A model for the assessment of waste in job shop environments

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A model for the assessment of waste in job shop environments
Article in International Journal of Operations & Production Management · August 2005
DOI: 10.1108/01443570510608619
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A model for the assessment of
waste in job shop environments
800
Industrial Engineering Department, University of Jordan, Amman, Jordan
Ibrahim A. Rawabdeh
Abstract
Purpose – The paper aims to investigate the waste in a job shop environment and proposes an
assessment method aimed at helping companies to identify root causes of waste.
Design/methodology/approach – The seven wastes (overproducing; processing; inventory;
transporting; producing defects; time waiting; and motion waste) and their relationships were
explored. A waste matrix was developed to quantify in a percentage form the relationships among
wastes and represents a probability that a certain type of waste will affect others or be affected by
others. An assessment questionnaire was employed to allocate the source of waste and differentiate
between the levels of waste. The waste matrix and the assessment questionnaire were incorporated in
the assessment method to rank the existing waste in a job shop.
Findings – The developed model serves as guidelines for simplifying the search of waste problems
and identifies opportunities for waste elimination. A case study was conducted to validate the model;
and the results of the assessment and the real situation concur.
Research limitations/implications – This paper has investigated a method to allocate waste,
quantify it and discuss the relationships among wastes without quantifying the potential savings.
Further research should be done in order to investigate the level of reduction in effort and time as a
result of implementing the method.
Practical implications – The approach provides a method by which managers can identify the
sources of waste, differentiate between the levels of waste and rank their significance.
Originality/value – The simplicity of the matrix and the comprehensiveness of the questionnaire
contribute to the achievement of accurate results in identifying the root causes of waste. The new
model provides an insight into on where to concentrate effort by weighing the contributions of the
different waste types.
Keywords Waste minimization, Just in time, Assessment, Materials management
Paper type Research paper
International Journal of Operations &
Production Management
Vol. 25 No. 8, 2005
pp. 800-822
q Emerald Group Publishing Limited
0144-3577
DOI 10.1108/01443570510608619
Introduction
International competition and customer demands are forcing radical changes to occur
in manufacturing. As a result, companies worldwide that are realizing the importance
of being part of the global market are searching for operational methods to increase
their competitive power through the use of innovative production systems. Traditional
manufacturing paradigms are being challenged and new manufacturing principles are
being developed. Terms such as: lean manufacturing, world-class manufacturing, and
agile manufacturing have emerged. Firms have given increased emphasis to delivering
products, that are needed by customers, faster than their competition, and meeting or
exceeding “best-in-class” quality requirements.
As more manufacturers struggle with global markets, competition from low-cost
countries and faltering home economies, the attention of many manufacturers has
naturally turned to operational costs and waste reduction (Strategic Direction, 2004).
The typical approach taken in the past when studying improvement opportunities, has
been to focus on the manufacturing processes, or the value-added process steps
(Conner, 2001). In an internal manufacturing context, there are three types of operation
that can be categorized: non-value adding (NVA); necessary but non-value adding
(NNVA); and value-adding (VA). The first of these is pure waste and involves
unnecessary actions that should be eliminated (Hines and Rich, 1997). Invariably little
attention was given to non-value-added activities such as storage and transportation.
The result is that minimal effect is realized in overall lead time, improved quality and
reduced cost. For instance, Conner (2001) reported that when lead-time was examined,
the two percentages of value-added activities and non-value-added activities are found
to be 5 and 95 per cent, respectively. When all energies are spent trying to improve the
value-added component of the lead-time, then the improvement to lead-time would be
only 2.5 per cent.
An array of new systems aiming at improving production efficiency and
maintaining a high level of quality, cost, and on-time delivery has been developed.
Just-in-time (JIT), in particular, has attracted much attention during the past
decade; and has been shown to yield increased efficiencies and performance
excellence throughout an organization; and its successes are well documented
(Daugherty et al., 1994). Many specific topics have been considered in the literature
as elements for JIT; these being summarized into: quality control, work force
preparation and waste elimination (Rawabdeh, 2001). JIT is an umbrella term for a
number of techniques whose purpose is to improve product quality and reduce
cost by eliminating all waste in the production system (Miltenburg, 2001). In the
JIT philosophy, the principal focal point is the elimination of all waste within a
system (Daugherty et al., 1994).
Waste can be defined as anything other than the minimum amount of resources
which are absolutely essential to add value to the product. Canel et al. (2000) defined
waste as anything other than the minimum amount of equipment, materials, parts,
space, and workers’ time, which are absolutely essential to add value to the product or
service. In terms of cost, waste refers to any incurred costs such as inventory, set-up,
scrap, and rework that do not add to the value of the product (Svensson, 2001).
Flinchbaugh (2001) argued that any goal beyond delivering the right product to the
right customer at the right time at the right price is waste. From the perception of end
users, waste is internal and external resources that are consumed without adding value
to the customers (Emiliani, 2001), i.e. if a customer is not willing to pay for them, then
their existence is considered a waste. This means that the different types of wastes
threaten many facets of performance of the company that customers may value. Hence
their elimination has become an axiom.
The use of waste elimination to drive competitive advantage inside organizations
was pioneered by Toyota’s chief engineers, Taiichi Ohno and Sensei Shigeo Shingo
(Hines and Rich, 1997), and was focused principally on productivity gains rather than
improved quality. The rationale is that improved productivity leads to leaner
operations that, in turn, exposes further waste and quality problems in the system.
Indeed, lean production’s originators, by formulating the “operating problem” as an
unceasing battle against waste (or muda in Japanese) were able to make it almost
axiomatic that lean implied better (Lewis, 2000). Thus the systematic elimination of
waste is also a systematic assault on the factors underlying poor quality and
fundamental managerial problems. From a practical perspective, waste can be
categorized into seven categories: waste from overproducing; processing; inventory;
Waste in
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transporting; producing defects; time waiting; and motion waste (Shingo, 1992; Imai,
1997; Emiliani, 2001; Flinchbaugh, 2001).
The seven wastes can also be categorized into three main groups related to: man,
machine and material by means of activities or conditions that affect the fourth,
namely, money. The man-group contains the concepts of motion, waiting, and
overproduction; the machine-group contains over-processing waste; and the
material-group contains transportation, inventory and defects waste. However, man
and material overlaps in overproduction waste, whilst machine and material overlaps
in defect waste. Figure 1 shows this classification.
There have been many applications concerning the use and importance of the waste
elimination concept in different fields of industry. However, investigations have
followed varying approaches. The objective of this paper is to introduce an innovative
approach in developing an assessment model that supports categorisation of the types
of waste in a job shop environment. This paper is organized as follows: first, a
background on waste elimination is presented, followed by a review of relevant
literature. Second, the developed model is explored and discussed showing the
concepts of seven waste relationships, a relationship matrix, and waste assessment
questionnaire. Third, the results of model implementation are presented and discussed
in a case study context. Finally, conclusions are presented, followed by
recommendations for future work.
Background
Elimination of waste is the corner-stone of a JIT system. It is acknowledged that the
implementation of JIT is one of the major factors contributing to the success achieved
in the international competitiveness of Japanese manufacturing firms in the last two
decades (Wu, 2003). Studies have identified that JIT also helped companies improve
their performance (Ahmad et al., 2004). JIT manufacturing systems consist of
systematic allocation and reduction of wasteful practices at all levels of any
organization. It can be argued that the philosophy underpinning waste identification
and its elimination is the basis upon which the JIT concept is built (Karlson and
Awstrom, 1996). Waste allocation and elimination have recently become an important
subject of research. Numerous contemporary definitions focus on JIT as an approach to
minimize waste in manufacturing and research has identified that the JIT
manufacturing philosophy is dependant upon organizations continually seeking to
improve their products and processes by eliminating waste (Monden, 1983; Toyoda,
Figure 1.
The three categories of
waste (man, machine,
materials) and its effect on
money
1987; Chong et al., 2001; Swanson and Lankford, 1998; Canel et al., 2000; Yasin et al.,
2004).
The objectives of JIT are complex to interpret due to the lack of homogeneity in the
literature. However, two objectives appear to be common denominators: a continuous
search for waste reduction and to make only what is needed in a timely way (Svensson,
2001). However, the JIT production system is being adopted by many firms and
companies worldwide, so increasingly companies (especially small and medium sized)
in their continuous strive for excellence, have realized that JIT production systems
could be a direction for future competitiveness and prosperity. It is a perspective on the
continuing evolution towards world-class manufacturing (Rawabdeh, 2001).
A systematic and continuous identification and elimination of waste can lead to
increased efficiency, improved productivity and enhanced competitiveness. Generally,
companies that work towards the elimination of waste in their manufacturing
processes realize the following benefits: lower raw material stock and associated
holding cost, reduced work-in-process, and lower finished goods inventories; higher
levels of product quality; increased flexibility and ability to meet customer demands;
lower overall manufacturing costs; and increased employees’ involvement (Chase et al.,
1998; Canel et al., 2000). Emiliani (2001) reported that, fundamentally, poor
competitiveness is caused by the existence of large amounts of waste. Reduction of
these non-productive activities (waste) eventually saves time and allows more
resources to be allocated to improving throughput and profitability. The principle of
continuous improvement by waste elimination has been applied as an approach to
improving the performance of a case production system (Ramaswamy et al., 2002).
Evans and Jukes (2000) suggested that synchronization in the area of product
development can be achieved through the four key steps of process standardization,
knowledge sharing, alignment of existing practices, and continuous elimination of
waste within the joint development cycles. In JIT terminology, standard operations and
procedures endeavour to produce efficiently with the least amount of waste, using
efficient rules and methods (Lim et al., 1999).
The process of identifying waste activities, however, is not an easy task. The large
number of parameters and overlap between different processes may cause waste
activities to be concealed between other activities. Nevertheless, the mere consideration
of waste reduction brings about an important focus on the subject. Moreover, the
importance of the problem is usually underestimated, and the starting point of where
and how to search for waste is unclear. An additional issue is, when there are
interventions to eliminate one type of waste, this may result in other waste-types being
negatively affected. Such factors make it difficult to consider removing what may be
considered as waste activities.
A number of approaches have been developed to explore waste-related issues.
Kobayashi (1995) developed a system termed the practical program of revolutions in
factories (PPORF). The approach uses a 20-key system that defines the meaning of
excellence in twenty key areas related to quality, cost, and delivery. That system
demonstrates how improvements in these areas collectively improve a company’s
overall competitiveness. It presented a scoring method that measured the progress of
the company through five levels, in each area. Waste elimination is key number
thirteen in that approach. Imai (1997) developed what is called a continuous
improvement or kaizen approach. The approach is based on three ground rules for the
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practice of kaizen: specifically, housekeeping, standardization, and waste elimination.
It employs a process in which cross-functional teams systematically analyze processes
to identify and eliminate waste. Imai reported that each kaizen event can yield a higher
per cent in waste reduction compared to that sporadically achieved by batch-and-queue
businesses. Investment analysts would be wise to participate in shop floor kaizen
events and witness first-hand the elimination of waste and concomitant improvements
in operating and financial performance (Emiliani, 2001). Brunet and New (2003)
discussed the practical aspects of kaizen and concluded that it appears to be less of a
stand-alone suite of techniques and practices, and more of an integral part of an overall
system of operations planning. They reported that there remained good reasons for
continuing to seek the transferable “core” of kaizen management ideas, especially as
organizations across the world attempt to replicate the operational success of many
Japanese firms.
Lim et al. (1999) proposed a holistic framework that was formulated after careful
consideration of Japanese corporate experience and practices. They used the 4Ms (man,
machine, material and method) framework to help focus attention on potential areas
that need to be addressed and improved. They recognized that the sources of waste
often lie not simply in “hard” or “technical” operations, but reside within the soft
drivers of these operations. Such soft issues need evaluation of how their role as
supporting procedures and the format of documentation need to be engineered (or
re-engineered), and so create efficient waste-less manufacturing operations. O’hEocha
(2000) explored the practical use of the 5S technique for waste reduction in a
manufacturing company. He demonstrated that the 5Ss were effective in improving the
working environment and final performance, due primarily to the measured reductions
in waste at the production level.
The literature identifies that the concept of eliminating non-value activities, and
reducing inventories, motions, defects, waiting and overproduction, is an essential part
of a JIT manufacturing system. Although Japanese industries achieved substantial
success by applying this concept, there have been few systematic methodologies that
identify the procedural starting point for waste allocation. By adopting the principle of
systematic waste elimination, this requires thinking and talking in the language of
waste. The literature has not addressed the strength of relationships among all types of
waste. There is little empirical work of a quantitative nature that adequately defines a
comprehensive tool for waste elimination, and which will reduce types of wastes
without negatively affecting other causes of waste.
Methodology
The proposed waste assessment model commences by articulating the definitions of
each type of the seven wastes and their overlapping areas. A criterion was established
to quantify the strength of direct relationships, thus leading to the creation of a waste
matrix that classifies the strength of relationships using a scale ranging from very
weak to very strong. Next, an assessment questionnaire was introduced. Within the
context of a jobbing shop, it was possible to rank waste by combining the relationship
matrix and the results of the assessment questionnaire.
Seven wastes relationships
All types of waste are inter-dependent, and each type has an influence on the others;
and simultaneously is influenced by the others. For example, overproduction is
regarded as the most serious waste as it gives rise to other types of waste (Kobayashi,
1995). Wu (2003) reported that over-production forces the plant to change the number
in the work force, thus making standardization very difficult, that leads to quality
problems and waste of competencies.
Discussing the relationships among wastes is complex because the influence of each
type on the others can appear directly or indirectly. The following discussion addresses
the effect of each type of waste on the other six types. Each type of waste was
abbreviated using its initial, (O: Over-production, I: Inventory, D: Defect, M: Motion,
P: Process, T: Transportation, W: Waiting), and each relationship was assigned the
symbol of underscore “_”. For instance, O_I indicates the direct effect of
overproduction on inventory. Figure 2 shows which one is affecting, and is affected,
by the others; Table I summarizes the explanation for the relationships.
The different types of relationships and the nature of each type suggest that all
these relationships are not of equal weights. The need to assign weights to
relationships is justified by the need to know which type of waste contributes more to
the wasteful activities on a shop floor. A measurement criterion based on a
questionnaire was developed to quantify the strengths of waste relationships (see
Table II). It consists of six questions and each answer has a specific weight ranging
from zero to four. Several brainstorming sessions among specialists were held to
Waste in
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environments
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Figure 2.
Direct wastes relationship
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Overproduction
O_I
O_D
O_M
O_ T
O_W
Inventory
I_O
I_D
I_M
I_T
Defects
D_O
D_I
D_M
D_T
D_W
Motion
M_I
M_D
M_P
M_W
Transportation
T_O
T_I
T_D
T_M
Table I.
The explanation of waste
relationships
T_W
Over-production consumes and needs large amounts of raw material causing
stocking of raw material and producing more work-in-process that consume floor
space, and are considered as a temporary form of inventory that has no customer
(process) that may order it.
When operators are producing more, their concern about the quality of the parts
produced will decrease, because of the sense that there exists enough material to
substitute the defects.
Overproduction leads to non-ergonomic behavior, which leads to non-standardized
working method with a considerable amount of motion losses.
Over-production leads to higher transportation effort to follow the overflow of
materials.
When producing more, the resources will be reserved for longer times, thus other
customer will be waiting and larger queues begin to form
The higher level of raw materials in stores can push workers to work more, so as to
increase the profitability of the company.
Increasing inventory (RM, WIP, and FG) will increase the probability of become
defected due to lack of concern and unsuitable storing conditions.
Increasing inventory will increase the time for searching, selecting, grasping,
reaching, moving, and handling.
Increasing inventory sometimes block the available aisles, making a production
activity more transportation time-consuming.
Over-production behavior appears in order to overcome the lack of parts due to
defects.
Producing defective parts that need to be reworked means that increased levels of
WIP exist in the form of inventory.
Producing defects increases the time of searching, selection, and inspection of
parts, not to mention that reworks are created which need higher training skills.
Moving the defective parts to rework station will increase transportation intensity
(back streams) i.e. wasteful transportation activities.
Reworks will reserve workstations so that new parts will be waiting to be
processed
Non-standardized work methods lead to high amounts of work in process.
Lack of training and standardization means the percentage of defects will increase.
When jobs are non-standardized, process waste will increase due to the lack of
understanding the available technology capacity.
When standards are not set, time will be consumed in searching, grasping,
moving, assembling, which result in an increase in part waiting parts.
Items are produced more than needed based on the capacity of the handling
system so as to minimize transporting cost per unit.
Insufficient number of material handling equipment (MHE) leads to more
inventory that can affect other processes.
MHE plays a considerable role in transportation waste. Non-suitable MHE can
sometimes damage items that end being defects.
When items are transported anywhere this means a higher probability of motion
waste presented by double handling and searching.
If MHE is insufficient, this means that items will remain idle, waiting to be
transported
(continued)
Process
P_O
P_I
P_D
P_M
P_W
Waiting
W_O
W_I
W_D
In order to reduce the cost of an operation per machine time, machines are pushed
to operate full time shift, which finally results in overproduction.
Combining operations in one cell will result directly to decrease WIP amounts
because of eliminating buffers.
If the machines are not properly maintained defects will be produced.
New technologies of processes that lack training create the human motion waste.
When the technology used is unsuitable, setup times and repetitive downtimes will
lead to higher waiting times.
When a machine is waiting because its supplier is serving another customer, this
machine may sometimes be forced to produce more, just to keep it running.
Waiting means more items than needed at a certain point, whether they are RM,
WIP, or FG.
Waiting items may cause defects due to unsuitable conditions.
Question
(1) Does i produce j?
Always
Sometimes
Rarely
(2) What is the type of the relationship between i and j?
As i increases j increases
As i increases j reaches a constant level
Random depends on conditions.
(3) The effect of j due to i:
Appears directly and clearly
Needs time to appear
Not often appears.
(4) Eliminating the effect of i on j is achieved by:
Engineering Methods
Simple and direct
Instructional solution
(5) The effect of j due to i, mainly influences:
Quality of products
Productivity of resources
Lead time
Quality and productivity
Productivity and lead time
Quality and lead time
Quality, productivity and lead time
(6) In which degree does the effect of i on j increase
manufacturing lead time?
High degree
Medium degree
Low degree
Note: i stands for any type of waste which has an effect on the other type of waste j
Waste in
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807
Table I.
Weight
4
2
0
2
1
0
4
2
0
2
1
0
1
1
1
2
2
2
4
4
2
0
Table II.
The developed criteria for
evaluating the strengths
of waste relationships
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explore and answer the questions. The following steps show the analysis for
developing relationship weightings.
Table III illustrates an example of tabulating the results related to the relationship
between over-production and inventory (O_I) and shows that if the answer to question
number one is yes, then it is represented by the letter “a”, i.e. does i waste produce j
waste, where i and j are types of waste? The same is applied for all questions about this
particular relationship. Each answer was assigned a weight identified in the
measurement criteria, and each number beside each character represents the weight of
the answer. The weights of all answers of each relationship were added together,
resulting in an overall summation. The summation was recorded in the column headed
“Score”, where the score indicates the strength of each relationship. In order to
distinguish different relationships, it was noted that higher scores represent stronger
relationships and vice versa. The range of scores, based on the suggested method of
evaluating the strengths of the wastes relationships, is found to be between (1) and (20),
and it is divided into five equal intervals, each indicating a level of strength of a
relationship (see Table IV). These steps are applied for each relationship resulting in
total scores that were represented by symbols that related to the different types of
relationship between each pair of waste types. The results are summarized in Table V.
Waste relationship matrix
The measurement criterion analysis was organized in a matrix titled waste
relationship matrix (WRM). Each row indicates the effect of a certain waste on the
other six wastes; similarly each column indicates to what extent a certain type of waste
will be affected by others. The WRM is presented in Figure 3. The diagonal of the
matrix was assigned with the highest relationship value, as, by default, each type of
waste will have the ultimate relationship with itself. The waste matrix represents real
relationships among wastes.
The weightings of each row or column were totalled to obtain a score that
represents the effect of a waste type on others or was affected by the others. This score
is converted into a percentage to provide a more simplistic metric, as illustrated and
Table III.
The relationship between
overproduction and
inventory (O_I)
Table IV.
Range divisions of
strength of direct
relationship
Question
1
2
3
4
5
6
Relationships Ans Wght Ans Wght Ans Wght Ans Wght Ans Wght Ans Wght Score
O_I
O_D
a
B
4
2
a
c
2
0
a
b
4
2
A
B
2
1
f
a
2
1
a
c
4
0
18
6
Range
Type of relationship
Symbol
17 to 20
13 to 16
9 to 12
5 to 8
1 to 4
Absolutely necessary
Especially important
Important
Ordinary closeness
Unimportant
A
E
I
O
U
O_I
O_D
O_M
O_T
O_W
I_O
I_D
I_M
I_T
D_O
D_I
D_M
D_T
D_W
M_I
M_D
M_W
M_P
T_O
T_I
T_D
T_M
T_W
P_O
P_I
P_D
P_M
P_W
W_O
W_I
W_D
Question
Relationships
Wght.
4
2
2
2
2
2
2
4
4
2
2
2
4
2
0
2
4
2
0
0
2
2
2
2
0
2
2
2
2
4
2
a
b
b
b
b
b
b
a
a
b
b
b
a
b
c
b
a
b
c
c
b
b
b
b
c
b
b
b
b
a
b
1
Ans.
a
c
c
a
b
c
c
b
c
b
c
c
b
a
a
b
a
b
c
b
c
c
c
b
c
a
c
a
c
a
b
Ans.
2
2
0
0
2
1
0
0
1
0
1
0
0
1
2
2
1
2
1
0
1
0
0
0
1
0
2
0
2
0
2
1
Wght.
a
b
c
b
b
a
b
b
c
a
b
a
a
b
b
b
a
a
b
b
b
c
a
b
c
a
c
b
b
a
b
Ans.
3
4
2
0
2
2
4
2
2
0
4
2
4
4
2
2
2
4
4
2
2
2
0
4
2
0
4
0
2
2
4
2
Wght.
a
b
a
b
a
a
a
a
a
c
b
b
b
b
c
a
a
c
b
b
b
c
b
a
a
a
a
a
b
a
a
Ans.
4
2
1
2
1
2
2
2
2
2
0
1
1
1
1
0
2
2
0
1
1
1
0
1
2
2
2
2
2
1
2
2
Wght.
f
a
d
f
e
e
a
e
c
e
e
e
c
e
e
g
e
d
c
f
f
e
e
e
c
a
g
e
b
g
a
Ans.
5
2
1
2
2
2
2
1
2
1
2
2
2
1
2
2
4
2
2
1
2
2
2
2
2
1
1
4
2
1
4
1
Wght.
a
c
c
b
a
b
b
c
b
c
b
b
b
b
c
a
a
b
c
c
b
c
b
c
c
c
b
b
c
a
c
Ans.
6
4
0
0
2
4
2
2
0
2
0
2
2
2
2
0
4
4
2
0
0
2
0
2
0
0
0
2
2
0
4
0
Wght.
18
6
6
11
13
12
9
11
9
9
9
11
13
11
6
15
18
11
4
6
9
4
11
9
3
11
10
12
6
20
8
Score
A
O
O
I
E
I
I
I
I
I
I
I
E
I
O
E
A
I
U
O
I
U
I
I
U
I
I
I
O
A
O
Relationship
Waste in
job shop
environments
809
Table V.
The relationship between
different types of waste
IJOPM
25,8
810
Figure 3.
Waste relationship matrix
(WRM)
summarized in Figure 4. A scale of ten was chosen by dividing the right extreme by a
factor of 2 for ease of use and comparative exposition.
To validate the waste relationship matrix, and after reviewing the results, it was found
that these findings concur with the literature in terms of the influence of the seven wastes
on each other. Over-production waste was found to be dominating the other wastes with
the highest percentage (16.8 per cent). It was reported that over-production was considered
the most serious waste since it increases all the other types and has the maximum
influence (Kobayashi, 1995). That is because it discourages a smooth flow of goods or
services and is likely to inhibit quality and productivity (Hines and Rich, 1997). Producing
more items than is immediately needed by the next station or market creates excess
temporary inventories. This can be clearly recognized from the strong relationship
between over-production and inventory. Over-production also tends to lead to excessive
lead-times and increased storage. As a result, defects may not be detected sufficiently early
(Imai, 1997). Due to over-production, motion waste is expected to rise by the same degree
as that of defects. Additionally, material handling will be markedly increased, which
results in waiting-waste being affected to a higher degree because goods are not moving
and/or not being worked on. Conversely, the other wastes influence over-production by a
lesser degree; which can be seen by the smaller percentage value (13.6 percent).
Figure 4.
Waste matrix values
Excess inventory, i.e. inventory-waste, tends to increase lead-time, prevents rapid
identification of problems and increases space requirements, thereby discouraging
communication (Imai, 1997). In order to conduct effective purchasing, it is especially
necessary to eliminate inventory-waste due to incorrect lead-times and due-dates
(Barla, 2003). It is reported that removal of buffer stock is a major problem that should
be addressed on the shop floor of small and medium size enterprises (Ramaswamy
et al., 2002). It is found that inventory influences other wastes by 13.6 per cent.
Inventory affects over-production, defects, motion, and transportation wastes by the
same degree. Problems are hidden by inventory (Hines and Rich, 1997), so that waste
leads to inventory with the highest degree (18.4 per cent).
Defect-waste is the bottom-line waste since it is a direct cost. When a defect occurs,
rework may be required; otherwise the product will be scrapped. Generation of defects
will not only waste material and labor resources, but it will also create material
shortages, hinder meeting schedules, create idle time at subsequent workstations and
extend the manufacturing lead-time. As a result, defects influence other wastes by the
same degree as over-production (16.8 per cent). Defects have an effect on
over-production, inventory, motion and waiting by the same degree; but they affect
transportation by a higher level because of wasteful transportation activities due to
rework and scrapped items. Defects are also affected by the other six wastes, indicating
a comparatively high percentage (17.6 percent).
Motion-waste involves poor ergonomics of production, where operators have to
stretch, bend and pick up when such actions could be avoided. Such waste is likely to
lead to poor productivity and, often, to quality problems (Hines and Rich, 1997). This
can be clearly recognized from the matrix as it affects the other wastes by 15.2 per cent;
whilst being influenced by other types of wastes (albeit by a lower level of 13.6
percent). Motion results in waiting by the highest level, while at the same time it leads
to defects more strongly than any other type of waste. Also, it affects inventory and
process-wastes by differing amounts.
Transportation involves goods being moved around. Therefore, taken to an extreme
argument, any movement in the factory could be viewed as a waste. In addition, double
handling and excessive movements are likely to cause damage and deterioration, with
the distance of communication between processes proportional to the time it takes to
feed back reports of poor quality and to take corrective action (Hines and Rich, 1997).
This is strong evidence that transportation has a major influence on defects and
waiting. Transportation affects the other types of waste and is affected by them by the
same level (12.0 percent).
Inappropriate processing occurs in situations where overly complex solutions are
found for simple procedures. It also occurs when machines are used inefficiently, so
that poor quality goods will be produced (Imai, 1997). Process-waste affects other
wastes by a percentage of 14.4 percent. However, it is influenced only by motion-waste,
and hence the reason why it scores the lowest type of waste having an influence on
others (6.4 per cent). One of the most wasteful manufacturing activities is waiting time
(Fullerton and McWatters, 2001). It was found to have the highest percentage (18.4 per
cent) in terms of its effect on the other wastes. Waiting-waste occurs whenever goods
are not moving or being worked on and affects inventory and results in excessive work
in process stocks (Hines and Rich, 1997). Waiting is the result of all types of waste, as it
leads directly to increased manufacturing lead-time. However, the 11.2 per cent of the
Waste in
job shop
environments
811
IJOPM
25,8
812
influence of the waiting-waste on the others derives principally from its impact on
over-production, inventory and defects.
Waste assessment questionnaire
A waste assessment questionnaire was developed to allocate waste in a jobbing shop.
Jobbing shops do not make the same product each day. Their business is likely to be
“make-to-order”, with thousands of part numbers, and they can never accurately
predict which part number will be in demand (Krajewski and Ritzman, 2002). In
jobbing shops, machines are arranged into groups according to their general type of
manufacturing process. Different parts, each requiring its own unique sequence of
operations, can be routed through the respective departments in a sequential order.
The assessment questionnaire consists of 68 different questions, which were
introduced for the purpose of allocating waste. The assessment questions were
introduced so that each question represents an activity, a condition or a behavior that
may lead to a specific type of waste. Some questions are assigned a “From” note, which
means that the question represents an existing type of waste that may lead to other
wastes, with reference to the waste relationship matrix. Other questions are assigned a
“To” note, which means that a question represents any existing type of waste that may
have been caused by other types of waste. Each question has three answers and each
answer was assigned a weight of: 1, 0.5 or zero. The questions were then categorized
into four groups of man, machine, material and method since each question is related to
one of these categories. A sample of the assessment questions is shown in Table VI.
Upon development of the assessment model questionnaire, it was noted that each
question led to a certain type of waste by a certain degree, depending on its answer.
The final rank of wastes depended on the combination of answers. Because of this, an
algorithm consisting of several steps was developed. It starts with counting the “From”
and “To” questions of the same type of waste. Table VII shows the number of
questions of each “From” or “To” type. Based on the Table VII classification, and
utilizing the original weights of waste relationships in Table V, Table VIII is produced
to simplify calculating the final score of existing waste types.
The second step of the algorithm is to rearrange Table VIII and to remove the effect
of variation of number of questions for each question type by dividing each weight in
the row by the corresponding number of questions (Ni) for each question (see Table IX).
Let W to be the weight of relationship and j the type of waste for each question number
k, the values in each column under each type of wastes can be summed up to obtain a
score based on equation (1) as follows:
Sj ¼
K
X
W j;k
Ni
K¼1
for
each
type
of
waste
j
ð1Þ
where: Sj is the score of the waste, and k ranges between 1 and 68.
The third step is to remove the effect of the null answer. For each type of waste,
which is represented by the waste columns, each cell that was assigned a weight was
counted, where: Fj is the frequency (number) of cells that were assigned a weight other
than 0, for each type of waste (j). The results for the frequency values (F) are shown in
the bottom of Table IX.
#
Question
Category (1): Man
1.
Does the management transfer operators to various jobs and
machines so that operations can be performed by all individuals?
2.
Do supervisors provide the amount and quality of supervision
needed?
3.
Are hourly workers adequately supervised on evening shifts?
4.
Are positive steps taken to raise hourly workers’ morale and work
interest?
Category (2): Material
8.
Is vendor lead time available to production schedulers?
9.
Are schedules checked for material availability before release to
production?
10.
Are parts received in unitized loads?
11.
Does production planning give warehouse personnel sufficient
advance notice of items and stock activity?
12.
Are warehouse personnel notified in advance of planned inventory
changes?
13.
Is there any excessive accumulation of materials awaiting repair,
rework, or return to vendors?
14.
Do materials appear to be standing around piled up unnecessarily on
the receiving platform?
15.
Do production workers stand around waiting for materials to arrive?
16.
Are materials moved more often than necessary?
17.
Are delicate parts frequently damaged in transportation activities?
Category (3): Machine
32.
Are tests on the efficiency of the machines, standard to
manufacturer’s specifications, periodically conducted?
33.
Is the workload for each machine predictable in sufficient detail?
34.
Once a machine has been installed, is there follow-up to see if it
performs according to specifications?
35.
Is material-handling equipment capacity adequate to lift the heaviest
jobs?
Category (4): Method
44.
Is warehouse space availability known in order to avoid blockage of
warehouse aisles?
45.
Is there a satisfactory drawing-numbering system that permits easy
reference, storage and retrieval?
46
Is storage space used effectively for storage with the aid of racks and
forklift trucks?
63.
Do most of products flow in one direction?
64.
Is there a group or committee, concerned with design, component,
construction, drafting, and other forms of standardization?
65.
Do work standards have specific and known objectives, such as
component cost reduction, work simplifications, and inventory
control?
66.
Can work imbalances be forecast in time to adjust them?
67.
Are work procedures screening out redundant or unnecessary work?
68.
Are the results of quality control, product testing, and evaluation
passed on to engineering?
Type
Waste in
job shop
environments
To motion
From motion
From defects
813
From motion
To waiting
From waiting
From
transportation
From inventory
From inventory
From defects
From inventory
From waiting
To defects
From defects
From process
To waiting
From process
From
transportation
To transportation
From motion
From waiting
From motion
From motion
From motion
From
overproduction
From process
From defects
Table VI.
The assessment
questions and types
IJOPM
25,8
814
Table VII.
Number of grouped
assessment questions
i
1
2
3
4
5
6
7
8
9
10
11
Ques. type
Table VIII.
The original weights as
obtained from the WRM
Man
To motion
From motion
From defects
From motion
Material
To waiting
From waiting
From transportation
From inventory
From inventory
From defects
From inventory
From waiting
To defects
From defects
Machine
From process
To waiting
From process
From transportation
Method
To transportation
From motion
From waiting
From motion
From motion
From motion
From overproduction
From process
From defects
Type of question (i)
No of questions (Ni)
From overproduction
From inventory
From defects
From motion
From transportation
From process
From waiting
To defects
To motion
To transportation
To waiting
5
6
8
11
4
7
8
4
9
3
5
Question #
O
I
D
M
T
P
W
1
2
3
4
4
0
6
0
6
4
6
4
6
8
10
8
10
10
6
10
2
0
8
0
6
6
0
6
0
10
6
10
8
9
10
11
12
13
14
15
16
17
8
4
2
6
6
6
6
4
2
4
0
10
4
10
10
6
10
10
4
6
6
4
6
6
6
10
6
4
6
10
10
0
2
6
6
6
6
0
2
8
6
0
10
6
6
8
6
0
10
6
6
0
0
0
0
0
0
0
0
6
10
10
6
0
0
6
0
10
6
4
32
33
34
35
6
8
6
2
2
0
2
4
6
6
6
6
6
10
6
2
0
6
0
10
10
6
10
0
6
10
6
6
44
45
46
63
64
65
66
67
68
Score
6
0
4
0
0
0
10
6
6
318
6
4
10
4
4
4
10
2
6
396
8
8
4
8
8
8
4
6
10
450
0
10
0
10
10
10
4
6
6
420
10
0
0
0
0
0
6
0
8
260
0
6
0
6
6
6
0
10
0
232
0
10
10
10
10
10
8
6
6
402
Ques. type
#of ques.(Ni) Question # (K) Wo,k Wi,k Wd,k Wm,k Wt,k Wp,k Ww,k
Man
To motion
From motion
From defects
From motion
Material
To waiting
From waiting
From transportation
From inventory
From inventory
From defects
From inventory
From waiting
To defects
From defects
Machine
From process
To waiting
From process
From transportation
Method
To transportation
From motion
From waiting
From motion
From motion
From motion
From overproduction
From process
From defects
Score(Sj)
Frequency(Fj)
9
11
9
11
1
2
3
4
0.44
0
0.67
0
1.11
0.36
0.67
0.36
0.44
0.73
1.11
0.73
0
0.91
0.67
0.91
0
0
0.89
0
0
0.55
0
0.55
1.11
0.91
0.67
0.91
5
8
3
6
6
9
6
8
2
9
8
9
10
11
12
13
14
15
16
17
0.8
0.5
0.67
1
1
0.67
1
0.5
1
0.67
2
1.25
1.33
1.67
1.67
0.67
1.67
1.25
2
0.67
0.8
0.5
2
1
1
1.11
1
0.5
3
1.11
0
0
0.67
1
1
0.67
1
0
1
0.67
0
0
3.33
1
1
0.89
1
0
5
0.89
0
0
0
0
0
0
0
0
0
0
2
1.25
2
0
0
0.67
0
1.25
3
0.67
7
5
7
3
32
33
34
35
0.86
0.8
0.86
0.67
0.29
2
0.29
1.33
0.86
0.8
0.86
2
0.86
0
0.86
0.67
0
0
0
3.33
1.43
0
1.43
0
0.86
2
0.86
2
3
11
8
11
11
11
5
7
8
44
45
46
63
64
65
66
67
68
0.67
0
0.5
0
0
0
2
0.86
0.75
45
49
1.33
0.36
1.25
0.36
0.36
0.36
2
0.29
0.75
70
68
2
0.73
0.5
0.73
0.73
0.73
0.8
0.86
1.25
70
68
0.67
0.91
0
0.91
0.91
0.91
0.8
0.86
0.75
49
54
3.33
0
0
0
0
0
1.2
0
1
49
28
0
0.55
0
0.55
0.55
0.55
0
1.43
0
21
26
2
0.91
1.25
0.91
0.91
0.91
1.6
0.86
0.75
76
61
Waste in
job shop
environments
815
Table IX.
Division of Table VIII by
Ni values and summary
The next steps in the algorithm were completely dependent on answering the
assessment questionnaire. As discussed previously, each question has three
answers with assigned weights 1, 0.5 or zero. The obtained rows for each type of
waste are multiplied by the weight of each answer, which is given the symbol Xk.
For example, the number of questions in the “From Motion” in the Man-group of
questions is 11 and the weight of question 2 with respect to defect waste is 8, and the
answer to the question is b (X2 ¼ 0.5), this results in Wd,3 ¼ 0.5 * 8/11 (0.36). Table X
Ans.
Weight
K
Wo,1
Wi,2
Ws,3
Man
Wm,4
1
0.5
0
1
2
3
0.44
0
0
1.11
0.18
0
0.44
0.36
0
0
0.45
0
Wt,5
Wp,6
Ww,7
0
0
0
0
0.27
0
1.11
0.46
0
Table X.
Calculated weight values
for each type of waste
IJOPM
25,8
816
shows an example where rows are multiplied by the factor available in the “weights”
column.
The values in each column under each type of waste were summed to obtain the
new score (sj), as in equation (2):
sj ¼
K
X
XK £
K¼1
W j;k
Ni
for
each type
of
waste
ð2Þ
j
After the multiplication, the number of non-zero cells in each column was counted to
obtain the frequency (fj) of a particular situation (i.e. a company). The rationale for this
lies in the fact that sometimes the answer to a question will have a value that equals
zero and sometimes there is a question that cannot indicate a relationship with a waste
type and its value will also be zero. To obtain the initial indication factor of each type of
waste, depending on the answers, equation (3) was applied separately for each type of
waste:
Yj ¼
sj f j
£
Sj F j
for
each
type
of
waste
ð3Þ
j
where Yj is the initial indication factor of each type of waste. However, Yj only
represents mathematical results, since each type of waste affects all other types by a
certain percentage. The same is applied when considering how each type of waste is
affected by others. In order to expedite this, the “From” and “To” percentages obtained
from waste matrix values (Figure 4) are multiplied together to obtain the probability of
their occurrence (Pj) (i.e. effect of overproduction ¼ 16.8 * 13.6 ¼ 228.48).
To reflect the fact that the existence of each type of waste can affect others and at
the same time be affected by others, Yj is multiplied by Pj to obtain the final waste
factor (Yjfinal) as in equation (4):
Y jfinal ¼ Y j £ P j ¼
sj f j
£ £ Pj
Sj F j
for
each type
of
waste
j:
ð4Þ
As a result and based on the Yjfinal value of each waste, the types of waste were ranked
in descending order.
Case study
A case study of a steel furniture company introduces the application of the proposed
waste assessment model. The company is a medium-sized company with
approximately 100 employees and working capital of $5M. The concept of “The
seven wastes” and their interrelationships were introduced to the General Manager and
Production Manager. The factory has a high-level of product mix. There are 24 main
types of products in the plant categorized into four category groups: office furniture;
storage systems; safes; and customized products. The company has a jobbing shop
industrial environment. The flow of the materials into the factory is process oriented.
The factory consists of a single floor, and the offices are on two levels. The available
machines are either modern technology that depend on CNC or conventional manual
types.
Model implementation
The implementation of the assessment model passed through several reviews and
improvements, following management’s comments about its nature, the requirement of
being easy to understand and to implement. The answers and analysis of the
assessment questions for the company are presented in Table XI. Table XII
summarizes the assessment analysis and provides a rank of the different types of
wastes.
These results were presented to both the General Manager and Production
Managers who explained that the factory’s three major problems were as follows:
(1) Defects. Different types of defects existed among different departments in the
company’s inbound supply chain. There were no standard procedures to deal
with defective parts at that time. The company’s operators determined whether
to report the defect so that other replacement parts are produced immediately
Ans.
Question # (K)
Wo,k
Wi,k
Wd,k
Wm,k
Wt,k
Wp,k
Ww,k
1
2
3
4
0
0
0.333
0
0
0.182
0.333
0
0
0.364
0.556
0
0
0.455
0.333
0
0
0
0.444
0
0
0.273
0
0
0
0.455
0.333
0
8
9
10
11
12
13
14
15
16
17
0
0
0
1
0.5
0
0
0
0.5
0
0
0
0
1.667
0.833
0
0
0
1
0
0
0
0
1
0.5
0
0
0
1.5
0
0
0
0
1
0.5
0
0
0
0.5
0
0
0
0
1
0.5
0
0
0
2.5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.5
0
32
33
34
35
0.857
0
0
0
0.286
0
0
0
0.857
0
0
0
0.857
0
0
0
0
0
0
0
1.429
0
0
0
0.857
0
0
0
44
45
46
0
0
0
0
0.182
0
0
0.364
0
0
0.455
0
0
0
0
0
0.273
0
0
0.455
0
0
0.182
0
1
0.286
0.375
18
35
0
0.364
0
0.4
0.857
0.625
25
35
0
0.455
0
0.4
0.857
0.375
21
34
0
0
0
0.6
0
0.5
16
15
0
0.273
0
0
1.429
0
11
19
0
0.455
0
0.8
0.857
0.375
24
31
Waste in
job shop
environments
817
Man
0
0.5
0.5
0
Material
0
0
0
1
0.5
0
0
0
0.5
0
Machine
1
0
0
0
Method
0
0.5
0
0
0.5
0
0.5
1
0.5
Score (Sj)
Frequency (Fj)
63
64
65
66
67
68
0
0
0
1
0.857
0.375
12
21
Table XI.
Summary of the
assessment analysis and
a rank of the different
types of wastes in the
company
IJOPM
25,8
818
before the setup of the previous machine is changed. This leads to hidden
defective parts that are discovered later on, especially at the assembly station.
This creates the need to produce additional parts to overcome the lack of parts
caused by defects. Thus, the lead-time is increased. In addition, and based on
the managers assumption that 100 per cent inspection is implemented through
different processes, the inspection for both amount and quality received at each
station was not set as a standard procedure. This also led to a late discovery of
defects, and repetition of the problem.
(2) Down-times and set-ups. The company experienced frequent downtimes due to
machines malfunctioning. These malfunctionings were caused by lack of
continuous checking of the machine running requirements and conditions of
operations. No documented procedures were available to specify the status of
machines in order to prevent down-times before their occurrence.
(3) Over-production and inventory level. The level of inventory and the need for
over-production was minimal. The company production system was based on
make-to-order production.
The results of implementing the waste assessment model show the following:
.
Managers’ opinions and assessment results do match, with regard to the defects
problem. As the results show, defect-waste takes the first rank as a major waste
(approximately same as motion waste) with 20.5 perent.
.
Although motion-waste is not considered or mentioned by the managers as a
problem, the matrix shows that this type of waste can be the main cause of the
defects waste since there is a direct relationship between motion-waste and
producing defective parts. This type of waste is a significant issue but the
managers were not aware of it.
.
Process-waste is ranked third. This agrees also with the managers’ perception of
machine down-time being a problem.
.
Over-production-waste came in sixth position since the company’s policy
depends on matching produced quantity with demand. This is also proven by the
non-existence of excess finished products in a work-in-process form without a
production order.
.
Transportation-waste was ranked as the waste that is least likely to exist, (which
experience suggests is invariably the case), since the shop floor layout is
designed on a straight-line flow pattern, and no back-stream flows are allowed.
In addition, the factory has clear aisles for transportation with suitable distances,
which reduces the need for excessive transportation.
Table XII.
The company assessment
analysis
Score (Yj)
Pj Factor
Final result (Yjfinal)
Final result (%)
Rank
O
I
D
M
T
P
W
0.1126
228.48
25.76
10.1
6
0.1276
250.24
31.94
12.6
4
0.1762
295.68
52.10
20.5
2
0.2570
206.72
53.12
20.9
1
0.1683
144
24.23
9.5
7
0.3919
092.14
36.12
14.2
3
0.1515
206.08
31.21
12.3
5
.
Inventory- and waiting-wastes came in the middle positions as minor wastes.
These types of waste are usually incurred due to major waste, since inventory
usually is performed intentionally to hide the problems of motion- and
defect-waste.
As deduced from the assessment model, the first major type of waste that is more likely
to exist at the factory is motion-waste. The role of employees in producing defective
parts can not be ignored since it is clear that defects are produced due to either process
or operator problems. An investigation of the operators on the shop floor was carried
out, and revealed that the majority of operators were involved with receiving, shipping,
handling, storing and ergonomic activities. Both receiving and shipping activities of
parts or products were not always located in standard places. Operators needed to
walk to get the required parts, in addition to performing manual handling of materials
which led to extra movement and a high probability of damaging the bases of the
parts. Also, double handling of raw materials or finished goods was noticed where
materials were loaded first on the floor and then reloaded on pallets and forklifts to be
transported to the next station. Some tools, raw materials, and finished goods were not
adequately sorted. Also, non-ergonomic actvities were observed in the form of
unsuitable heights for both worker arms and backs, resulting in the need for arm
stretching, and over bending.
Moreover, the factory was suffering from high turnover of employees. This resulted
in frequent hiring of employees, who subsequently remained in their job for short
periods and which led to non-accountability of workers and lack of motivation. It is
found that many of the employees had insufficient training before being given the
responsibility of operating machines that resulted in them being unable to understand
their workstation requirements. Also, most of the jobs were not standardized, i.e. the
requirements of each job in terms of time, tools, and method were not documented. All
these observations led to the conclusion that motion-waste did exist at the factory. It
might be concluded, therefore, that the assessment results were thus satisfactory.
Conclusions
This paper presented a new model for performing an assessment of different types of
waste in a jobbing shop environment. The model incorporates the following new
features: wastes relationship, waste relationship matrix and assessment questionnaire.
The developed model is dependent on categorizing waste into the well-known seven
categories. Discussion covered the relationship amongst them, and provides the waste
relationship matrix, which utilized the measurement of the strength levels of the
relationships. It is argued that over-production-waste and defect-waste have the most
significant impact on all other types of waste. Conversely, inventory waste is found to
be highly affected by all others; while over-processing-waste is the least affected by
others. This is because it is not connected to material-, or man-types of waste.
All types of waste affect each other by different weights. However, existing
assessment models do not properly handle the weighing of the impact of these wastes.
Most research efforts have focused on tools for elimination of waste but without being
able to identify which type of waste causes an impact on the total generation of waste.
Consequently, the model is anticipated to play a significant role in identifying waste as
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820
a first step to elimination, and in helping solve problems related to the operational
environment of a jobbing shop.
The waste relationship matrix clarifies the relationships among the different
types of wastes. It provides an insight, in terms of weighing the contributions to the
existence of certain types of waste. The importance of the matrix derives from the
fact that it ranks the relationship quantitatively and classifies whether a certain
type of waste affects or is affected by other types of waste. On the other hand, the
waste relationship matrix (WRM) when integrated with the assessment
questionnaire can help a company in allocating or identifying the source of waste
and differentiating between the levels of waste and their effects on the performance
of the company. It thereby enables it to rank the significance of the waste types that
exist. The simplicity of the matrix and the comprehensiveness of the questionnaire
contribute to the achievement of accurate results in terms of identifying the root
causes of waste as seen in the case study. It has been noted that some of the waste
cannot be observed and acknowledged by managers.
The output of the model is a ranking for the existing waste in a jobbing shop.
This is important for a large variety of companies, for which the articulated waste
needs to be reduced or eliminated (based on their existence and the significant
contribution to the total existing waste). It is expected that the developed
assessment model will allow precise identification of waste generation. This has the
advantage of providing a focus for managers, reducing effort and time and bringing
about improved performance, in addition to quantifying the potential savings based
on waste elimination.
There are several interesting avenues for further research on this issue. One would
be matching waste elimination tools with waste allocation tools and studying the
allocation-elimination tools relationship. Another avenue would be to conduct a field
study to collect empirical data for the implementation of the developed assessment
model. Finally, it is also possible that this approach could be applied to the service
sector, taking into consideration that the definitions of each type of waste may change
due to specific requirements of the service sector.
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Further reading
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NY.
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