E L S E V I E R Int. J. Production Economics 52 (1997) 47 -53

international journal of

product!on economics

A conceptual model for disruption causes: A personnel and organization perspective

J o h a n E r i c s s o n * , P e r D a h l 6 n

Lund Institute of Technology, Department of Production and Material Engineering, Lund, Sweden

Abstract

Considering that more and more western companies are working in the JIT-philosophy with smaller and smaller buffer stocks it is important to increase the knowledge of how disruptions arise in manufacturing systems. This paper describes as investigation of disruptions (downtime, rejects, speed losses) at 12 different Swedish manufacturing systems.

With the help of a model which we have developed, the underlying causes of different disruptions have been mapped for the investigated manufacturing systems. The special conditions found in Sweden during the last years have motivated us to include factors outside the company in the developed disruption model.

Keywords: Disruption; Manufacturing system

1. Background and discussion of problems

In Europe and in the USA we have with admir- ation and fear noted the Japanese successes within different branches of industry, for example cars and consumer electronics. The success seem still more impressive bearing in mind that the expansion has occurred parallel with a steadily growing Yen- value. Part of the explanation for the Japanese wonder can be deduced from the large increases in productivity that have been reached with the help of the new industrial concept, which began to be developed after the second world war by Taiichi Ohno, Shigeo Shingo and others at Toyota Motor Company. We choose to call this new concept "lean

* Corresponding author.

production" as defined by Womack et al. (1) in "The Machine that Changed ~he World".

One of the more central parts in lean production is the Just in Time (JIT) philosophy. With the help of very small stocks and buffers the production shall start exactly when the need arises. Beside the direct earnings such as reduced capital tied-up, handling costs, need for storage rooms etc., the low stock level at JIT-product ion leads to indirect sav- ings when the company is forced to take care of the various disruptions occurring in the production. In practice, this means that in successful J IT-com- panies, small stock levels are used as a tool to reduce disruptions in the form of machine down- time and rejects. In contrast to traditional mass production, lean production contains a built-in concept, in order to continuously reduce costly disruptions.

0925-5273/97/$17.00 Copyright © 1997 Elsevier Science B.V. All rights reserved SSDI 0925-5273(96)00055-2

48 J. Ericsson, P. Dahl~n/lnt. J. Production Economics 52 (1997) 47-53

Most experts treat the fact that the JIT philos- ophy calls for continuous work with reduced dis- ruption and losses along the production flow. Oishi [2] deals with the necessity of short setup time, small breakdown frequencies and small scrap losses. Ames [3] points out in his article Total Quality Control: Necessary Foundation for Just- in-Time that the value of reducing all "predictable and unpredictable losses due to rejections of part and materials". Miller and Vollmann [4] consider that JIT first can be reached after succeeding in reaching stability in the production.

Many of the successful company that are work- ing according to the JIT principle have managed to reduce their disturbance level with help of the Japanese TPM-concept (Total Productive Main- tenance), Nakajima [5]. According to the TPM- concept, the different types of disruption that occur in a manufacturing system can be divided into the following three groups:

(1) low time utilization of production equipment (downtime losses), (2) rejects and rework (quality losses), (3) reduced operating speed rate (speed losses).

When disruptions occur in the production it is generally a series of incidents that in the end has resulted in a visible disruption, for instance a machine breakdown. The breakdown can, for example, be linked to poor machine maintenance which, in turn, can be related to organizational and staff related problems. When the efforts finally are made in order to reduce the actual down time, the underlying reasons should be handled, instead of the symptoms. In the area of quality, there is a long tradition of using a "Ishikawa (fish-bone) diagram" for mapping how a series of incidents finally could result in a quality disturbance. Another concept that shows a close resemblance to the "Ishikawa diagram" is Taiichi Ohnos "Five Why's'. Womack et al. [1] gives an example of how to use the "Five Why" concept for linking a inadequate product quality to a poor working environment according to the disruption chain below:

Lack of product quality (rejects) - Why? machine is maladjusted - Why? poorly educated operator - Why? labour turnover - Why? monotonous work in a noisy environment.

Womack et al. [1] complete the example by emphasizing that the underlying causes almost always seem to be of an organizational nature. This conclusion is partly confirmed by Hammer [6] who, in his study of 13 FMS systems, established the fact that the machine down time more often could be connected to deficiencies in the ograniz- ation than errors in the technical system. Together with our own experiences from disruption analyses, this shows that qualification and motivation of the personnel are more important than the technique being used to reach higher quality and productivity in the process. The big difference between the Japanese and the western production system is not in the technical system itself but how the technical parts in the manufacturing systems are controlled and utilized which, in turn, is determined by the personnel working in connection with the produc- tion system. When reducing disruptions it is there- fore important to analyze the different factors influencing the staff's capabilities and motivations to constantly reduce disruption occurrence in the manufacturing process.

2. Purpose and limitations

The purpose of the following paper is to derive the underlying causes of disruptions occurring in the production process. According to the earlier mentioned TPM-concept all the registered disrup- tion have been classified into (1) down time, (2) rejects and (3) speed losses. The result shall be presented in the form of a model, usable as an aid in combating disruptions. A special interest will be directed to analyze the personnel related factors influencing disruption occurrences.

We have studied machine controlled manufac- turing systems in Swedish mass manufacturing companies. As the machine down time accounted for over 80% of the measured disruptions the in- vestigations were concentrated to clarify these.

3. Data and methods

We have mapped the disruptions at 12 different manufacturing systems for about 100 h per system.

J. Ericsson, P. Dahlkn/Int. J. Production Economics 52 (1997) 47-53 49

The manufacturing systems are chosen from six Swedish companies working within different indus- tries giving us a wide range of material. When a disruption occurs in most of the studied cases it was difficult to define the whole disrup- tion chain directly. The down times arising during the scheduled time were therefore first registered and classified according to the following three levels: Level 1. If the down time had been able to be foreseen at least 24 h before it occurred, it was classified as planned. The opposite was named un- planned. Level 2. Depending on the reason for the down time, it was classified into one of the following groups: maintenance, labor, setup, others. Level 3. The reason for the down time is here specified in detail.

In the next step, the most important down time causes were selected. After that, the analysis began with deriving the underlying down time causes from the specified down time reason in level 3 via the disruption chain down to the original cause by using Ohnos 5 why-method.

Unplanned absence and staff turnover are de- fined as one of the underlying factors in the disrup- tion chain. Liukkonen and Gr6jer [7] have shown a variety of disruptions and costs caused by absen- teeism and staff turnover in Swedish companies. Stone [8] and Kivenko [9] examined these disrup- tions in the USA. Depending on purpose and perspective, different researchers have designed different models in order to explain and predict staff turnover and unplanned absenteeism.

The models are generally based on the March and Simons [10] model concerning the individual worker's ability and motive for being present and staying with his old organization. In a major re- search study Steers and Rhodes [11] organized a large number of empirical studies showing the correlation between absence and a variety of sundry factors in a systematic framework. Jackofsky [ 12] created a model predicting job turn- over that is an extension of March and Simons hypothesis to predict organizational withdrawal. The job turnover model includes movement be- tween organizations as well as movements within organizations.

Instead of March and Simon's method of looking at the individual worker, we have chosen a per- spective where we, from the employer's point of view, have designed a model that divides different factors into: 1. external influence factors and 2. internal influence factors. The external factors are those which cannot be influenced by the individual company. These factors are instead dependent on decisions and occurrences in the company's surroundings such as political decisions, economic situation and biological causes such as flu epidemics and so on. Internal factors are mainly motivation and load factors which can be related to the work oganization and the work environment, that means factors which the individual company itself can influence.

The external factors have been studied from a macroperspective. Statistics for attendance and staff turnover have been correlated to external factors influencing attendance and staff turnover in Swedish workshops. The external factors influence both the ability and the motivation in the tradi- tional model of March and Simon. For example, the external factor, unemployment, can according to Jackofsky, influence the employee's ability to get a new job, at the same time as in the model of Steers and Rhodes it influences the motivation to be present.

The internal factors also affect both the ability and the motivation of being present and staying in the organization. For example Porter and Steers [13] and Hackman and Oldham [14] found that a company, by improv- ing the work oganization, can increase the motivation of being present and staying in the oganization. At the same time the ability to attend will rise when the amount of work injuries caused by an unhealthy working environment decreases.

We have studied the influence of internal factors on sick leave and staff turnover in a case study where the company tried to increase the working motivation through a number of actions. We studied the development of the absence and turnover before and after the realization of the project.

50 J. Ericsson, P. DaMOn~Int. J. Production Economics 52 (1997) 47-53

4. Results

The down time and rejects for some of the inves- tigated manufacturing systems are listed in Table 1. In column 2 and 3 from the left, all the down time for each group are presented as a percentage of the total production time according to level 1 and 2. The rejects are presented as a percentage of rejects from the total number (or weight) of parts that have been manufactured.

When we started to derive the underlying reasons for the registered disruptions that were 0 described in level 3, we came in contact with the technical system in the form of manufacturing equipment and the personnel whose assignment mainly was to control or provide material, spare parts, etc., to the technical system. The personnel related disruptions could either be attributed to the operators interest in being present at the place of work (so called "labour stability") or the fact that the present personnel is not acting in a desirable way (work oganization).

A model describing disruption occurrences with the help of these three factors; technical system, work oganization and labor stability were put to- gether according to Fig. 1. The first two mentioned factors were shown to be mainly influenced inter- nally by the company. Personnel stability were observed to be connected to both internal and external factors.

The example given by Womack et al. [1] showed a disruption chain represented here by 1 ~ 3 ~ 4 -+ 5. The machines technical construc- tion caused monotonous work with a high noise level resulting in a bad working environment for

the operator (arrow 1). This resulted in a high staff turnover (arrow 3) which in its turn complicates the education of the operator (arrow 4). Lack of educa- tion and practical knowledge finally results in the machine being adjusted incorrectly, after which a large share of manufactured details are scrapped (arrow 5). For disruption chains containing the box "labour stability" a certain caution must be taken as it is sometimes difficult to decide if alterations in labor stability depends on internal (arrow 3) or external (arrow 7) factors. The risk of confusion can be minimized if both the internal and external fac- tors are analyzed during the actual period of time.

The results from our investigations show many different disruption chains illustrating our model. A few examples of these are: • The disruptions at a surface mounting line de-

pended mainly on the lack of material for elec- tronic components. The underlying causes were shown to be bad working routines and an incon- venient distribution of work in the planning de- par tment (arrow 5).

• The next example is taken from a line for machin- ing. The design of the products meant that the clamping could not be made at the same place on different variants. A change in the design resulted in a standardized clamping which reduced the line's adjustment time to half. Disadvantages in the old design caused manual work routines which increased the adjustment time, according to the disruption chain: 1 --* 5. The opposite dis- ruption chain is pointed out by Nakaj ima [5], who gives the relationship between poor main- tenance organization and the occurrence of ma- chine break downs, disruption chain: 2 ~ 8,

Table 1 Machine down time and rejects at 6 investigated manufacturing systems (source: Ericsson [15]).

Type of manufacturing Planned stop Unplanned stop system

Labour Maintenance Set up Other Labour Maintenance Other

Operating time

Rejects (scrap)

Synchronous pressline 1% Notching machine 0% Line for machining 2% Granulation (process industry) 1% Injection moulding 4% Robotized assembly line 6%

0% 10% 3% 3% 28% 2% 5% 15% 1% 14% 12% 1% 2% 11% 5% 3% 17% 3% 0% 11% 1% 3% 10% 0% 0% 3% 4% 5% 19% 4% 2% 0% 1% 2% 28% 5%

53% 52% 57% 74% 61% 56%

1% 2% 2% 5% 3% 1%

J. Ericsson, P. Dahl~n/lnt. J. Production Economics 52 (1997) 47-53 51

I Disruptions • machine downtime | • rejects | • speed losses •

/ t \ Effects . . . . . . . . . . . - z _ _ _ _ _ 4 - - - - - - - % . . . . . . . . . . . . . r . . . . . . . . . . . . . . .

f / ~'~ / F LabOur .ta"bility "~ [ lTechnlcal system / s l" L J L J L" absealteeism

\x I / %, 3

\ VWork organization - ~ / / 4 f~xteroal factors ~k] • work satisfaction J / | * unemployment |

~ 4 t ] • work enviroment l * sickness benefits l

Fig. 1. Causes and effects of disruption in manufacturing systems.

• At a robust line for the joining of different plate items three operators were working. When one of the group members was absent the machine down time increased considerably due to large work strain on the remaining two operators. De- pendent on if the reason for absence was due to internal or external factors the following disrup- tion chains can be: 3 ---,6,1 --,3 --*6, or 7 - , 6 .

The next example shows that major change in work oganization for a whole department resulted in big improvements of their labor stability and finally the departments productivity and quality. • In a study of ABB Control AB in V~isteras,

Sweden by Dahl6n [16], it was shown that the company had succeeded in influencing the ab- sence and staff turnover at one department by changing the work oganization (arrow 3). A change of layout where the manufacturing was divided into separate work cells, made it possible to increase the blue collar peoples responsibility for production scheduling, quality assurance, etc. In a period between 1988 and 1990, the sick leave decreased from 14% to 4% at the same time as the staff turnover almost ceased after having been about 40% per year. The company could also

show that the defects dropped from 15% to 1% and that the throughput times dropped from 12 to 1 days. The disruption that where eliminated correspond to the disruption chains: 3--, 6 or 3 --, 4 ~ 5. According to the Swedish employers confederations (SAF) who continuously measure the sick leave of those employed within the pri- vate industry, the average absence due to illness of blue-collar workers was 12.6% 1988 and 12.1% 1990. In the light of these facts ABB's reduction of absence due to illness by a factor over three is very dramatic. A parallel study of the external factors showed that these were very stable during the actual period of time. The unemployment in Sweden decreased a little from 1.8% 1988 to 1.7% 1990 and rules of sickness benefit and the marginal taxes were mainly unchanged. In the circumstances of the very large change being measured at ABB it can, for very good reasons, be said that the changes were mainly the effect of the internal oganiza- tional changes being carried out under the T 50 project.

The last example shows the relationship between external factors and the labor stability for the total work force in Sweden.

52 J. Ericsson, P. Dahl~n/Int. ~L Production Economics 52 (1997) 47 53

25

24

23

,,~ 22

'~ 21

l:1 20

19

18 1971

I

unemployment ~ 1 3.4

/ X 3.0

41 iii iii)i:iiiiiiiii . . . .

~." i ~ . ~ 2.2

: : : : I I t I I I I I I : : , " 1 . 0

1973 1975 1977 1979 1981 1983 1985 1987

Fig. 2. Sick leave and unemployment annually 1971 1987 [7].

Z

• External factors influence on the labor stability (arrow 7) can be exemplified with the help of the diagram below (Fig. 2) showing the relationship between sick leave and the level of unemploy- ment in Sweden. Another example of external factors (arrow 7) arose in connection with the strong economic decline that Sweden was hit by in 1990. During the following two years up to 1992 large changes in external factors occurred. Unemployment was trebled from 1.7% to 5.3%, the regulations regarding sickness benefit became stricter and margin taxes were substantially de- creased. Changes in all three cases gave rise to heavily increased incentive for the personnel to be present at their places of work. The personnel stability increased while among others, can be exemplified with the help of statistics for absence due to illness as this decreased from 12.1% in 1990 to 9.1% in 1992 (SAF). The main reasons for the absence due to sickness can be connected to the changes in external factors.

The results show that during the last ten years Sweden has offered unique conditions to study and analyze the two personnel related factors in the production disruption model. This depends on the dramatic changes being carried through both with- in and outside Swedish companies. A few of the most important changes are: • Very radical changes of the working oganization

at few industries gave the work force consider-

ably increasing internal motives and possibilities to work towards a decreased disruption appear- ance.

• During the late eighties external factors gave Sweden, from an international point of view unusually low unemployment numbers, high marginal taxes and an expensive sickness benefit system. These factors created an external milieu giving small incentive to be present at the place of work. The Economist [17] describes these ex- ternal factors in a special issue about the Swedish economy and points out the connections with a relative high absence due to illness.

• During the first two years of the nineties all the above external factors have changed. The result was that the motivations to be present at the place of work increased significantly.

5. The value of the results for practitioners and researchers

We hope that the model above will increase the understanding of how disruptions arise in produc- tion. The model shows the importance of co- ordinating the disruption analysis to cover both the mechanical system and the work oganization around the manufacturing system. An increased knowledge of the underlying causes of a disruption makes it possible to attack and eliminate the root of

J. Ericsson, P. Dahldn/Int. J. Production Economics 52 (1997) 47-53 53

the d i s r u p t i o n i n s t ead o f h i d i n g the p r o b l e m t e m -

p o r a r i l y by so lv ing o n e o f its s y m p t o m s . As d i s rup -

t ion , in the f o r m of m a c h i n e d o w n t ime a n d re jects

a re expens ive , r e d u c i n g the d i s r u p t i o n level is im-

p o r t a n t for al l types of c o m p a n i e s . T h i s is espec ia l ly va l id for the l ean c o m p a n y us ing J I T , w h e r e a l o w

d i s r u p t i o n level is a necess i ty in o r d e r to get an eff ic ient ly f u n c t i o n i n g p r o d u c t i o n .

References

[1] Womack, J., Jones, D. and Roos, D., 1991. The Machine that changed the world. Harper Perennial.

I-2] Oishi, O., 1989. Building a JIT pyramid. SME Technical Paper MS89-402.

[3] Ames, R.G., 1985. Total quality control: necessary founda- tion for just-in-time. Proc. 28th Annual Int. Conf. Proc. - Amer. Production and Inventory Control Society pp. 423 427.

[4] Miller, J. and Vollmann, T., 1985. The hidden factory. Har. Bus. Rev., Sept./Oct., 142-150.

[5] Nakajima, S., 1989. TPM Development Program - Imple- menting Total Productive Maintenance. Productivity Press.

[6] Hammer, H., 1992. The economics of flexible manufactur- ing systems contingent upon operating and service person- nel. Eur. Prod. Eng., 16.

[7] Liukkonen, P. and Gr6jer, J-E., 1990. Assessment of costs in the work environment. Arbetarskyddsn~imnden (in Swedish).

[8] Stone, T., 1980. Absence control - is your company a can- didate? Personnel Administrator: 77-84.

[9] Kivenko, K., May 1984. Employee absenteeism - the det- onation of productivity. P & IM Rev. APICS News: 52-55 and 70.

[10] March, J. and Simon, H., 1958. Organizations. New York: Wiley, New York.

[11] Steers, R. and Rhodes, S., 1978. Major influences on em- ployee attendance: a process model. J. Appl. Psychology, 63: 391-407.

[12] Jackofsky, E., 1984. Turnover and job performance - an integrated process model. Acad Mgmt. Rev., 9(1): 74-83.

1-13] Porter, L. and Steers, R., 1973. Organizational, work, and personal factors in employee turnover and absenteeism. Psych. Bull., 80: 151-176.

[14] Hackman, J. and Oldham, G., 1976, Motivation through the design of work-test of a theory, Organizational behav- iour and human performance, 16: 250-279.

[15] Ericsson, J., 1992. Machine downtime costs millions. Verk- st/iderna, 3:28-32 (In Swedish).

[-16] Dahl6n, P., 1991. Work organization in change. Verk- stiiderna, 7:20-24 (In Swedish).

1-17] The Economist., 3 March 1990. A survey of the swedish economy. 4 22.

[18] Ohno, T., 1988. Toyota Production System - Beyond Large Scale Production. Productivity Press.

[19] SAF., Statistics of time spending - Mean values, 1988-92 (in Swedish).

[20] Shingo, S., 1989. A study of the Toyota Production System from an Industrial Engineering Viewpoint. Productivity Press.