Work scheduling in a batch manufacturing system

Engineering

Management

In terna tional, 3 ( 1985 ) 153-l

64

Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands

153

L. Brennan and J. Browne Department of Industrial Engineering, University College, Gaiway Ilrelandj

B.J. Davies Department

of Mechanical Engineering, University of Manchester Institute of Science and Technology, University of Manchester, Manchester (U.K.)

ABSTRACT

This paper considers the question of work scheduling in a batch manufacturing environment in the particular con text of a dual-constrained job shop where resources of both machines and operators are limited. In particular, it considers the role which the concept of labour flexibility can play 5 improving the performance of a real life jo’, shop. The real life system is modelled with the aid of a digital simulation model. A series of experi-

ments is performed using the n-ode1 to test different degrees of labour flexibility and different labour assignment rules. It is concluded that the introduction of even a limited form of labour flexibility into the shop provides an improvement in the shop performance and that the assignment rule involving the Total Processing Time is superior to the other rules tested in ihe study.

INTRODUCTION

as “... a method by which the order in which batches are to be processed on one or more machines is determined”. Scheduling on the other hand, is a larger problem and involves desision making in areas such as batch sizing, operator allocation/assignment, dispatching or sequencing of batches onto machines, use of overtime, use of sub-contractors, and use of alternate manufacturing routes. Further, the schedulirg problem is dynamic as new batches constantly arrive and must be incorporated while the schedule must be re-evaluated in the light of the performance of the manufacturing facility (Browne et al., l9S2). In the context of this paper, work scheduling is seen as a restricted subset of the scheduling functions involving two major areas of decision making - machine sequencing and

Batch or Job Shop production is defined as the manufacture of discrete products in small batches or lots by a series of operations, each operation being carried out on the whole batch before any subsequent operation is started. The production system must be flexible and must use general purpose equipment in order to accommodate varying customer requirements and fluctuations in demand. The function “Production Control” is often termed Job Shop Control when applied to a job shop. Scheduling has been seen as a primary task of Job Shop Control and much research has been reported by Browne et al. A distinction is often drawn between scheduling and sequencing. Wild (1971) sees sequencing

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154

operator assignment. The machine sequencing problem - the problem of allocating m jobs to n machines where each job visits many if not all of the II machines and *;qrhere the processing time at each machine is known, is well reported in the literature. (See, for example, Conway et al., 1967). The operator assignment problem, i.e. the problem of deciding which operator should be assigned to one of a number of machines at a given point in time, is less frequently discussed. The two problems are of course inter-related, For example, let us consider a manufacturing system where p operators are responsible for m machines (p < m) and where an operator may only tend one machine at the time. If we look at the queues of work in front of each of the m machines then, of course, we can assign a relative priority to each individual batch using, for example, a “due date” or a processing time heuristic. Having decided on the most important batch at each machine, we may then compare the relative priority of batches as between machines ad, in this way, assign individual operators to machines. Then as batches become complete and operators are free, the cycle of allocating priority begins again. The problem under discussion here can usually be termed the dual constraint job shop scheduling problem; i.e. a job shop in which both operators and machines are considered to be constraining resources. Research has been reported on this problem - see, for example, Fryer ( 1973) and Holstein and Berry (1972). Fryer (1973) concluded that “In many cases, labour assignment decisions had greater effects on performance measures than dispatching decisions”. Rochette and Sadowski (1976) and Nelson (1967) report similiar work. Nelson concluded, based on a simulation study in which various combinations of labour assignment rules and dispatching rules were used, that assigning labour to the longest machine queue, combined with the SPT (Shortest Processing Time) sequencing or dispatching rule is most effective when the objective is to reduce mean job flow time. It is worth noting, however, that all of

the work reported here involves simulation studies of “hypothetical” manufacturing systems. For the review of the types of assumptions made in such work, the interested reader is referred to Day and Hottenstein (1974). It is of interest therefore to examine the problems of work scheduling in the context of a real batch manufacturing systems or job shop.

SYSTEM STUDIED The research undertaken on the dual-constrained job shop was based on a study of a real life job shop engaged in the manufacture of machine tools. Production is organized on a predominantly batch basis with 90% of parts for machines produced in batches. The job shop consists of 80 machines operated by 100 employees on a two-shift basis. In some cases, an operator is responsible for more than one machine. This means that since an operator can only manage one machine at any time, the othrzr machine for which he is responsible remains idle. With increasing sophistication of production equipment, multi-machine manning is now possible in more advanced production environments. However, the production equipment in the job shop under study was a conventional type requiring constant operator attention, thus preventing any scope for multi-machine manning. While some machines may be idle awaiting the attention of their assigned operators, other machines and their associated operators may be idle because there is no work waiting to be processed. Given the traditional structure of the workplace, established rigidities and demarcations between skills prevent the utilization of idle manpower at different Trrorkrrentres/departments. r:&atever Thus, ,)otentia.l might exist for improved utilization of facilities by the operation of flexibility in operator assignment is not exploited. However, given the degree of competitiveness in today’s trading environment, increased attention is being paid to the concept of flexibility in operator allocation in the production system, e.g. Groom and Goodhart

155

(1983), Lee (1982) and Painter and Parrish (1981). Plans at one company to improve productivity include a proposal for the introduction of full flexibilily for skilled workers, making obsolete the traditional rigid demarcation between skills or functions. Thus, it is of interest to determine if improvements can result in resource utilization levels, costs of inventory (Work in Progress and Finished Parts Stores) and the delive performance of the shop by the introduction of labour flexibility. Of course, the introduction of labour flexibility into the production system can involve extra costs in the form of training, transfer and higher wage costs. However, with labor flexibility, management has the opportunity of influencing shop performance by varying the assignment of men to machines. The purpose of the study reported in this paper is to assess the tidvantage offered by the introduction of labour flexibility into the dual constrained job shop described above. It is also concerned with determining which of a set of labour assignment procedures is most effective in improving shop performance. METHODOLOGY

EMPLOYED

A simulation model was developed and validated for the job shop under study. The simulation model mimics the production flow through the shop from the release of batches, through the operations at the various work centres to delivery of the completed batches into finished parts stores. The model is defined in terms of resources-machines and operators (subject to non-availability and breakdown), sanctions composed of batches, raw materials and various cost and process iriformation. The simulation is run for a fixed period and produces performance measures in terms of resource idleness costs, inventory costs and levels of delivery. These measures can be used as a means of assessing alternative strategies. A detailed description of the structure and operation of the simulation model can be found in Browne and Davies (1984). In addition, an outline of the simulation model is presented in the appendix.

LABOUR FLEXIBILITY

IN THE JOB SHOP

For the purpose of investigating labour flexibility in the job shop and associated labour assignments rules, three different set.s of experiments were performed along with the single experiment representing operation of the job shop without any provision for labour flexibility. This later experiment represents the base line for assessing the effects of operator flexibility. Three priority rules were used as a means of ranking machine centres for extra operator allocation. The three rules used were: 1. Rank machine centres according to the number of jobs awaiting processing in the machine centre queue. Idle operators are transferred to the machine centres with the most number of jobs waiting. centres according to the 2. Rank machine waiting time spent by the jobs in the machine centre queue. The machine centre whose queue contains the job with longest waiting time is accorded the highest priority. centres according to the 3 Rank machine total processing time involved in the jobs contained in the queue of the machine centre. The machine centre which has to carry out the largest amount of processing arising from the jobs awaiting processing at the machine centre is accorded the highest priority. For each of three priority rules outlined above, five sets of experiimen ts were performed. These consisted of varying the number of operator transfers which could be made from idle machines to priority machines from one up to five. In the system outlined here, a machine centre which is sufficiently high on the priority list (e.g. within the ^top three of the priority list, given that only three transfers are to be made) is only allocated an extra operator if it is being operated by an operator responsible for two machines. Thus, the intention of the procedures adopted is to increase the processing capacity of the machine centres which have large amounts of work waiting or to clear from queues jobs which are spending

156 an

excessive service.

amount

of time

queueing

chine allocation before any changes were implemented at the start of each week. This was and operators necessary so that machines could revert to their previous states at the end of the simulation week. Additionally, two new routines were developed. The first routine’s function is to check through each of the machine centres and identify those machines with no work waiting for processing at the start of each week. This routine is called at the beginning of each

for

MECHANISM OF LABOUR ASSIGNMENT To implement the above procedures in the model required a number of changes and additions. In all, a total of about 254) extra lines of program code was required. Arrays were set up to store the details of the operator/maIdentify machine zero at

and record centres jobs

start

with

in queue of week

pizggigsy allocation

y

of extra

operator

ranked r-emaining machine centre satisties criterion for extra operator

\

Yes

A

in machine/operator allocations

i,

<

Fig. 1. Routine

to hmdle

labour flexibility.

/

No

157

week. Thus, a list of possible operators available for transfer to priority machines is generated. At the same time, machine centres are checked according to the particular one of the three priority rules in force for allocation of the additional operators. A priority list of machines is compiled. The machine centre with the highest priority is then checked to see if its operating time can be increased by the provision of an extra operator with full responsibility for one of its machines on that shift. If, however, the machine centre in question has no machines being operated by an operator responsible for two machines, no change is made. (In total, up to ten such tests can be made if no suitable high priority machine centre is found. After the tenth test, the procedure is discontinued for that week). If the processing capacity of the machine centre can be increased by such a step, the list of possible operators available for transfer is examined. A possibility which must be considered before any transfer is made is that the operator being transferred is himself responsible for two machines. If this is the case, a check must be made to ensure that the two machines belong to the same work centre for which no work was found to be immediately available. If the operator being considered works within this machine centre, then the transfer can go ahead. If not, the list of possible operators is reexamined to select another operator for transfer to the priority machine. Assuming an operator is found suitable for transfer, the next function of the routine is to make the appropriate changes in the operator allocations. A message is also put out indicating the changes which have been made. If more changes are to be made, then the above procedure is repeated. Otherwise, a call is made to the second new routine for activation at the end of the simulation week. An outline flowchart of the first routine for switching operators is given in Fig. 1. The role of the second and much shorter routine is to reset the operator/machine allocation back to its original state at the end of

every week. This is necessary because the decision as to changes in the operator allocation is made at the start of every week. This decision is made with the original allocation of operators as the starting point.

RESULTS OF EXPERlMENTS The results of fifteen different sets of runs made using a form of operator flexibility are now presented along with the basic run. As noted earlier, three types of priority rules were employed as the basis for allocating “free” operators to other (busier) machines at the beginning of each of the weeks of simulation time. In addition, the number of possible operator transfers were varied from a minimum of one per week to a maximum of five per week. Thus, a total of five experiments were performed using each priority assignment rule. The shortest processing time sequencing rule is used with each of the priority assignment rules tested.

LARGEST QUEUE PRCORITY RULE The first set of runs to be performed related to the largest queue priority assignment rule. In essence, this rule was used to assign operators to machines with the Lzgest number of jobs waiting to be worked. The use of this system of labour assignin the perfomment produces %-----+*ements L+ti: ante of the job shop. For example, the costs of machine and operator idleness drop by the order of 20% for the case when up to five operator transfers can be made on the basis of the assignment rule, as compared to the case when no such assignment is possible. However, even for the case when only one such assignment is possible, there is significant reduction in these costs. The reduction (aF can be seen in Table 1) is progressive according to the number of operator transfers possible. Such a result is not unexpected though the potential for cost reduction revealed by the

158 TABLE 1 Results of experiments using Largest Queue Priority Rule Performance criterion

Basic run

No. of operator transfers 1

2

3

4

5

Machine and Operator Idleness costs (X $1000)

286.2

269.8

259.7

256.3

229.0

227.4

Work in Progress costs (x slooo)

11.7

12.1

11.9

11.8

12.0

12.1

Finished Parts Stores costs (x SlOOO)

19.4

19.7

20.0

20.1

20.1

20.2

Total Output (X 1000 h)

50.8

51.6

52.6

53.2

53.8

54.2

Cost Per Unit Output ($)

6.2

5.8

5.5

5.4

4.8

4.7

51.4

51.7

55.3

Percentage of batches delivered after 20 weeks

51

52

experiments is instructive. If operators, instead of being idle, are used to operate machines where large queues of work await processing, then the positive effect on both machine and operator utilization can be farreaching. The costs of Work In Progress sh ~(r a less well defined outcome in Table 1. With greater processing ability available at certain machines, the jobs in the shop are likely to be further processed than could be the case without operator transfer. However, depending on whether such processing caused jobs to advance into Finished Parts Stores more quickly, there could be a consequent reduction in Work In Progress costs. Such an outcome seems to occur to a varied degree among the runs performed. Work in Progress costs show an increase over the case where no operator transfer occurs, though this increase is not substantial and is not uniformly increasing as the number of operator transfers increases. This suggests that the extra processing time available contributed to some increase in Work in Progress but, judging by the scale of this increase, it must also cause an increase in Finished Parts Stores delivery rates.

--

54

Finished Parts Stores costs (as shown in Table 1) are more affected by the operation of the operator transfer system. There is greater variability shown in the costs incurred for the different runs and the costs increase with the number of transfers made. Total Output is also favourably affected by the use of the operator transfer system. The use of up to five operator transfers compared with no such transfers induces an increase in output of the order of 7 percent. Again, the level of Total Output produced increases according to the number of operator transfers made. Perhaps the most dramatic change is evident from the level of Cost per Unit Output for the different runs undertaken shown in Table 1. This variable shows a decrease of the order of 25 percent when up to five operator transfers are possible from the figure when no such transfers are possible. In line with the performance cf the previous variables, the reduction in cost per unit output varies with the number of operator transfers possible. The performance of the final performance criterion - rate of delivery of detailed parts after 20 weeks - is less dramatic. Some im-

provement does occur for each of the runs made involving operator transfer, but these are not consistently related to the number of transfers possible for each run. Nevertheless, a maximum improvement of the order of 8 percent over the zero transfer position is obtained. The different number of transfers possible on each run will impact differently on batches to be processed - some favouring batches containing major parts more t.han detailed parts and vice-versa. In addition, with the dual constrained job shop, some imbalance exists in the capacity of the shop which, even with limited operator flexibility, is not satisfactorily resolved. The rate of delivery of detailed parts is still much less than desirable. Nevertheless, it is clear from the results that the introduction of this (perhaps idealized) and extremely limited form of operator flexibility has had a very useful impact on the performance of the shop. No additional costs have been assumed in the model to cover the introduction of such a system of higher productivity (e.g. higher basic wage rate). Thus, the results produced are perhaps the most favourable possible under such a system. The

improvements in Cost per Unit Output and in Total Output have been considerable and would have a significant impact on the performance of the job shop if introduced in practice.

LONGEST WORKING TIME PRIORITY RULE A similar series of experiments were performed in respect of the second priority assignment rule considered. This rule involved assigning free operators to those machine centres with jobs with the longest waiting time. The results for these runs are presented in Table 2. Again, the use of this limited form of o;Derator flexibility using this separate priority rule provides improvement in the shop’s performance. For example, the costs of machine and operator idleness decrease substantially and in line with the number of operator transfers possible. The difference between the level of costs recorded for the case where no operator transfer is possible to the case where up to five transfers are possible is

TABLE 2 Results of experiments using Longest Waiting Time Priority Rule Performance criterion

Basic run

No. of operator transfers 1

2

3 -.

286.2

268.3

253.5

243.5

Work in Progress costs (x ~1000)

11.7

11.9

12.0

12.0

12.1

12.2

Finished Parts Stores costs (x SlOOO)

19.4

19.4

19.7

20.0

19.2

20.0

Total Output (x 1000 h)

50.8

52

53.4

54.4

53.8

53.2

5.7

5.3

5.0

5.0

5.1

50.5

51.4

52.6

50.5

Machine and Operator Idleness costs (X SlOOO)

Cost per Unit Output (E j Percentage of batches delivered after 20 weeks

6.2 51

-_

4

5

241 .O

240.7

53

160

of the order of 17.5 percent. This decrease results from the increased level of utilization of machines and operators involved in the use of the labour transfer system. The level of Work in Progress costs also increases with increasing number of operator transfers though the degree of change between the runs is not substantial. However, the picture produced for Finished Parts Stores costs is somewhat erratic and no clear pattern can be drawn. These results for Work in Progress and Finished Parts Stores are in direct contrast to those produced for the earlier priority rule. In that case, the level of Finished Parts Stores tended to increase with increasing labour transfer, while the levels of Work in Progress were somewhat erratic. This indicates that while both rules tend to increase the total processing undertaken in the shop over a fixed period of operation, the initial priority rule (longest queue assignment basis) is more successful in delivering batches into Finished Parts Stores. This conclusion &o gains support from the results produced for the rate of delivery of detailed parts into Finished Parts Stores. On this criterion, performance is again erratic between the different degree of labor transfers possible and no consistent pattern is obtained. Results for Total Output are in all cases above that obtained for zero labour transfer capability. However, they do not increase in a consistent fashion with increasing degree of labour transfers. These results suggest that the use of a rule which relates to the longest waiting time among the jobs waiting for processing at machines as a means of allocation of free operators is not necessarily optimum in its effect. It is certainly less reliable and consistent in its operation than the priority rule which involves consideration of the total number of batches waiting at the different work centres. While cost per unit output shows substantial reduction with the use of the operator trader system compared to the absence of such a system, the reduction does not vary directly with the number of labour transfers possible for each run. Compared with the

earlier run,: using the largest queue assignment rule, the reductions achieved are less in the case of higher numbers of operator transfer. Thus, while improvement in the shop performance is possible on some criteria, notably cost, the impact on other criteria is less consistent. In particular, delivery performance on detailed parts is not necessarily enhanced by the use of this rule. This may be explained by the fact that the queueing rule in operation for batches at the work centers is the shortest processing time rule. The priority assignment rule is more useful to machine centres where batches, because of their relatively long processing times (e.g. majors), have been forced to spend long periods queueing due to the priority selection rule for batches which is operated on these runs. As a result, the two prior%y rules in force in the shop for these runs tend to have a different impact on the operation of the shop, whereas the earlier priority assignment rule and the shortest processing time dispatching rule do not necessarily have a different impact on the shop’s operation. LARGEST TQTAL PROCESSING TIME PRIORITY RULE ‘The final assignment priority rule to be examined concerned the total processing time in the operations to be carried out on all bstehes waiting at a work centre. Priority in the assignment of additional operators was given to those work centres which had the largest amount of processing to be carried out on queueing batches. Again, runs were undertaken with the number of operator transfers varying from a minimum of one to a maximum of five for each run. The results of these runs are presented in Table 3. The operation of this system of operator transfer produced an improved performance in the job shop. The costs of machine and operator idleness once again decrease with a maximum decrease of the order of 24 percent. In fact, the results produced using this assignment rule outperform the results obtained ,!or the previously used priority rules. However,

161 TABLE 3 Results of experiments using Largest Total Processing Time Priority Rule Performance criterion

Basic run

No. of operator transfers 1

2

3

4

5

286.2

263.5

251.4

240.8

217.2

224.9

Work in Progress costs (x SlOOO)

11.7

11.9

11.8

11.9

12.0

12.3

Finished Parts Stores costs (x ElOOO)

19.4

19.4

19.8

20.1

20.1

20.2

Total Output (X 1000 h)

50.8

52.8

53.4

53.6

54.2

54.2

Cost per Unit Output ($)

6.2

5.6

5.2

5.0

4.6

4.7

50.5

51.9

52.6

53.5

54.6

Machine and Operator Idleness costs (X $1000)

Percentage of batches delivered after 20 weeks

51

while the results obtained generally show a reduction in costs related to the degree of operator transfer, this is not the case in moving from four operator transfers to five operator transfers. This su fgests that, while there may be some gain in allowing a fifth transfer, the overall impact results in a lower utilization of resources than that obtained with up to four transfers. The degree of change obtained in the costs of Work in Progress and Finished Parts Stores is limited. Overall, Work in Progress costs tend to increase with the degree of transfer possible. For Finished Parts Stores, there is some evidence of a similar trend though the degree of change involved is very limited. As expected, Total Output tends to increase in line with the number of operator transfers though there is virtually no change between an operator transfer level of four and five. Likewise, the rate of delivery of detailed parts int5 Finished Parts Stores tends to increase with the number of operator transfers allowed, though performance on delivery is still unsatisf&ory at less than 55 percent after 20 weeks. It is, however, superior to that obtained using the Longest Waiting Time

priority rule and is on average superior to the Largest Queue priority rule. The Cost per Unit Output criterion falls dramatically with a maximum reduction of the order of 26 percent compared to the run involving no operator transfers. Given the earlier results related to costs and output with up to five operator transfers, it is not unexpected to find that the run with operator transfers of up to four is superior on this performance criterion. It is, however, still superior to the remaining runs based on this priority assignment rule. The results obtained are uniformly superior to those obtained fou this criterion, using the priority assignment rule involving the Largest Queue criterion, and are on average superior to the results obtained for the Longest Waiting Time assignment rule.

COMPARISON BETWEEN PRIORITY ASSIGNMENT RULES All three priority rules Katie effect on the performance of the all cases, the cost of producing output drops substantially - in

a beneficial

job shop. In each unit of one case in

162

percent. This is achieved in the mgn by a higher level of utilization of resources which generally allows for the increased production of output. The use of the Largest Total Processing Time rule as the basis of determining priority in the assignment of cifree” operators produces the largest increase in utilization, while the use of the Longest Waiting Time rule is least effective in reducing the costs of machine and operator idleness A similar pattern obtains in relation to Total Costs involving Work in Frngess and Finished Parts Stores as well as Machine and Operator Idleness Costs. The Largest Total Processing Time performs best in reducing total costs. It also performs best in increasing the level of Total Output produced. The reduction in the level of Cost per Unit Output is greatest with the use of the Largest Total Processing Time priority assignment rule. The Longest Waiting Time priority assignment rule outperforms the Largest Queue priority assignment rule for lower levels of operator transfers (l-3) but for higher levels (4-5), the latter rule is better. There are small variations between the priority assignment rules on the rate of delivery of detailed parts into Finished Parts Stores. However, none of the assignment rules produces a satisfactory level of delivery, nor indeed does any degree of labour transfer attempted. This is probably due to imbalance in the composition of resources in the shop in the aftermath of the reductions made in resource composition. Of the rules tested, the Largest Processing Time assignment rule appears to offer most scope for improvement in delivery performance. It is of interest to note the similarity of the results obtained using the above system of labour flexibility with the results of a study by Eilon and Ghowdhury (1975) involving the concept of machine flexibility somewhat analogous to the system of labour flexibility employed in this study. A flexibility index (B was defined as a relative frequency with which the machine set (i.e. set within which a machine can replace any other for the perPO= of performing a particular operation) excess

of

26

applies. It was found that the greater the flexibility, the greater the reduction in job waiting time. Also, the improvement in waiting time levelled off as 0 increased. The improvement was most pronounced when @ was low. Such a scheme involving operational flexibility has parallels with the system of labour flexibility adopted in this study, with the effect of the number of labour transfers permitted parelleling the effect of the increase in probability/relative frequency with which the machirre set applies.

CONCLUSION This paper has examined the application of a form of labour flexibility to a real job shop with the use of the simulation model. It is clear from the results produced that, within the job shop structure modelled, there is scope for a considerable improvement in shop performance with the introduction of such a system. Three different types of labour assignment rules were modelled with the Total Processing Time rule proving superior. Performance also improves with an increase in the number of labour assignments made each week, but it is clear that the rate of performance improvement diminishes given the resource constraints and the nature of the system of fiexibility employed. However, from a management point of view, the improvement obtained from labour flexibility is encouraging.

REFERENCES Browne, J., O’Kelly, M.E.J. and Davies, B.J., 1932. Scheduling in a batch or job shop production environment. Engineering Management International, l(3): 173-184. Browne, J. and Davies, B.J., 1984. The design and validation of a digital simulation model for job shop decision making. International Journal of Production Research, 22(2): 335-357. Conway, R.W., Maxwell, W.C. and Miller, L.E., 1967. Theory of Scheduling. Addison-Wesley, Reading, MA. Day, J.E. and Hottenstein, M.P., 1974. Review of

163

sequencing research. In: D.C. Montgomery and W.L. Berry (Eds.), Production Planning, Scheduling, and Inventory Control - Concepts, Techniques and Systems. ABE, Georgia, AL. 5 Eilon, S. and Chowdhury, I.G., 1975. Studies in a simulated job shop. Proc. Inst. Mech. Eng., 189(3): 417-425. policies in multi6 Fryer, J., 1973. Operating echelon dual-constraint job shops. Management Science, 19(9): 1001-1012. D., 1983. Britain’s 7 Groom, B. and Goodhart, productivity. Enter the jack-of-all-trades. Financial Times, August 17 th. 8 Holstein, W.K. and Berry, W.L., 1972. The labour assignment problem: an application of work flow structure information. Management Science, lS(7). 9 Lee, M., 1982. Danger: men at work. Management Today, May. 10 Nelson, R.T., 1967. Labour and machine limited production systems. Management Science, 13( 9). 11 Painter, C.W., Parrish, D.J., 1981. Flexible labour systems. The Production Engineer, Ncvember. 12 Rochette, R. and Sadowski, R.P., 1976. A statistical comparison of the performance of simple dispatching rules for a particular set of job shops. International Journal of Production Research, 14( 1): 63-75. 13 Wild, R., 1971. The Techniques of Production Management. Holt, Rinehart and Winston Ltd., London.

APPENDIX The simulation model constructed with the aid of GASP IV* - a combined continuous/ discrete Fortran based simulation language is designed to follow the passage of batches through the shop and includes all the relevant activities of all the operators and machines which take place within the machine shop. As a result of this design, all the production activities which take place within the machine shop are reproduced by the simulation model. The model simulates the batch production of components within the machine shop. The important entities within the system and their activities are modelled. The entities involved are: Raw materials *Pritsker, A. Allen B., 1974. The GASP XV Simulation Language. Wiley Interscience, New York.

Machines Operators Tooling Manufacturing documentation Batches and sanctions Materials handling equipment Finished parts Management. The logic of the model involves the release of batches into the machine shop. For each batch released, raw material availability is checked. If the material is available in stock for the batch, it is assigned to the particular machine queue for its first operation. (If raw material stock is inadequate, the model logic authorises the placement of a raw material order and subsequently models its receipt into raw material stores.) Given that raw material is available, a check is then made on the status of the machine and operator. If either or both is unavailable (and no alternatives are possible), the batch is placed in the appropriate position in the machine queue. Otherwise, the batch is loaded and processed on the selected machine. When the processing time has elapsed, the batch is unloaded from the machine. If all required operations are completed on the batch, it is placed into finished parts stores to await assembly. Otherwise, the details of the next operation are determined and the procedure outlined above repeated. The work queue in front of the previous machine is also examined and a batch loaded onto it. The simulation proceeds according to the above logic. The model operates using reallife production data, resource data and on the basis of the control run parameters assigned to it. In addition to the actual simulation logic, the model produces output reports on a regular basis detailing such information as: Machine and Operator Utilization Levels Inventory (Work in Progress and Finished Parts Stores) Levels Waiting Times Output Levels Delivery Rates. In this way, the performance of the shop

164

can be assessed and alternative strategies evaluated. The machine shop modelled consisted of approximately 80 machines and 100 opera-

tors. Some of the machines are operated on a two-shift basis. The shop Ilandles about 1500 different batches.