- Email: [email protected]
Cellular design for injection moulding shop
Pergamon
Computers ind. Engng Vol. 35, Nos 3-4, pp. 487-490, 1998 © 1998Published by Elsevier ScienceLtd. All rights reserved Printed in Great Britain PII: S0360-8352(98)00140-5 o360-8352/98 $19.00+ 0.o0
CELLULAR DESIGN FOR INJECTION MOULDING SHOP Ebrahim Shayan industrial Engineering Group IRIS Swinbume Univerisity of Technology-Hawthorn, Vie 3122, AUSTRALIA FAX: +613 9214 5050 EMAIL: [email protected] ABSTRACT This paper attempts to highlight the fact that application of GT does not always lead to a productive cell formation regardless of the algorithm used. The reason is that some practical issues are impossible to be included in the GT process. However a careful systematic IB analysis of the cell formed by GT may reveal new opportunities for improvements eventually leading to a more effective cell. A successful case demonstrates the idea. © 1998 Published by Elsevier Science Ltd. All rights reserved. 1. INTRODUCTION A cell is a set of machines (work stations) grouped to provide all the necessary activities for processing (servicing) of a family of products (items). Theoretically a single machine or a set of manual tasks can be considered as a cell. Some cells may have several machines or a combination of machines and other manual work stations. The major impact of a cell is that it provides a flow type environment for all in the family. Parts enter from one end in a primitive form and out, as a distinguished product, from the other end. An immediate result is the sense of ownership generated in the team of people working in the cell due to their identifiable impact on the parts made in that cell. In addition tremendous advantages are received from cells in forms of less inventory due to flow, less handling due to closeness, availability of more immediate assistance in resolving problems due to multiskilling, mutual relief and the like. All these tend to improve moral and quality while reducing lead time, errors, rejects, scraps which translate into financial gains. Literature is full of examples regarding achievements of different companies using cellular operations. Reduction of lead time from several weeks to hours is quite a common outcome [1]. In most cases the idea of forming a cell emerges from these envisaged benefits. It is utterly important for people involved to develop a thorough understandings and belief in the advantages. The expert is then in a position to challenge obstacles to develop a cell out of any possible situation, as is the concern of this paper. However before the case is explained it would be worthwhile reviewing the direction of research in cell formation.
2. Cell Formation There are several problems that have to be resolved to form a production cell. The first logical problem is to identify which machines have to be in the cell and what group of products should be in the family produced by the cell. This is the well researched area of Group Technology (GT) [2], [3], known as cell formation. Cluster identification algorithms attempt to develop an abstraction by forming a matrix of part-machine matching which is manipulated to, form clusters of related machines-parts. Complete clusters form the independent cells. Common machines between overlapping cells are either shared or when feasible duplicated. Despite the attempts for inclusion of more constraints into the cell formation scenario, most of the research work are simplified representations of the reality where some practical constraints have been intentionally relaxed to make the algorithm work, sometimes resulting in a non-productive cell. Nonetheless the grouping achieved through GT are good starting points, particularly when a large number of parts are involved. Several other methods have been developed for GT including similarity coefficient methods, sorting based algorithms, extended cluster identification [2], [4]. Little research appears to be ongoing about the necessary transitional tasks from the cell formulation results to productive cellular operation [5]. Some relate the issue to problems in inadequacy of process plan information and accordingly recommend solutions to increase group-ability. The author's experience shows 487
488
Selected papers from the 22nd ICC&IE Conference
that, in addition, serious problems may occur due to the nature of the cell elements. After all, most of the cell formation algorithms ignore several practical factors such as set-up time, material handling and other technological constraints. Accordingly to implement the cell for operational effectiveness consideration of practical issues is vitally important. The logical cell design must be transferred to a physical reality by layout design of the cell, " intra-cell or machine layout problem". This is another new field of research and developmenrin industrial engineering which has significantly progressed in recent years. There are two types of approaches to cell layout design which are of interest in this paper. The first approach considers an area as a grid and attempts to put machines, as blocks, into the grid cells in such a way to optimise some objectives such as minimising total handling, maximising throughput and the like, as in Quadratic Assignment Problems, QAP, formulation. Several algorithms have been developed to solve these problems [6]. Recently random search algorithms such as Simulated Annealing [7]and Genetic Algorithms [8] are gaining popularity in this field. The second approach to intra-cell layout considers the floor as a continuous plane where machines can be located at any unrestricted area. The question is to find the exact location of machines which optimises certain goals, eg. Minimising total area. Formulation of this problem is more complicated. However it has the advantage of continuous variables which can be handled easier. Bazergan[9] has applied Simulated Annealing and Tavakkoli and Shayan[10] attempted to solve the problem using Genetic Algorithms. The third stage may be considered as the overall layout of several cells within the shop floor, "inter-cell layout". A drawback in the existing approaches is the lack of an integration between GT, machine layout and inter-cell layout problems. As a result, global solutions may be sacrificed for the optimal local solutions. 3. The Case A plastic moulding company is experiencing difficulties in filling the orders on time under pressure on price competition. In particular one product, wheel cap, supplied to an automobile company is facing serious problems, edging at losing customers. The objective is to improve the flexibility of producing different eolours, cheaper while ensuring that quality is not compromised. The existing manufacturing cell to produce car wheel cover products consists of a number of work stations including injection moulding, sort and paint them, pack and dispatching to customers. However the present cell is not productive due to the fact that the GT design did not subject the solution procedure to practical considerations. To understand the performance of the current operations a standard industrial engineering study was conducted to measure and document the activities performed in the following sequence: 1. 2. 3. 4. 5. 6.
injection mould of wheel cover trimming by operators cooling down of caps packing in a box move to paint area unpack box
7. 8. 9. 10. 11.
put into paint booth conveyor stay on conveyor to dry pack in box move box to store move box from store to production line
Injection moulding machine is a considerable investment that cannot be replaced or redesigned, despite its inflexibility, a constraint we have to live with. The cycle time of the injection moulding machine is 68 seconds with production capacity of 1200 wheel covers per day. The moulded wheel cover is released from the gate, picked by a robot and delivered to the operator who then does visual quality checks for 7 seconds, sprue cutting 4 seconds, wire fitting 5 seconds, foam lining 2 seconds, a total of 25 seconds. The wheel covers are then stored in 3 bins of 120 capacity each. At the end of each shift the bins are transferred by a lift truck to the paint booth, taking 10 minutes. The bins are stacked at the paint booth waiting for availability of manpower to run the paint booth. The bins are taken from the stack and covers are removed and put in the paint booth, taking 15 seconds for each cap. Painting is a complicated bottleneck operation, deserving more explanations. The new design aims mainly to resolve the bottleneck problem. 3.1 PAINTING OF MOULED COMPONENTS Presently there are two types of painting in practice for plastic moulded components. Base coat is the original colour applied initially. Clear coat is the second transparent layer applied if necessary. Ordinary
489
Selected papers from the 22nd ICC&IE Conference
car models use base coated wheel covers only. But wheel covers for special model have both base coat and clear coat painting. Base Coat Operation: The operator takes a component from the bin for spray painting, 30 seconds, then hangs the component onto an overhead conveyer to dry out while travelling around for 25 minutes. Covers are then packed into small boxes which are stored again in another bin, ready for shipping to the assembly plant. However normally there is a delay time as bins are never shifted immediately after they are full. The daily requirements of the assembly plant is 460 wheel covers approximately. Base Coat and Clear Coat: The procedure for this type of painting is more elaborate. The cover, picked from the bin, is loaded on the conveyor and passes through the Triehloroethane chamber at 70°C. This operation removes the mould release agent from the component. Then the cleaned cover is passed through an antistatic chamber. This is for removal of static electricity from the component. The component is then passed through the oven to release the mould stresses. The painting follows with an initial base coat followed by a final clear coat. The clear coat contains Isocyanide and is dangerous to human health. The baking time for this paint is 30 minutes. The current rejection rate is 5% mainly due to over painting or dirt on the surface of the moulding. Painting is done normally twice a week. The number of components being painted is 320 in each batch.
3.2
Analysis of the current production
The conservative value added time period including 25 seconds for wire fitting and the rest of the operator's activities, 30 seconds for painting and 15 seconds for final packing, totals to (30+25+15)=70 seconds per wheel cover. The moulding time is the same in the new solution. The total time (average) taken for a wheel cover to go through the whole process was measured at about 100 hours. That is an efficiency (value added time divided by total time) of about .02 percent. Acceptance of this situation has brought about other side effects such as lack of accountability and absence of any operators' involvement in decision making and process improvement, a culture of 'no care'. This was a powerful motivation to embark on the study of the new approach as follows: 4. Improving the Cell Layout Design and Operation In order to Come up with a solution, the current situation must be understood, challenged by serious questions, and at each step alternative innovative solutions be considered to resolve the overall problem. Consideration of operators involvement in the solution process and later operation is a key success factor. The main bottleneck, painting, drove the new cell design activity. Changing from one colour to another with the current booth was unacceptably time consuming. Some preliminary tests revealed that there is no reason for cooling the wheel covers down to ambient temperature before painting. These fmdings suggested a need for a quick changeover of paint colour right after moulding. The existing high capacity of the paint booth, also being utilised for other jobs, and its size made its installation next to the moulding machine unsuitable. Requirements for flexibility in colour variations resulted in design of a small paint booth capable of handling a range of colours with no significant set-up. Resolving this problem integrated the cell operations and collapsed it into a small area. The modified cell layout consists of the following elements:
4.1 1. 2. 3. 4. 5.
T h e new Cell The injection moulding machine (as before) Two temporary storage tables Two conveyors A small painting and air blow drying unit Packing area
r-1 ]Operator
AirOut~~p~~
7-S---1
The storage tables (2) can hold thirty wheel covers in five stacks each. Air may be blown in, if necessary, for faster cooling of wheel covers while stacked or being moved by the conveyer(3) into the paint booth(4). The painting unit is the miniaturisation of the base coat paint booth having all necessary facilities to handle the spray painting. In a semi-automatic operation the operator will do the painting manually. The paint booth has several fixed nozzles each linked to a paint tank of a different colour or alternatively one nozzles could be linked with flexible connections to paint containers. Even in semi-auto case, change from one colour to the next has insignificant overhead cost/time. The painting booth is fully enclosed with a
490
Selected papers from the 22nd ICC&IE Conference
transparent window for control. Due to the presence of poisonous additives, special protective clothing for the painter and fumes exhaust devices are required. The turntable inside the booth holds and rotates the wheel cover for uniform painting. The exiting hot air from the primary storage table, may be utilised for paint drying purposes as well to save energy, at least when there is no change of colour Automation options of the clear coat process may be worth investigating. At this stage the painted wheel covers may be sent straight to the clear coat line via an overhead conveyor (since the wheel covers will be dried before they are moved, the problem of dripping paint and hard to remove dust will be eliminated). The sequence of operations in the new system are as follows: Step-I: Receive the moulded component from the robot and conduct the followings: • Visual quality check(7 sac) * Putting foam liner (2 sec) • Sprue cutting (4 sec ) • Stacking on storage table (7 sec) • Wire fitting (5 sec ) Step-H: The operator then does spray painting, 15 seconds. The painted wheel cover passes through the drier. Then it is placed on the secondary storage table as a buffer for final packing. Step-III: The operator packs four wheel covers in a cardboard box (20 seconds), ready to go to the customer. Cost of the new establishment was $41,000. The time saving provides a 1.03 years payback period. The cost justification was an encouraging factor, however issues regarding flexibility of operation much overweighed the direct financial rewards. The new system allows for the establishment of the mixed model [11] which provides a true production flexibility in terms of colour and quantity. The outcome of the cell, with 12 minutes cycle time for a pack of 12 wheel covers, allows direct delivery to the production line. In fact as the new line is much more compact, a new strategy may even favour establishing of the wheel cover production line as a feeder line adjacent to the assembly line. The new arrangements is positively changing the operators' and engineers' mental set to challenge the accepted norms and remove productivity improvement barriers which have been ingrained over the years. 5. Conclusions This paper discusses the theoretical and practical issues in cell formation, installation and operations based on a real case conducted in a manufacturing company. It demonstrates how practical considerations are difficult to be included in the GT or other algorithms by emphasising on the need for consideration of practical elements leading to more flexibility. Page limitation does not allow more details and some references have been dropped for the same reason. References 1. A. Kusiak Ed. Intelligent Design and Manufacturing. John Wiley(1992). 2. S. Heragu. Group Technology and Cellular Manufacturing. IEEE-Transactions on Systems. Man and Cybernetics Vol. 24, No.2, 203-214(1994). 3. L. Kandiller. "A Comparative Study of Cell Formation in Cellular Manufacturing Systems", Int'l J. of Prod. Res., Vol.32, No. 10, 2395-2429(1994). 4. S. Heragu. Facilities Desig. PWS(1997). 5. B Bidanda and R. Billo and P. Kharbanda. Re-engineering Process Plans for Effective Manufacturing Cell Formation. Int'l J. Of Mfg. Systems Design. Vol. 1, No. 3, 217-229(1995). 6. P.S. Welgamma and P.R. Gibson. Computer-Aided Facility Layout - A Status Report. Int. J. Of Advanced Manufacturing Technology, Vol. 10, 66-77(1995). 7. CL Cben and Contravo NA and Beak. A Simulated Annealing Solution to the Cell Formation Problem. Int'l J. Prod Res., Vol 33, No. 9, 2601-2614(1995). 8. R. Tavakkoli and E.Shayan. Manufacturing Facilities Design: A State of the Art Survey of Advanced Modelling. proc. 24 Int'l Mech Eng Conf. Vol 4, P877-885, Shiraz, Iran(1996).. 9. M. Bazargan-Lari. An Integrated approach to the intra-cell and inter-cell layout designs in a cellular manufacturing environment. PhD thesis University of N.S.W(1995). 10. R.Tavakkoli and E. Shayan. (An Analysis of genetic Operators Affecting the Performance of Genetic Algorithms for facilities Layout Problems", 7th Int'l Conf. On Manufacturing Engineering, Calms, Australia (1997). 11. J. Browne and J. harhen and J. Shivnan. Production management Systems, An Integrated Perspective, 2 ~ Ed. Addison Wesley (1996).
Computers ind. Engng Vol. 35, Nos 3-4, pp. 487-490, 1998 © 1998Published by Elsevier ScienceLtd. All rights reserved Printed in Great Britain PII: S0360-8352(98)00140-5 o360-8352/98 $19.00+ 0.o0
CELLULAR DESIGN FOR INJECTION MOULDING SHOP Ebrahim Shayan industrial Engineering Group IRIS Swinbume Univerisity of Technology-Hawthorn, Vie 3122, AUSTRALIA FAX: +613 9214 5050 EMAIL: [email protected] ABSTRACT This paper attempts to highlight the fact that application of GT does not always lead to a productive cell formation regardless of the algorithm used. The reason is that some practical issues are impossible to be included in the GT process. However a careful systematic IB analysis of the cell formed by GT may reveal new opportunities for improvements eventually leading to a more effective cell. A successful case demonstrates the idea. © 1998 Published by Elsevier Science Ltd. All rights reserved. 1. INTRODUCTION A cell is a set of machines (work stations) grouped to provide all the necessary activities for processing (servicing) of a family of products (items). Theoretically a single machine or a set of manual tasks can be considered as a cell. Some cells may have several machines or a combination of machines and other manual work stations. The major impact of a cell is that it provides a flow type environment for all in the family. Parts enter from one end in a primitive form and out, as a distinguished product, from the other end. An immediate result is the sense of ownership generated in the team of people working in the cell due to their identifiable impact on the parts made in that cell. In addition tremendous advantages are received from cells in forms of less inventory due to flow, less handling due to closeness, availability of more immediate assistance in resolving problems due to multiskilling, mutual relief and the like. All these tend to improve moral and quality while reducing lead time, errors, rejects, scraps which translate into financial gains. Literature is full of examples regarding achievements of different companies using cellular operations. Reduction of lead time from several weeks to hours is quite a common outcome [1]. In most cases the idea of forming a cell emerges from these envisaged benefits. It is utterly important for people involved to develop a thorough understandings and belief in the advantages. The expert is then in a position to challenge obstacles to develop a cell out of any possible situation, as is the concern of this paper. However before the case is explained it would be worthwhile reviewing the direction of research in cell formation.
2. Cell Formation There are several problems that have to be resolved to form a production cell. The first logical problem is to identify which machines have to be in the cell and what group of products should be in the family produced by the cell. This is the well researched area of Group Technology (GT) [2], [3], known as cell formation. Cluster identification algorithms attempt to develop an abstraction by forming a matrix of part-machine matching which is manipulated to, form clusters of related machines-parts. Complete clusters form the independent cells. Common machines between overlapping cells are either shared or when feasible duplicated. Despite the attempts for inclusion of more constraints into the cell formation scenario, most of the research work are simplified representations of the reality where some practical constraints have been intentionally relaxed to make the algorithm work, sometimes resulting in a non-productive cell. Nonetheless the grouping achieved through GT are good starting points, particularly when a large number of parts are involved. Several other methods have been developed for GT including similarity coefficient methods, sorting based algorithms, extended cluster identification [2], [4]. Little research appears to be ongoing about the necessary transitional tasks from the cell formulation results to productive cellular operation [5]. Some relate the issue to problems in inadequacy of process plan information and accordingly recommend solutions to increase group-ability. The author's experience shows 487
488
Selected papers from the 22nd ICC&IE Conference
that, in addition, serious problems may occur due to the nature of the cell elements. After all, most of the cell formation algorithms ignore several practical factors such as set-up time, material handling and other technological constraints. Accordingly to implement the cell for operational effectiveness consideration of practical issues is vitally important. The logical cell design must be transferred to a physical reality by layout design of the cell, " intra-cell or machine layout problem". This is another new field of research and developmenrin industrial engineering which has significantly progressed in recent years. There are two types of approaches to cell layout design which are of interest in this paper. The first approach considers an area as a grid and attempts to put machines, as blocks, into the grid cells in such a way to optimise some objectives such as minimising total handling, maximising throughput and the like, as in Quadratic Assignment Problems, QAP, formulation. Several algorithms have been developed to solve these problems [6]. Recently random search algorithms such as Simulated Annealing [7]and Genetic Algorithms [8] are gaining popularity in this field. The second approach to intra-cell layout considers the floor as a continuous plane where machines can be located at any unrestricted area. The question is to find the exact location of machines which optimises certain goals, eg. Minimising total area. Formulation of this problem is more complicated. However it has the advantage of continuous variables which can be handled easier. Bazergan[9] has applied Simulated Annealing and Tavakkoli and Shayan[10] attempted to solve the problem using Genetic Algorithms. The third stage may be considered as the overall layout of several cells within the shop floor, "inter-cell layout". A drawback in the existing approaches is the lack of an integration between GT, machine layout and inter-cell layout problems. As a result, global solutions may be sacrificed for the optimal local solutions. 3. The Case A plastic moulding company is experiencing difficulties in filling the orders on time under pressure on price competition. In particular one product, wheel cap, supplied to an automobile company is facing serious problems, edging at losing customers. The objective is to improve the flexibility of producing different eolours, cheaper while ensuring that quality is not compromised. The existing manufacturing cell to produce car wheel cover products consists of a number of work stations including injection moulding, sort and paint them, pack and dispatching to customers. However the present cell is not productive due to the fact that the GT design did not subject the solution procedure to practical considerations. To understand the performance of the current operations a standard industrial engineering study was conducted to measure and document the activities performed in the following sequence: 1. 2. 3. 4. 5. 6.
injection mould of wheel cover trimming by operators cooling down of caps packing in a box move to paint area unpack box
7. 8. 9. 10. 11.
put into paint booth conveyor stay on conveyor to dry pack in box move box to store move box from store to production line
Injection moulding machine is a considerable investment that cannot be replaced or redesigned, despite its inflexibility, a constraint we have to live with. The cycle time of the injection moulding machine is 68 seconds with production capacity of 1200 wheel covers per day. The moulded wheel cover is released from the gate, picked by a robot and delivered to the operator who then does visual quality checks for 7 seconds, sprue cutting 4 seconds, wire fitting 5 seconds, foam lining 2 seconds, a total of 25 seconds. The wheel covers are then stored in 3 bins of 120 capacity each. At the end of each shift the bins are transferred by a lift truck to the paint booth, taking 10 minutes. The bins are stacked at the paint booth waiting for availability of manpower to run the paint booth. The bins are taken from the stack and covers are removed and put in the paint booth, taking 15 seconds for each cap. Painting is a complicated bottleneck operation, deserving more explanations. The new design aims mainly to resolve the bottleneck problem. 3.1 PAINTING OF MOULED COMPONENTS Presently there are two types of painting in practice for plastic moulded components. Base coat is the original colour applied initially. Clear coat is the second transparent layer applied if necessary. Ordinary
489
Selected papers from the 22nd ICC&IE Conference
car models use base coated wheel covers only. But wheel covers for special model have both base coat and clear coat painting. Base Coat Operation: The operator takes a component from the bin for spray painting, 30 seconds, then hangs the component onto an overhead conveyer to dry out while travelling around for 25 minutes. Covers are then packed into small boxes which are stored again in another bin, ready for shipping to the assembly plant. However normally there is a delay time as bins are never shifted immediately after they are full. The daily requirements of the assembly plant is 460 wheel covers approximately. Base Coat and Clear Coat: The procedure for this type of painting is more elaborate. The cover, picked from the bin, is loaded on the conveyor and passes through the Triehloroethane chamber at 70°C. This operation removes the mould release agent from the component. Then the cleaned cover is passed through an antistatic chamber. This is for removal of static electricity from the component. The component is then passed through the oven to release the mould stresses. The painting follows with an initial base coat followed by a final clear coat. The clear coat contains Isocyanide and is dangerous to human health. The baking time for this paint is 30 minutes. The current rejection rate is 5% mainly due to over painting or dirt on the surface of the moulding. Painting is done normally twice a week. The number of components being painted is 320 in each batch.
3.2
Analysis of the current production
The conservative value added time period including 25 seconds for wire fitting and the rest of the operator's activities, 30 seconds for painting and 15 seconds for final packing, totals to (30+25+15)=70 seconds per wheel cover. The moulding time is the same in the new solution. The total time (average) taken for a wheel cover to go through the whole process was measured at about 100 hours. That is an efficiency (value added time divided by total time) of about .02 percent. Acceptance of this situation has brought about other side effects such as lack of accountability and absence of any operators' involvement in decision making and process improvement, a culture of 'no care'. This was a powerful motivation to embark on the study of the new approach as follows: 4. Improving the Cell Layout Design and Operation In order to Come up with a solution, the current situation must be understood, challenged by serious questions, and at each step alternative innovative solutions be considered to resolve the overall problem. Consideration of operators involvement in the solution process and later operation is a key success factor. The main bottleneck, painting, drove the new cell design activity. Changing from one colour to another with the current booth was unacceptably time consuming. Some preliminary tests revealed that there is no reason for cooling the wheel covers down to ambient temperature before painting. These fmdings suggested a need for a quick changeover of paint colour right after moulding. The existing high capacity of the paint booth, also being utilised for other jobs, and its size made its installation next to the moulding machine unsuitable. Requirements for flexibility in colour variations resulted in design of a small paint booth capable of handling a range of colours with no significant set-up. Resolving this problem integrated the cell operations and collapsed it into a small area. The modified cell layout consists of the following elements:
4.1 1. 2. 3. 4. 5.
T h e new Cell The injection moulding machine (as before) Two temporary storage tables Two conveyors A small painting and air blow drying unit Packing area
r-1 ]Operator
AirOut~~p~~
7-S---1
The storage tables (2) can hold thirty wheel covers in five stacks each. Air may be blown in, if necessary, for faster cooling of wheel covers while stacked or being moved by the conveyer(3) into the paint booth(4). The painting unit is the miniaturisation of the base coat paint booth having all necessary facilities to handle the spray painting. In a semi-automatic operation the operator will do the painting manually. The paint booth has several fixed nozzles each linked to a paint tank of a different colour or alternatively one nozzles could be linked with flexible connections to paint containers. Even in semi-auto case, change from one colour to the next has insignificant overhead cost/time. The painting booth is fully enclosed with a
490
Selected papers from the 22nd ICC&IE Conference
transparent window for control. Due to the presence of poisonous additives, special protective clothing for the painter and fumes exhaust devices are required. The turntable inside the booth holds and rotates the wheel cover for uniform painting. The exiting hot air from the primary storage table, may be utilised for paint drying purposes as well to save energy, at least when there is no change of colour Automation options of the clear coat process may be worth investigating. At this stage the painted wheel covers may be sent straight to the clear coat line via an overhead conveyor (since the wheel covers will be dried before they are moved, the problem of dripping paint and hard to remove dust will be eliminated). The sequence of operations in the new system are as follows: Step-I: Receive the moulded component from the robot and conduct the followings: • Visual quality check(7 sac) * Putting foam liner (2 sec) • Sprue cutting (4 sec ) • Stacking on storage table (7 sec) • Wire fitting (5 sec ) Step-H: The operator then does spray painting, 15 seconds. The painted wheel cover passes through the drier. Then it is placed on the secondary storage table as a buffer for final packing. Step-III: The operator packs four wheel covers in a cardboard box (20 seconds), ready to go to the customer. Cost of the new establishment was $41,000. The time saving provides a 1.03 years payback period. The cost justification was an encouraging factor, however issues regarding flexibility of operation much overweighed the direct financial rewards. The new system allows for the establishment of the mixed model [11] which provides a true production flexibility in terms of colour and quantity. The outcome of the cell, with 12 minutes cycle time for a pack of 12 wheel covers, allows direct delivery to the production line. In fact as the new line is much more compact, a new strategy may even favour establishing of the wheel cover production line as a feeder line adjacent to the assembly line. The new arrangements is positively changing the operators' and engineers' mental set to challenge the accepted norms and remove productivity improvement barriers which have been ingrained over the years. 5. Conclusions This paper discusses the theoretical and practical issues in cell formation, installation and operations based on a real case conducted in a manufacturing company. It demonstrates how practical considerations are difficult to be included in the GT or other algorithms by emphasising on the need for consideration of practical elements leading to more flexibility. Page limitation does not allow more details and some references have been dropped for the same reason. References 1. A. Kusiak Ed. Intelligent Design and Manufacturing. John Wiley(1992). 2. S. Heragu. Group Technology and Cellular Manufacturing. IEEE-Transactions on Systems. Man and Cybernetics Vol. 24, No.2, 203-214(1994). 3. L. Kandiller. "A Comparative Study of Cell Formation in Cellular Manufacturing Systems", Int'l J. of Prod. Res., Vol.32, No. 10, 2395-2429(1994). 4. S. Heragu. Facilities Desig. PWS(1997). 5. B Bidanda and R. Billo and P. Kharbanda. Re-engineering Process Plans for Effective Manufacturing Cell Formation. Int'l J. Of Mfg. Systems Design. Vol. 1, No. 3, 217-229(1995). 6. P.S. Welgamma and P.R. Gibson. Computer-Aided Facility Layout - A Status Report. Int. J. Of Advanced Manufacturing Technology, Vol. 10, 66-77(1995). 7. CL Cben and Contravo NA and Beak. A Simulated Annealing Solution to the Cell Formation Problem. Int'l J. Prod Res., Vol 33, No. 9, 2601-2614(1995). 8. R. Tavakkoli and E.Shayan. Manufacturing Facilities Design: A State of the Art Survey of Advanced Modelling. proc. 24 Int'l Mech Eng Conf. Vol 4, P877-885, Shiraz, Iran(1996).. 9. M. Bazargan-Lari. An Integrated approach to the intra-cell and inter-cell layout designs in a cellular manufacturing environment. PhD thesis University of N.S.W(1995). 10. R.Tavakkoli and E. Shayan. (An Analysis of genetic Operators Affecting the Performance of Genetic Algorithms for facilities Layout Problems", 7th Int'l Conf. On Manufacturing Engineering, Calms, Australia (1997). 11. J. Browne and J. harhen and J. Shivnan. Production management Systems, An Integrated Perspective, 2 ~ Ed. Addison Wesley (1996).