System Dynamics '95 — Volume II
Understanding Strategy for a Manufacturing Based Learning
Organization in Transition in the Twenty First Century
Hamza Musaphir
University of Manitoba
Department of Mechanical and Industrial Engineering
Winnipeg, Manitoba.
Canada. R3T 2N2
Tel. 204-831-2615
Fac. 204-888-2951
Ostap Hawaleshka
Executive Director of Ukrain Technical Institute
Kiev, Ukrain
ABSTRACT
Manufacturing strategy offers a means for integrating operations management decisions and
linking them with the firm’s business strategy to attain a competitive position. The goal of this
paper is to develop a model using Systems Thinking which can be utilized to better understand
what constitutes manufacturing strategy, and why certain decision choices better mesh and
lead to a superior competitive position. The model focuses on understanding linkages among
operation management decisions which will include the decision areas of process, materials
management, quality, workforce management, and maintenance.
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THE NEED FOR MORE RESEARCH
There are firms such as General Electric, Chrysler, Outboard Marine, and Allen-Bradley that
are adopting the integrative approach. The recent successes in the plants owned by these U.S.
companies and Japanese companies (Wheelwright 1981) are an evidence of how an integrated
approach can lead to competitive success. The integrative approach subscribes to the argument
that manufacturing decisions must mesh with each other and with the firm’s business
strategy. The effectiveness of an integrative approach in some of the examples cited above is
one reason for conducting research on how to integrate actions in manufacturing. If theories
are made available, then manufacturing firms may be better able to achieve superior
performances more consistently.
A lack of knowledge or explanation of relationship among widely disparate and
dispersed elements of production in a firm has been cited as one of the key reasons why
manufacturing slipped to being a millstone rather than a source of competitive advantage
(Skinner 1978 and Hill 1985). Research scholars must bear blame for this lack of knowledge
base. A theory about integrating actions in manufacturing is needed. Such a theory will help
managers transform manufacturing from a millstone to a source of competitive advantage. In
essence there is a need to develop theory to guide systematic planning and implementation of
manufacturing strategy to bring manufacturing to the level of other function’s as being a
source of competitive advantage.
Developing a theory on integrating actions in manufacturing means understanding the
relationships among operations management decisions. Porter (Porter 1980) suggests that
firms are better able to develop sustainable competitive positions if the decisions mesh with
each other. The soundness of Porter’s argument is one reason for studying linkages in
manufacturing.
Up until recently, the majority of research on manufacturing strategy, such as that by
Abernathy (1976) and Skinner (1969, 1974), has mainly relied on case studies. Recently there
have been some empirical studies (Miller et al. 1983, 1984, 1985, 1986; Hayes and Clark 1985;
Roth et al. 1987; and DeMeyer et al. 1987) that have statistically analyzed data collected from
many organizations. There also have been some studies that have employed analytical (Cohen
and Lee 1985) analysis to gain insight into the linkages in manufacturing. A significant
weakness of the above mentioned research is that most of the research was conducted from a
disjunctive point of view rather than of a holistic nature.
RESEARCH METHOD OVERVIEW
This paper utilizes system dynamics to develop a model that can be used to better understand
relationships among the decision areas of Process, Quality, Materials Management,
Maintenance and Workforce Management in manufacturing strategy. The simulation
language used for this model is STELLA.
According to the Executive Summary of the 1987 North American Manufacturing
Futures Survey; competitive priorities based on quality, and delivery time will be the theme of
the nineties. Delivery time denotes the elapse time between receiving a customer's order and
filling it. Speed of delivery is viewed as a means of achieving superior quality (Hayes and
Schemmer 1978). Krajewski and Ritzman (1987) considers fast delivery as an independent
basis of gaining competitive advantage.
A key measure of delivery time is the cycle time for a product. Cycle time is defined as
the time required to manufacture one part or product unit. Cycle time is being proposed as the
measure to examine relationships among and within the decision areas of Process, Quality,
Material Management, Work Force Management and Maintenance.
In formulating the model, two distinct avenues were pursed in selecting variables for
the decision areas under examination. Variables for the decision areas of Process, Quality, and
Materials Management were deductively derived from the existing knowledge base. Since there
seems to have been little published effort to date, if any, to relate workforce management and
maintenance to manufacturing strategy, the variables identified in the model are of an
exploratory nature. Case studies with manufacturing firms and survey analysis were the
research methodologies utilized to propose the variables for workforce management and
maintenance.
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System Dynamics '95 — Volume II
INFLUENCE DAIGRAMS FOR DECISION AREAS
As previously mentioned, time based competitiveness was rated highly as a competitive
priority for businesses in the nineties. To be effective in time-based competition, managers
must carefully define steps and time involved in processing customer orders. Next, they must
critically analyze each step to see whether production time can be shortened without
compromising the quality of the product or service. Significant time reduction in operations
can often be achieved by changing the way current. technologies are used, by turning to
automation, by identifying and reducing non-value added time, by effective maintenance and
by effective management of workforce. With these thoughts in mind, the following sections
describe the variables identified for the decision areas of process, quality, material
management, workforce management and maintenance.
The next section illustrates an influence diagram of the Decision Areas of
Manufacturing Strategy that are being examined. Following are influence diagrams of the
Decision Areas of Process, Quality and Materials Management that were deductively derieved
from the existing knowledge base on manufacturing strategy. A brief description explaining
the variables identified for Workforce Management and Maintenance follows since they are of
an exploratory nature.
Competitive
Priorities
vA
Process
Delivery Workforce Maintenance
Time Management Y
Quality
Cycle fF
Time a“
——~___ Materials
Management
Figure 1. Influence diagram of Decision Areas of Manufacturing Strategy
WORK STATIONS
FOR JOB SHOPS “Sq
vos,
SHOP
PROCESS
PRODUCT ge NON-VALUE AODED T:ME
FOCUS QUE TO PROCESS TYPE,
CONTINUOUS
Bo
Figure 2. Influence diagram of the Decision Area of Process
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ACCEPTABLE
}
‘OaY STORES
|
PRODUCTION
customer
To vENOOR
DELAY DUE TO
LACK OF MATERIALS
BUYER WORKS WITH
PAATS SUPPLIED VENDOR ON QUALITY
BY VENDOR issues
A SA neouce
oeFecTs
vewooa
+ ronitor ogezerive
PARTS SUPPLIED
Figure 3. Influence diagram of the Decision Area of Materials Management
FINISH = QUALITY ~g——— Rework
proouer e —
FINAL
gay MS SHIPTO
Fini5H#=9 50008 7 custome
inveNToRY
“A ea
PACKAGED
cus
Figure 4. Influence diagram of the Decision Area of Quality
MAINTENANCE
Maintaining production capacity, regardless of the degree of capital intensity is essential to a
firm's long term growth and profitability. Maintenance managers must continually find ways
to ensure adequate output performance while minimizing maintenance activity cost and
system failure costs. Maintenance activity costs are the costs incurred in attempting to
maintain the desired output rate. System failure costs are the costs incurred when the system
fails to perform at the desired output range. System failures never happen at a “good time”,
typically require emergency measures, and can be extremely costly. Hundreds of workers on a
production line can be idled, along with expensive equipment, and customer shipments
delayed just because one machine fails.
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System Dynamics '95 — Volume IT
As previously mentioned, cycle time is a key measure of delivery time which an
increasing number of companies are using as a basis for gaining competitive advantage. The
time required by machinery to process a product significantly affects cycle time. Based on the
case studies completed for this paper, the efficiency of a preventative maintenance program,
work order efficiency, machine operator's involvement and levels of automation.are being
proposed as variables that can significantly affect the machine time to process a product.
Preventative Maintenance involves a pattern of routine inspections and servicing at
regular intervals. These activities are intended to detect potential failure conditions and take
steps to prevent their occurrence. Traditionally, preventative maintenance programs are set up
to carry out equipment maintenance, on a regular calendar schedule or by hours of operation,
based on the manufacturer's recommendations. These recommendations are usually based on
an average operating environment. Routine inspections often highlight problems that may
cause equipment to operate below its normal efficiency, thereby, affecting process time.
The variables work reduction factor and work induced factor are proposed to examine
the effects of a preventative maintenance system on generating maintenance tasks.
Hypothetically, maintenance tasks (sometimes refer to as machine repair activities) should
decrease if scheduled preventative maintenance work orders are completed as per schedule and
vice-versa.
In this study, maintenance tasks, also refer to as work requests are grouped into four
major categories: emergency, operations, scheduled, and shutdown. The emergency tasks
(usually unplanned critical production machine breakdown) are usually performed when the
equipment fails to operate, often at a premium cost. Operation tasks are those that are
generated from the daily operations of the plant. Scheduled tasks are maintenance tasks that
are scheduled to be completed sometime in the future due to lack of resources or materials.
Shutdown tasks involve work that can only be completed during plant shutdowns.
Training hours is proposed as a variable to examine the effects of motivation and the
effectiveness on backlog hours. Theoretically, productivity increases are equated to training
hours to describe a potential increase in productivity. It is assumed that when a worker
receives training there will inevitably be some form of improvement.
Resources represent the available number of tradesman. If this number changes for
whatever reasons (retirement, fired or better opportunity) then there is automatic hiring to
satisfy the original amount of workers. Resource hours are determined by the number of
workers multiplied by five days per week and eight hours per day. Available hours which
determine the available hours that can be assigned to completing work requests or
preventative maintenance work orders is calculated from resource hours plus any allowable
overtime minus any hours dedicated to training.
Improperly operated equipment may not only cause breakdowns but also can
significantly affect machining time for a process. Therefore, poorly operated machinery could
possibly have a compounding detrimental affect on cycle time. Not only is the cycle time
increased from an increase in machining time but also machine breakdowns which increases
the need for maintenance repairs causing a reduction in machine availability for production;
hence lengthening the time it takes to manufacture a product. It is being proposed in this study
that training procedures for operators and their attitudes can significantly affect the way in
which the equipment is operated.
Since technology is changing so rapidly, it is more important than ever for operations
managers to make intelligent, informed decisions about automation. Many new opportunities
are the result of advances in computer technology. Deciding whether to take advantage of such
opportunities can significantly affect cycle time and the work force. Cycle time may decrease
dramatically with automation. Automation however, affects jobs at all levels. Some are
eliminated, some are upgraded and some are downgraded. Even where the ‘changes resulting
from automation are small, people related issues become large. For example, poorly trained
and poorly motivated workers can cause enormous damage. The transition is easiest when
automation is part of capacity expansion or a new facility and doesn't threaten existing jobs.
In other situations, early education and retraining is essential. The effects of different levels of
automation on cycle time is examined in this study. The influence diagram below (figure 5)
indicates the variables of the efficiency of a preventative maintenance program, work requests
(maintenance tasks) efficiency, machine operator involvement, and different levels of
automation in relation to machine processing time.
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SHUTOOWN
"= HOURS.
TOTAL WORK
EMERGENCY PE nsouest s WORK REDUCTION
REQUEST HOURS NRK WORE EONS
‘OPERATIONS | a
Yo WORK INOUCED we
SCHEDULED WORK REQUEST FACTOR
EFFICIENCY SQ
COMPLETION
PARTS RATER) erent
AVAILABILITY 4 EQUIPMEN
7 AVAILABILITY
COMPLETION a
NCE WORKER er RATE
1 VENESS REVENTATIVE
AVAILABLE WORK
REQUEST HOURS
ACTUAL :
PRODUCTIVITY MAINTENANCE
INCREASE MOTIVATION
\ A MAINTENANCE
-FRESRETICAL TRAINING HOURS
PRODUCTIVITY INCREASE
TRAINING
PROGRAM FACTOR
NOMINAL MACHINE
ae ACTUAL MACHINE ra
. TEN NUMBER OF -
" 4 PREVENTATIVE BREAKDOWNS
MACHINE: MAIN AN
OPERATORS, LEVELS OF , , NCY
A ~\ AUTOMATION
ATTITUDES: ICTION IN
Figure 5. Influence Diagram representing Maintenance Management
WORKFORCE MANAGEMENT
This section explores the human side of manufacturing today .
technology means competing on the organization of information; invariably one thinks of a
battle of computers. But the machine is not at the center of competition; knowledge workers are
the only corporate assests that lasts. This study proposes that people are both a source of
strategy and the means to achieving its goals - even a technology - based strategy has its
foundations in people. Without the right people, the most streamlined processes make no
difference to the bottom line. The ability to reduce cycle time is necessary to make the changes
required by customer demands and desires. In order to acquire the ability to reduce cycle time,
an organization must be flexible. A flexible organization leads to an improved strategic
position and a competitive advantage that helps to ensure long term viability. Three values
essential to a corporation in pursuit of flexibility are diversity, discourse and empowerment.
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System Dynamics '95 — Volume II
Business is increasingly complex; and work that individuals used to perform is now
done on teams, For this reason, companies may need to transform a collection of individuals
of both genders and of different ethnic, racial, and religous backgrounds into a cohesive team
sharing a common goal, trust and interdependence. Companies must attract and motivate the
best and brightest people from every available source and coax the greatest contribution from
each person. Companies can't afford to have people working at 50 percent capacity because they
feel that certain of their abilities and attributes aren't welcome. What should companies hope
to accomplish by valuing diversity? First and foremost, companies will be creating an
environment in which every employee can make his or her fullest contribution to the company
goals. This will boost productivity immediately and enormously. Secondly, diversity will
change the psychological contract between employees and employer. When an employee works
to create an environment in which diverse people and talents are valued, people get motivated
and energized. They work at full capacity and get something back from the system in terms of
career and personal growth. People will play hardball if they know that they are truly on the
company team.
The second value essential to corporate flexibility is communication. Communication
too often becomes a one-way street; emanating from the top down. Communication gives rise
to the belief that information sharing is right and necessary. Sharing the corporate vision,
strategies and goals is fundamental, as is getting input and reactions to refine them. People
believe that listening is a way to learn and that ongoing learning keeps an individual and an
organization vital. They believe that the exchange of ideas leads to innovation and discovery
and that no one person has all the answers.
More than any other variable, communication drives flat organizational structures.
Information that travels by the shortest distance and most direct is the freshest, most
accurate, and most relevant. Given the distance between the top and the bottom of
organizations in pyramidal, hierarchial structures, it is not suprising that the top and bottom
are disconnected, don't understand each other, can't communicate, and (more often than not)
are working on entirely different agendas, goals, and programs. A flat structure, with its quick
access, puts everyone back on the same team on the same playing field on the same day. It isa
huge step toward a winning attitude and the success that results.
The third value essential to corporate flexibility is empowerment. Technically, to
empower means to invest with legal power, or to authorize. In today's human resources
vernacular, however, the word is used more for its connotative than literal sense. Empowered
people operate out of the passion and courage of their convictions. They do the right thing, live
out their values and beliefs, behave authentically, and follow through on commitments. They
are honest and fair with themselves and others, upfront and nonmanipulative. The definition
of empowerment is difficult to pin down exactly because it deals with the elusive world of
feelings. People feel empowered when their head and heart and gut are synchronized and they
are centered in the power that results. Everyday people all around us are empowered as they
accomplish their potentials.
The culture that springs from empowerment is a meritocracy. It invests in humans and
their growth and development, takes a long-term perspective, and supports personal
commitment and responsibility. The behaviors in this culture revolve around high
motivation with low supervision. This results from the combination of teamwork, shared
vision, and self-determination. People rotate in and out of full-time status. They express
loyalty and achieve quality and excellence in processes and products. They follow through on
commitments and take initiative by signing up for work that contributes to company goals.
They seek innovation and renewal.
The final link in the chain leading to flexibility is the human resources practices and
programs. It is difficult to predict accurately just what programs and systems an organization
shoud design. However, it is important to note that whatever programs are chosen, they should
be tied together into a system, and must all be directed at achieving flexibility. Some of the
most powerful tools that an organization can use to motivate employees are: recognition and
reward systems, benefits and training.
Based on the above information, five variables are being proposed to develop the
workforce management decision area of the model: skill levels, motivation, variances, tooling
and empowerment illustrated below in figure 6.
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TRAINING —-— ACTUAL LABOR
waa pacessaiie Te
VARIANCES
rgoerica. Facron NOrNA
PRODUCTIVITY INCREASE, \ me:
Inposred__SENEFITS
worstoace ToouING INvENToAY
LAYOFFS CTS ON we
NA RE
a COMMUNICATION uMion pe
Faglview NEGOTIATION’
OF LAYOFFS sew * ed
WRITE
nS EN roou
Weas DAMAGED
TRAINING TooLs
TECHNICAL
SUPPORT
Figure 6. Influence diagram representing Workforce Management
BASE RUN
The results of the base run are illustrated in figure 7. Key variables to this simulation model in
relation to cycle time are the hiring and layoff of employees, communication, union relations,
training, variances (meetings, sicktime, and training), equipment availability, maintenance
overtime hours, maintenance training hours, operator’s attitudes and their training
procedures, defective parts supplied by vendors, vendors delivering parts late to customers and
inspection errors during the receiving inspection of supplied parts. Cycle time includes labor
time, machine time, non-value added time due to the type of facility layouts, material handling
systems and delays either from parts being delivered late or poor quality parts supplied by the
vendor.
Cycle time varied over the ten year period with the exception of a few periods in which
they were significantly higher. The excessively long cycle times were as a result of the
cumulative affects of poor operator training procedures, layoffs, poor union relations and a
number of experienced and highly skilled employees leaving due to attrition. The downward
trends (i.e. reduction in cycle time) were due to good union relations, a period in which
suppliers supplied good quality parts and on time, reliable maintenance, high level of
communication, ample and effective training for employees and good operating procedures by
machine operators. The upward trends (increase in cycle time) were due to layoffs, highly
experienced and skilled employees leaving due to attrition, and poor operating procedures by
machine operators. The instances where there was a significant reduction in cycle time was as
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System Dynamics '95 — Volume II
a result of a process change due to continuous quality improvements. These improvements
were from a combination of actions such as high employee involvement, good. technical
support, high degree of empowerment and management support to implement the changes. The
erratic behavior of the system is due to the randomness of union relations, operator's
operating procedures, variances (meetings, sick leave). Figure 8 illustrates the systems flow
diagram of the proposed model .
© Crens Ti
a hormesis ieee
=
8 sant
1: 5.00
0.00
Bs Graph t: Paget
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4 RS ee
Figure 8. System Flow Diagram of Proposed Model of Manufacturing Strategy
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CONCLUSION
This paper proposes a model using Systems Thinking that can be utilized to better understand
the interrelationships among decision areas of manufacturing strategy. The framework
presented is in its conceptual stage, and further efforts are currently being pursued to validate
the model. The intent of this paper was to demonstrate the potential of studying
manufacturing strategy from a Systems Dynamic point of view; and to propose a conceptual
framework on such an approach.
REFERENCES
Abernathy, W.J. 1976. Production Process Structure and Technological Change. Decision
Sciences. Vol. 7.
Cohen, M.A. and HLL. Lee. 1985. Manufacturing Strategy: Concepts and Methods. The
Management of Productivity and Technology in Manufacturing. Ed. P.R. Kliendorfer.
DeMeyer, A. and K. Ferdows. 1987. Mangerial Focal Points in Manufacturing Strategy.
France: INSEAD European Institute of Business Administration.
Hayes, R.H. and K.B. Clark. 1985. Adversaries in Alliance: Managing the Productivity
Technology Dilemma. Boston: Harvard Business School Press.
Hayes, R.H. and RW. Schmenner. 1978. How Should You Organize for Manufacturing.
Harvard Business Review. Jan-Feb.
Hill, T. 1985. Manufacturing Strategy. London: Macmillan Education Limited.
Krajewski, L.J. and LP. Ritzman. 1987. Operations Management and Analysis: Strategy and
Analysis. Addison-Wesley.
Miller, J.G. et al. 1983. 1983 North American Manufacturing Futures Survey: Summary of
Survey Responses. Boston: Boston University Manufacturing Roundtable Research
Report Series.
Miller, J.G. et al. 1984. 1984 North American Manufacturing Futures Survey: Summary of
Survey Responses. Boston: Boston University Manufacturing Roundtable Research
Report Series.
Miller, J.G. et al. 1985. 1985 North American Manufacturing Futures Survey: Summary of
Survey Responses. Boston: Boston University Manufacturing Roundtable Research
Report Series.
Miller, J.G. et al. 1986. 1986 North American Manufacturing Futures Survey: Summary of
Survey Responses. Boston: Boston University Manufacturing Roundtable Research
Report Series.
Porter, M.E. 1980. Competitive Strategy. New York: The Free Press.
Roth, A. et al. 1987. Differentiated Manufacturing Strategies for Competitive Advantage: An
Empirical Investigation. Boston: Boston University School of Management Research
Report Series.
Senge, P.M. 1990. The Fifth Discipline. New York: Doubleday/Currency.
Skinner, W. 1969. Manufacturing - Missing Link in Corporate Strategy. Harvard Business
Review. May-June.
Skinner, W. 1974. The Focused Factory. Harvard Business Review. May-June.
Skinner, W. 1978. Manufacturing in the Corporate Strategy. New York: Wiley.
Wheelwright, S.C. 1981. Japan - Where Operations Really are Strategic. Harvard Business
Review. July-Aug.
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