactur-
ing, which was described by Skinner [13], was that the
manufacturing department was not represented in the
board of directors.
Manufacturing strategy is a plan that describes the activi-
ties that are necessary for manufacturing to take in order to
achieve the company aims that have been made. This plan
should comprise both the content of the strategy as well as
the process of formulating and implementing the strategy,
see fig 1 [10].
Figure 1: Manufacturing strategy: content and process [10].
The existing manufacturing strategy is dominated by the
seminal work by Skinner [14]. He identified seven perform-
ance objectives that constitute the guide for making deci-
sions on manufacturing:
Cost, efficiency, productivity
Delivery lead-times
Service, reliability
Flexibility for product change
Flexibility for volume change
The investment required in the production system
These objectives emanate from the expectancies of the
customers, and are included in the content of manufactur-
ing strategy.
4.2 Manufacturing strategy content
Manufacturing strategy content can be described as con-
sisting of two main parts, competitive factors and decision
categories, see table 1 [10]. Competitive factors indicate
on what aspects the company competes on the market.
Some of these factors can be categorized as order winners
or order qualifiers. The winners indicate why customers
would choose us as suppliers, while the qualifiers are nec-
essary to meet in order to be considered as supplier. The
decision categories, on the other hand, outgo from the
company itself and describe how the company performs in
these aspects.
Manufacturing strategy content
Competitive factors Decision categories
Delivery capability
Vertical inte-
planning and
Table 1: Manufacturing strategy content [10].
Manufacturing strategy content has however been the
subject of research for decades and somewhat differently
According to Hill [11], the company should make an analy-
sis of what the market needs and how products qualify and
win orders in the market place. These competitive factors
could be:
Conformance quality
Delivery speed and/or reliability
Demand increases
Color range
Product range
Brand name
Technical support
Manufacturing strategies should make it possible for the
company to reach these objectives. Manufacturing strategy
decisions comprise both structural and infrastructural deci-
sions. The structural issues are:
Choice of alternative processes
Trade-offs embodied in the process choice
Role of inventory in the process configuration
Vertical integration
Make or buy decision
Capacity planning
Infrastructural factors comprise:
Function support
Manufacturing planning and control systems
Quality assurance and control
Manufacturing systems engineering
Clerical procedures
Compensation agreements
Work structuring
Organizational structure
The formulation and implementation of these strategies is
called manufacturing strategy process, which is further
described in the next section.
4.3 Manufacturing strategy process
Often people of today talk about being world-class in their
manufacturing performance, which in fact means perform-
ing in accordance with best practice in the field of action.
Roth et. al. [15] declared: ‘World-class competitors have
clearly thought out and defined manufacturing strategies
and plans. Their strategies are congruent with the overall
business goals and objectives and are enough to adapt to
change. However, the real winners are those best in strat-
egy implementation.’
Manufacturing strategy process is concerned with the
procedures that can be used to formulate the manufactur-
ing strategies that should be adopted and how they should
be implemented. The process and content must however
communicate, since the content has a direct impact on the
process of strategy formulation. The reason is that content
creates a number of constraints on the process and the
preferences of which content areas are regarded particu-
larly important rules the exact nature of process [16].
Hill [11] presented the formulation of manufacturing strat-
egy as a process consisting of a series of sequential steps.
He proposed a manufacturing strategy framework with the
following five stages:
Defining corporate objectives
Determining marketing strategies
Identifying how products win orders
Establishing the most appropriate mode of manu-
facture for the sets of products, i.e. process
Determining the appropriate manufacturing infra-
structure to support production.
This approach emerges from the market demands and is
called market based. Another way of attacking the problem
is to start from the manufacturing capabilities and deter-
mine the company resources [10]. Through this resource
based view it becomes clearer what the company can offer
the market.
An iterative approach, where the market requirements are
matched against the manufacturing capabilities, would be
an ideal solution. Platts and Gregory [12] presented a
framework for manufacturing audits, see figure 2. The
manufacturing capabilities are estimated and if the profiles
show mismatches action, plans can be formulated to take
corrective actions.
Figure 2: A framework for manufacturing audit [12].
A similar framework was presented by Miltenburg [17],
where he also added the choice of manufacturing system
layout. This framework was further developed and tested
at small and medium sized manufacturing enterprises –
SMMEs, by Säfsten and Winroth [18].
These frameworks were applied generally on manufactur-
ing strategy and its linkage to design of manufacturing
system. If we regard automation strategies as included in
the manufacturing strategy, a focus on automation calls for
further development of the strategy process. This is further
described in the next chapter.
5.1 Formulation
Existing models for manufacturing strategy formulation, ex.
[11] and [17], adopt an analytic approach and the starting
point is always in the corporate and market objectives. This
is necessary, but there has to be a continuous loop where
the operational capabilities and performance form input to
the formulation of the principal objectives. Platts and Greg-
ory [12] add this dimension to the previous models when
they include a profiling and prioritization of the relative
competitive performance, which indicates possible gaps for
driving improvements. These different models do however
mainly focus on the overall performance of corporate func-
tions and not on the link between choosing a certain tech-
nological complexity and the capability of employees and
According to Säfsten et al [10], process choice, including
choice of technology level and automation, is one of the
eight strategic decision areas that are important for the
success of a manufacturing organization. All these decision
areas are however closely interlinked, consequently leading
to trade-offs, i.e. it is impossible to achieve the highest
performance in all areas simultaneously and the optimum
could be a reduction of the performance in some of the
areas. Since the areas are interlinked, e.g. the choice of a
certain level of automation calls for an identified skill level of
personnel, the component supply needs to be carried out in
a certain manner, and quality management needs to be
considered etc.
Span of Process
Human Resources
Control Policies
New Products
In the next section, the implementation of automation strat-
egy is discussed.
5.2 Implementation
Implementation of automation strategies concerns imple-
mentation of automation according to the level of automa-
tion and improvement of detected capabilities. It is how-
ever important that the company, during the implementa-
tion phase, always keeps in mind the objectives that drive
the automation. Once again we emphasize the need for a
continuous loop between corporate objectives and opera-
tional performance.
A technological approach focused on the manufacturing
processes is adopted by Groover [19], who describes the
USA-principle which indicates the importance of studying
the manufacturing processes prior to implementing auto-
1. Understand the existing process.
2. Simplify the process.
3. Automate the process.
Often the result after the simplification phase is that auto-
mation is unnecessary since the manufacturing operation
is better or cheaper performed manually.
A list of ten strategies for carrying out improvements of
productivity, quality, or other measure of performance, was
presented by [19]. They are called strategies for automa-
tion and production systems and they are useful both for
automation projects and for other improvement work.
1. Specialization of operations. This strategy uses special-
purpose equipment for carries out a single operation with
high efficiency. It could also imply labor specialization in
order to improve the productivity of manual operations.
2. Combined operations. Many production tasks involve a
large number of processing operations. By combining
operations and making it possible to perform several op-
erations in one machine, the routing problems can be
minimized. Another achievement is that the setting-up of
tools and work pieces can be kept to a minimum. The
overall manufacturing lead time will be reduced as a con-
sequence of this strategy.
3. Simultaneous operations. Investigate the possibility of
performing two or more processing operations simultane-
ously on the same work part at one workstation. This will
reduce the total processing time.
4. Integration of operations. The possibility to link several
workstations together by using automated handling equip-
ment for transferring work pieces between different sta-
tions should be explored. This reduces the number of
separate machines through which the product must be
scheduled. The overall output of the system will thus be
increased, since several parts can be processed simulta-
5. Increased flexibility. The main purpose of this strategy is
to reduce setup time and programming time for the manu-
facturing equipment. This is achieved by using the same
equipment for many different work pieces. This leads to
higher utilization of the equipment and is applicable when
there is a large variety of products which normally leads to
a job shop layout.
6. Improved material handling and storage. Introducing
automated material handling and storage systems is often
a good effort that can lead to reduction of work-in-process
and shortening manufacturing lead time.
7. On-line inspection. Quality inspection after the process,
which is normally the case, leads to that the process is
already finished. Integrating inspection into the process
itself enables taking corrective actions directly as the proc-
ess is being performed. It leads to reduced scrap rate and
improvement of the overall product quality.
8. Process control and optimization. Different control
schemes help to operate processes and related equip-
ment. Process times are reduced and product quality im-
proved. One example of a commonly used tool is statistical
process control, SPC.
9. Plant operations control. Control at the plant level aims
at managing and coordinating aggregate operations more
efficiently. This usually implies a considerable use of com-
puter networking and links to enterprise resource planning
systems, ERP.
10. Computer-integrated manufacturing (CIM). If the previ-
ous strategy is further developed, we reach an integration
of factory operations and engineering design and business
functions. Computer applications are widely used; including
data bases and enterprise wide computer networks.
These strategies form a checklist that can help companies
in their automation projects. Multiple strategies may apply
for most situations. The most important issue is however to
decide what level of automation is suitable depending on
the existing situation and conditions.
Groover [19] also presents a specific automation migration
strategy, which describes the implementation of automa-
tion during the various product lifecycle phases, figure 3.
The purpose is to shorten the time for introducing the
product to the market. Thus, during the first phase the
manufacturing is performed manually. The tooling and
equipment is fairly low cost. If the product is a hit on the
market, each cell can be transformed into automated cells
and, during the last phase, the high volume is met by con-
necting the stations together into a continuous flow with
highly integrated automated cells.
The advantages of the automation migration strategy of fig
3 are mainly:
Short product introduction times.
Gradual introduction of automation.
It allows the company to postpone high invest-
ment cost when introducing products with an un-
certain market forecast.
Product demand
Phase 1 Phase 2 Phase 3 Time
Automated integrated
Connected stations
Figure 3: A typical automation migration strategy, adopted
from [19].
This model suits however not all situations in manufactur-
ing companies. It is suitable only to manufacturing of prod-
ucts with very long product life cycles, where it is worth the
effort to change the way of producing. It is also necessary
to prepare the product for automated production or other-
wise the product has to be revised.
The next chapter presents some of the empirical findings
relevant to automation strategies.
The Delphi-study that was carried out among Swedish
SMEs gave various results. Most companies emphasized
the importance of having an automation strategy that forms
the base for investing in new production equipment.
The driving forces for automation are mainly productivity,
with better financial outcome as the main objective, and
ergonomic reasons. Improved competitiveness, as a con-
sequence of cost reductions, is regarded highly important.
Another important issue is the possibility to increase pro-
duction volumes on the same premises.
The most important problems with automation were:
Adapting the product to automation
The high number of different products and vari-
Problems to get the money back from the invest-
The lack of competence at shop floor level
The respondents considered automation to be not suitable
in the following cases:
When ramping up manufacturing of new products
During manufacturing of a large variety of prod-
ucts and variants in small volumes
If the product life cycle is very short
If the product needs e.g. visual inspection
On the question about when it would be relevant to take
variable levels of automation into consideration, the re-
spondents answered:
To increase flexibility
To facilitate ramp-ups and change-overs
To handle disturbances
To improve system robustness
To reduce production cost
To improve productivity
Finally, the question about on what grounds automation
decisions should be made got the following answers:
On financial grounds
Based on demands for productivity improvement
On quality demands
On working environment demands
On production capacity demands
In the DYNAMO-project, a large number of interviews and
case studies at the companies that are partners in the
project have been carried out. The most striking finding is
the very different opinion about automation and also the
use of variable or dynamic levels of automation. It seems
like the companies that act as subcontractors to many
customers, thus having more general purpose equipment,
are more willing to accept that it is possible to change the
level of automation. The companies that invest large
amounts of money into highly specialized equipment in-
cluding tooling and fixtures are more reluctant to the possi-
bilities. They plan for a specific level of automation from
the start and everything is locked until they change product
or product platform. This is mostly applicable to automation
of the mechanical tasks. It may be more interesting to be
able to change the level of automation of the information &
control tasks. Possibility to override the automatic control
system during ramp-up could be applicable. The compa-
nies were, however, not aware of this view since they
mostly discuss and think on automation as physical task
Another opinion that was put forward was that increasing
the level of automation is not always to prefer. If the avail-
ability is optimum, increasing the level of automation may
make the system more vulnerable, thus reducing the avail-
ability and up-time.
Other companies have the straightforward automation
strategy to automate as much as possible, no matter the
cost. A large company within the consumer electronics
business invested in highly automated final assembly lines.
The industrial engineers did not even have to justify the
investment financially. The company did not have enough
competence to install and start production, so they hired
consultants for a long period of time. The problems still
remained and after a short while the equipment was re-
moved and the company went back to manual assembly.
This is an example where the company’s capabilities did
not correspond to the complexity of the new system.
Many companies make very large investments in highly
sophisticated and automatic manufacturing systems, with-
out knowing if the investment is suitable, or even possible.
With a better decision support tool, companies could get a
better match between possible and desirable investments.
They could also see when it is time to abandon continuous
improvement of the existing equipment and go for larger
changes of their operations.
7.1 Content
It has been noticed during several case studies that auto-
mation involves more than just the process technology.
Other functions, such as quality management, human
resources, supply, capacity, facilities, and organization, are
affected by such a decision. On the other hand they also
form the input when making the decision. Thus, automation
strategy is a part of the manufacturing strategy and a profil-
ing of the capabilities is desirable to detect mismatches
and identify suitable changes.
7.2 Process
The formulation of the automation strategy needs to be
designed as a continuous loop covering market require-
ments, existing equipment and routines as well as other
manufacturing capabilities of the company.
The conditions for automation strategy implementation
vary depending on what kind of manufacturing process the
company has. We have detected major differences be-
tween companies with highly advanced continuous produc-
tion lines, for a limited number of products and variants,
and companies with batch flow layouts, producing a large
product variety in smaller volumes with more general pur-
pose machines. The continuous lines need to be run in full
speed almost from the beginning since balancing does not
match at lower speeds. This makes simulation and off-line
testing very important tools. A discontinuous flow makes it
possible to test each cell isolated from the rest of the pro-
duction, which limits the disturbances on the output.
The results from the DYNAMO project need to be further
developed into useful tools for practitioners involved in
automation projects. We do, however, see a large potential
for industrial purposes if companies can adopt a less rigid
view on automation.
This research is funded by the Swedish Foundation for
Strategic Research in the project DYNAMO – Dynamic
Level of Automation. Research partners are Chalmers
University of Technology, School of Engineering at
Jönköping University, and The Swedish Institute for Indus-
trial Research – IVF. A total of eight manufacturing com-
panies are partners in the project and they represent large
companies and SMEs as well as different industrial sectors
such as the wood and furniture industry, industrial automa-
tion, metal machining, and automotive industry.
[1] Sheridan, T.B., 2002, Humans and Automation: Sys-
tem Design and Research Issues, Wiley series in
System Engineering and Management.
[2] Hoffmann, C., Orr, S., 2005, Advanced Manufacturing
Technology Adoption – The German experience,
Technovation, Vol. 25, pp. 711-724.
[3] Säfsten, K., Winroth, M., Stahre, J, 2005, The content
and process of automation strategies, 18th Interna-
tional Conference on Production Research, July 31. –
August 4., Salerno, Italy.
[4] Hayes, R.H., Wheelwright, S.C., 1984, Restoring Our
Competitive Edge: Competing Through Manufactur-
ing, Wiley, NY, USA.
[5] Swink, M., Way, M.H., 1995, Manufacturing Strategy:
Propositions, current research, renewed directions,
International Journal of Operations & Production
Management 15(1), 4-26.
[6] Linstone, H.A., Turoff, M., 2002, The Delphi Method –
Techniques and Applications, New Jersey Institute of
Technology, web-version downloaded from, first printed in
[7] Granell, V., Frohm, J., Winroth, M., 2006, Controlling
Levels of Automation – A model for identifying manu-
facturing parameters, 9th IFAC Symposium on Auto-
mated Systems Based on Human Skill and Knowl-
edge, Nancy, France, May 22.-24.
[8] ManVis Report No 3, 2005, Manufacturing Visions –
Integrating Diverse Perspectives into Pan-European
Foresight (ManVis), Delphi Interpretation Report, De-
liverable D15, contract no NMP2-CT-2003-507139-
[9] Winroth, M., Säfsten, K., Stahre, J., 2006, Automa-
tion strategies – existing theory or ad hoc decisions?
International Journal of Manufacturing Technology
and Manufacturing, Forhcoming.
[10] Bellgran, M., Säfsten, K., 2005, Produktionsutveck-
ling – Utveckling och drift av produktionssystem, Stu-
dentlitteratur, Lund, Sweden (in Swedish).
[11] Hill, T.J., 1994, Manufacturing strategy: Text and
Cases, Irwin, Homewood, IL, USA.
[12] Platts, K.W., Gregory, M.J., 1992, A manufacturing
audit approach to strategy formulation, in Voss, C.A.
(ed.) Manufacturing strategy: Process and content,
Chapman & Hall, London, UK.
[13] Skinner, W., 1969, Manufacturing – Missing link in
corporate strategy, Harvard Business Review, May-
[14] Skinner, W., 1992, Missing the links in manufacturing
strategy, in Voss, C.A. (ed.) Manufacturing strategy:
Process and content, Chapman & Hall, London, UK.
[15] Roth, A.V., Giffi, C.A., Seal, G.M., 1992, Operating
strategies for the 1990:s elements comprising world-
class manufacturing, in Voss, C.A. (ed.) Manufactur-
ing strategy: Process and content, Chapman & Hall,
London, UK, pp. 133-165.
[16] Slack, N., Lewis, M., 2002, Operations Strategy,
Prentice Hall, UK.
[17] Miltenburg, J., 1995, Manufacturing Strategy – How
to formulate and implement a winning plan, Productiv-
ity Press, Portland, Oregon, USA.
[18] Säfsten, K., Winroth, M., 2002, Analysis of the con-
gruence between manufacturing strategy and produc-
tion system in SMME, Computers in Industry, No 49,
pp. 91-106.
[19] Groover, M.P., 2001, Automation, Production Sys-
tems, and Computer-Integrated Manufacturing, 2nd
ed, Prentice Hall, Upper Saddle River, NJ, USA.
... Automation can be regarded as either fully automated or full manual, and it is aimed at acquisition of value addition, better process throughputs and increased productivity [15,16]. Similarly, the competitive approach of reducing the unit cost of a product agitated the need for a faster production pace, and this is through automation of crucial tasks [17]. ...
... On the contrary, automation considered not to be suitable in the following cases: when ramping up manufacturing of new products, manufacturing of a large variety of products and variants in small volumes, very short product life cycle and requisites of product e.g. visual inspection [16]. ...
... The best of automation efforts are realized if they only conform to the industry's goals and objectives. The main key to success is to integrate good organizational structure and manufacturing tools [16]. If the main goal is to reduce production cost, then the concern will only be to automate with a mere implementation strategy on human labour such as task allocation. ...
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Quality of sugar from the industry is dependent on the appropriateness of the advanced automation technique that is employed for the extraction of sucrose concentration (brix) from the sugarcane and also, monitoring and regulation of process parameters like the amount of imbibition water, amount of suspended solids, temperature, pH and the leanness of automation technique that determines an optimum extraction. This in turn affects the cost of sugar production. Thus, the need to determine the best automation approach of attaining optimum sucrose concentrations in juice extracts. To achieve this, a comparative analysis of three different levels of automation found in Kenyan Sugar industries was carried out in a case company to assess their impact on the purity of juice extracted and hence the quality of sugar produced. It was found that, levels of automation (LoA) 6 and 5 recorded the highest brix of 96% compared to 75% recorded by level 4. Also, LoA 6 allowed adjustments to achieve improved process balance of juice brix, bagasse moisture, extraction and energy consumption in juice evaporation. Therefore, LoA 6 also called six-sigma automation should be adopted in the sugar industry for optimum sugar quality and reduced cost of production.
... Automatisering blir ofte sett på som den viktigste løsningen for å forbedre effektiviteten i industrien (Winroth et al, 2006) og potensielt forbedre konkurranseevnen til industribedrifter (Säfsten et al., 2007). Videre ansees automatisering som en enten «på» eller «av» -beslutning, altså at systemet er enten fullstendig manuelt eller helautomatisk (Winroth et al, 2006 Den knyttes også opp mot en høyere produksjonsrate, høyere nivå av produktivitet og en større verdi tilføring (Orr, 1997). ...
... Automatisering blir ofte sett på som den viktigste løsningen for å forbedre effektiviteten i industrien (Winroth et al, 2006) og potensielt forbedre konkurranseevnen til industribedrifter (Säfsten et al., 2007). Videre ansees automatisering som en enten «på» eller «av» -beslutning, altså at systemet er enten fullstendig manuelt eller helautomatisk (Winroth et al, 2006 Den knyttes også opp mot en høyere produksjonsrate, høyere nivå av produktivitet og en større verdi tilføring (Orr, 1997). På den andre siden gjør prispresset på produktene i markedet at produksjonen må oppnå en høyere takt som vanskelig kan oppnås uten å automatisere noen prosesser (Ribeiro and Barata, 2011). ...
... Vi velger å se dette i sammenheng med Orr's (1997) oppdagelse om at mange bedrifter kan benytte kontinuerlig opplaering av ansatte under gjennomføringen av automatisering for å mer effektivt justere de mot teknologi (Orr, 1997;Winroth et al., 2006). Dette kan blant annet gjøres vha. ...
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Looking at a local injection moulding producer in Trondheim, Norway, and how they can become more efficient through LEAN inspired methods and automation via robotics. Conclusions about robotics vs. traditional workers, and layout of production facilities etc.
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Continuous improvement encompasses identification of threats and opportunities, proposal and implementation of the solutions, and lastly monitoring and evaluation of sugar production. Cane juice extraction in Sugar production is achieved through two techniques namely milling tandem or diffuser. In Kenya, out of the 12 sugar industries available, the means of juice extraction in 11 industries is by milling tandems. Only one industries has both diffuser and milling tandems with conventional automation. However, sugar productivity from these industries is 85% which is lower than 92% recommended worldwide. The cost of production of 46,000/MT is twice that of small economy countries like Swaziland and Uganda. This can be attributed to the type of juice extraction technique which will determine the rate of sugar production. It is therefore aimed to assess the impact of a diffuser which employs Six-Sigma automation on the improvement of the production. A case company having both diffusion and milling was selected and operations compared. It was found that 98.5% of sugar extraction from diffuser with 6-σ automation can be achieved compared to 80% in mills and a production rate of 360 T/h compared to 100 T/h in mills. However, extensive cane preparation has to be achieved.
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Conference Paper
A production system must reflect a company's manufacturing strategy and the chosen competitive priorities. Tools to assess the congruence between the manufacturing strategy and the production system can hence support the companies' competitive position. In this paper, the usability of an analysis model suggested by Miltenburg [How to Formulate and Implement a Winning Plan, Productivity Press, Portland, OR, 1995], aiming at mapping manufacturing strategy and production system, is investigated. The usefulness of the analysis model is investigated in terms of how easy it is to use and in terms of the obtained results. The investigation is performed by means of empirical studies in two medium sized manufacturing companies. The result is that the model seems to be useful in the sense that, if knowledge about the underlying principles in the analysis model is at hand, it is possible to investigate the congruence between a manufacturing strategy and a production system. It is, however, believed that the analysis model needs some further development to be considered an easy to use tool, e.g. for a SMME production manager.
The decision process that organisations utilise when evaluating technology investment opportunities is a complex and even political process; however, the correct decision can provide the organisation with considerable operational and competitive benefits. The research presented in this paper presents the findings of a postal survey of the benefits provided by technology investments to large German manufacturers. It was found that only where middle management generated the idea for the advanced manufacturing technology (AMT) investment was success in that investment significantly more likely. Respondents who established a project team to plan the technology proposal, regardless of the department which generated the ideas for technology investment, were not significantly associated with a greater likelihood for success.The respondents typically took between 3 and 12 months before making the final decision to invest, irrespective of the department generating the idea for the AMT, and a further 6 months to implement the AMT. Respondents who utilised a discounted cashflow analysis took significantly longer to make the final decision to invest. The greatest number of manufacturing outcomes of significantly higher importance was identified for respondents where Engineering, IT or R&D generated the AMT ideas. It was also determined that the respondents most frequently considered AMT investments in computer hardware or software and technical training for process workers to be necessary at the time of considering the investment. Middle management were found to be significantly more concerned than managers on other levels about opposition of workers to the AMT, while the process workers were significantly more concerned about interruptions to the process during installation.
A substantial number of propositions have been made over the last 20 years regarding the content of manufacturing strategy and the process of strategy development and implementation. Although many of the propositions have been well received, few have been rigorously tested via empirical methods. Reviews empirical research efforts to date in order to assess the effectiveness of current research directions and methodologies in evaluating earlier propositions. Discusses strengths, weaknesses and directions for future research in each area of manufacturing strategy.
This problem solver offers a wealth of remedies for American industry's neglect of competitive manufacturing strategies and its resulting loss of productivity. Drawing upon the example of world-class and foreign manufacturers, the book illustrates what American industry must do in terms of manufacturing capability to regain a preeminent spot in the marketplace.