improving productivity of manufacturing division using lean concepts
Transcription
improving productivity of manufacturing division using lean concepts
I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2( De c e mb e r2 0 1 2 ) LeanThi nki ng journalhomepage: www.thi nki ngl ean.com/i jl t IMPROVING PRODUCTIVITY OF MANUFACTURING DIVISION USING LEAN CONCEPTS AND DEVELOPMENT OF MATERIAL GRAVITY FEEDER –A CASE STUDY K.Hemanand Department of Mechanical Engineering, PSG College of Technology,Coimbatore – 641 004, India. D.Amuthuselvan Department of Mechanical Engineering, PSG College of Technology,Coimbatore – 641 004, India. S.Chidambara Raja* G.Sundararaja Department of Mechanical Engineering, PSG College of Technology,Coimbatore – 641 004, India. chidambararaja1989@gmail.com Department of Mechanical Engineering, PSG College of Technology,Coimbatore – 641 004, India. ABSTRACT The automotive industry has been experiencing a competitive environment and striving hard to find methods to reduce manufacturing cost, waste and improve quality. Lean manufacturing concepts are used by the industries to reduce work in progress inventories and also to reduce the waste for competing in the global market. The ultimate goal is to speed up the process there by increasing productivity through a proper utilization of man and machine. In a manufacturing industry, the layout and material flow in the shop floor decides its productivity. Material handling system also plays a key role in influencing productivity, throughput time and cost of the product. This research work has been carried out as a case study in an automotive industry with the objective of waste reduction. Efforts are made to reduce the motion waste in the shop floor. The problems in the current layout are identified and analyzed through simulation. Then the layout is modified, simulated and the results are compared with the current layout. The results revealed an improvement of 11.95% in productivity. A new material handling system has been designed and developed to reduce the motion wastes and unwanted transportation. KEYWORDS Layout, Simulation, Material, Time, Transportation ARTICLE INFO Received 30 July 2012 Accepted 07 September 2012 Available online 01 October 2012 1. Introduction Lean manufacturing is “A systematic approach for identifying and eliminating waste through continuous improvement by flowing the product at the pull of customer in pursuit of perfection”. Lean manufacturing concepts are mostly applied in industries where more repetitive human resources are used. In these industries productivity is highly influenced by the efficiency working people with tools or operating equipments. To eliminate waste, it is important to understand exactly what it is and where it exists. The processes add either value or waste to the production of goods. The seven manufacturing wastes originated in Japan, where waste knows ________________________________ as “muda" as Author demonstrated by Rotaru (2008). * Corresponding HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) as “muda" as demonstrated by Rotaru (2008). The concept of Lean manufacturing first came to be more widely known with the book ‘The Machine That Changed the World’ published by Womack et al.(1990) and later through the book ‘Lean Thinking’. The Key points of emphasis in Lean appear to be reducing process variability, reducing system cycle times, and above all, eliminating wastes in the manufacturing cycle as stated by Womack and Jones (1986). Paul and Rabindra (2006) used subjective assessment through questionnaire, direct observation method, and archival data to improve productivity, quality, increasing revenue and reducing rejection cost of the Manual Component Insertion (MCI) lines in a printed circuit assembly (PCA) factory. Live experiments were conducted on production lines. The drawback of this work is that an experimental design could not be performed to find the best insertion sequence and component bin arrangements as there was a hindrance in conducting experiments in real-life line, i.e. the study itself might reduce line output and affect quality. Brown and Mitchell (1988) did an investigation into operators, engineers, and managers of PCA factories to determine the work environment parameters that inhibited their performance and they recommended opportunities to improve productivity & quality. Lim and Hoffmann (1997) found that improved layout of the workplace increased productivity of the workers, through more economical use of hand movements by conducting an experiment on hacksaws assembly. Christopher (1998) stated that the success in any competitive context depends on having either a cost advantage or a value advantage, or, ideally, both. Imad Alsyouf (2007) illustrated how an effective maintenance policy could influence the productivity and profitability of a manufacturing process and showed how changes in the productivity affect profit, separately from the effects of changes in the uncontrollable factors, i.e. price recovery Browning and Heath (2009) developed a revised framework that reconceptualises the effect of lean on production costs and used it to develop eleven propositions to direct further research and illuminated how operations managers might control key variables to draw greater benefits from lean implementation. White et al. (1999) found that plant size had a significant effect on the implementation of lean practices. This shows that, regardless of establishing what lean is, it remains important to establish how best to become lean in varied contexts. Shah and Ward (2003) empirically validated four “bundles” of inter-related and internally consistent practices; these are just-in-time (JIT), total quality management (TQM), total preventive maintenance (TPM), and human resource management and investigated their effects on operational performance. Flynn et al.(1995) and McKone et al.(2001) have explored the implementation and performance relationship with two aspects of lean. Crute et al.(2003) discussed the key drivers for Lean in aerospace and did a Lean implementation case comparison which examines how difficulties that arise may have more to do with individual plant context and management than with sector specific factors. Womack et al.(1990) developed from the massively successful Toyota Production System, focusing on the removal of all forms of waste from a system. Krafcik, (1998) describes the Japanese-style manufacturing process pioneered by Toyota, which uses a range of techniques including just-in-time inventory systems, continuous improvement, and quality circles. 118 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) In the cited literatures, Researchers revealed the importance of lean concepts in the competitive industries especially for improving the productivity, quality of products, profitability, and for reducing lean wastes and inventories. The current research aims at improving productivity, increasing revenue of the plant by the reduction of motion wastes. In addition, the design and development of the gravity feeder for the material handling have been done as a value addition to this research work. The methodology of the current case study is presented in the block diagram and depicted in Figure 1.The collection of data is done by direct observation method. The time study is conducted using stop watch. From the collected data, the problems in the current layout are identified and rectified by redesigning the layout in two aspects. One aspect is reducing the material handling by the design and development of new material gravity feeder which is designed in solid edge V19 and structural analysis is done in Ansys 12. Another aspect is conducting the simulation study to reveal the performance of current layout using WITNESS simulating software. Based on the results, a new layout is proposed and implemented. Figure 1: Block diagram of methodology followed in the case study 119 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Abbreviations Opn - Operation SPM - Special purpose machine VMC - Vertical machining centre HMC - Horizontal machining centre RM - Raw material FG - Finished goods MHS - Material Handling System M/C -Machine No. - Number Nomenclature M - Bending Moment (N mm) I - Moment of Inertia (mm4) σ - Bending stress (N/mm2) Y - Distance from neutral axis (mm) 2. Case study – Layout of CNC Machine shop 2.1 Current layout A case study on machining of bearing cap has been chosen to find the working of current layout and its performance. The Bearing cap for engine is machined using CNC and Special purpose machines. The surfaces of bearing cap to be machined are marked by arrows in Figure 2. Figure 2: Bearing cap machining details The part flow and sequence of the machining processes carried out on the bearing cap from raw material to final finished goods are shown in Figure 3. The machines used for the sequence of operations are two Special purpose machines (SPM) and five CNC machines. 120 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Figure 3: Flow chart for Process sequence 2.2 Time study Time study is defined as a work measurement technique for recording the times and rates of working for the elements of a specified job carried out under specified conditions, and for analyzing the data so as to obtain the time necessary for carrying out the job at a defined level of performance [6]. A time study has been carried out for all operations on the bearing cap in the layout by direct observation method and the observed data is listed in Table 1. Table 1 Details of Time study Opn. M/C type No. No. of operators No. of Components 10 Man working Man idle M/C working M/C idle Cycle time Cycle time per time time time time İn seconds Component in seconds İn seconds İn seconds İin seconds İn seconds SPM 1 1 24 26 50 0 50 50 63 20 SPM 1 1 42 21 32 31 63 30-A VMC 1 2 95 0 95 0 95 30-B VMC 1 2 53 70 82 41 123 62 40-A VMC 1 2 63 15 25 53 78 39 40-B VMC 1 4 164 75 166 136 302 76 50 HMC 1 1 64 0 64 0 64 64 60 Deburring 2 1 60 0 0 0 60 60 70 Inspection 2 1 40 0 0 0 40 40 80 Washing & 2 1 10 4 4 10 14 14 Packing 121 48 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) 2.3 Takt time calculation Takt time is the average time allowed to produce unit production to meet customer demand and the process time should be less than or equal to the takt time. Takt time is calculated based on machine available time and the required number of units. The procedure followed to determine takt time for the current production of bearing cap is as follows: Total available time Customer Demand / day Available Working time/shift (Excluding lunch and tea break) Available time/day Takt Time = 3 Shifts / day /25 working days in a month = 1167 pieces = 420 minutes=25200 seconds. = 25200 x 3=75600 seconds. = Total available time /Customer demand = 64.78 seconds/piece ≈ 65 seconds/piece 2.4 Cycle time calculation From the time study on current layout (Table 1), it is identified that the operations 30A and 30B are identical and so the cycle time of one component is found to be 55 seconds by averaging the cycle times of these two machines. Similarly, operations 40A and 40B are identical and by taking the average, one components’ cycle time is found to be 58 seconds. For all the operations, cycle time for a single component is estimated and listed in Table 2. Also, the same is depicted in the bar chart as shown in Figure 4. Table 2 Processing time calculation Opn No. 10 20 30 40 50 60 70 80 Process description Top and bottom face milling Crank ,nut & joint face roughing Nut face milling, drilling and processing dowel Crank boring, Notch Milling Joint face milling, Register width finishing Deburring Inspection Washing and Packing 122 Cycle time in seconds 50 63 55 58 64 60 40 14 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Figure 4: Bar chart depicts the takt time for one day basis 2.5 Problems Identified in the current layout The major issues faced in the current layout are explained as follows and the current layout is depicted in Figure 5. Figure 5: Current Layout 2.5.1 Idle time of the operator Idle time of the operator is found from the time study and total idle time of all operators for three shifts in one day is found and tabulated in Table 3. 123 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Table 3 Idle time of the operators for three shifts in one day Sl.No 1 2 3 Man idle time Opn No. for one cycle Outputs/day in Seconds 20 21 1200 3070 614 B 4075 250 B Idle time for 3 Idle time of shifts in one operator per day in seconds day inhours 25200 7 43024 11.95 18775 5.22 Total 24.17 This idle time can be utilized in a better way by operating two machines simultaneously. 2.5.2 Waste in transportation by manual operation In this layout material handling is done using wooden pallets which is transferred by trolley from one station to another station. It consumes considerable time and results in increased manufacturing lead time. The materials are moved from one station to another by operator causing motion waste and transportation waste which is about 68.9 m for every batch of components as given in Table 4. Table 4 Distance travelled by operator Sl. No. Stations 1 2 3 4 5 6 7 8 9 Total RM- opn.10 opn.10-20 opn.20-30 opn.30-40 opn.40-50 opn.50-60 opn.60-70 opn.70-80 opn.80-FG Distance travelled without MHS in meters 1.53 3.66 12.2 13.7 10.7 18.3 4.88 0.914 3.05 68.9 The operator movement in the current layout is depicted in Figure 6. This has to be reduced with suitable material handling device. 124 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Figure 6: Operator and material movement in Current layout 3. Proposed layout Owing to the problems existing in the current layout, a new layout is proposed based on the study and analysis of the current scenario. The features of the new layout are listed as follows 1. All machines are connected with a new gravity feeder for carrying material from one station to another which reduces transportation waste by the amount of 47.85 meters as shown in Table 5 and feeder is shown in the Figure 7 as number 1.The transportation in the proposed layout is pictorially depicted in Figure 8. Table 5 Operator motion distance comparison Current layout Sl. No. Stations without MHS in meters 1 RM- opn.10 1.53 2 opn.10-20 3.66 3 opn.20-30 12.2 4 opn.30-40 13.7 5 opn.40-50 10.7 6 opn.50-60 18.3 7 opn.60-70 4.88 8 opn.70-80 0.91 9 opn.80-FG 3.05 Total (meter) 68.93 Proposed layout with MHS in meters 1.53 0 0 0 0 16 0 0.5 3.05 21.08 Difference in distance travelled in meters 47.85 2. Two machines are interchanged because it is identified that the idle time of the operator is more as mentioned in the Table 3. Operation 30B and 40B having high idle times 70s and 75s respectively. In order to reduce the idle time of operators, the machines C and D are interchanged and the orientation of 125 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) C, E and F are altered as shown in the Figure 7 as number 2. In this new arrangement, Machines B and D are operated by a single operator simultaneously. Similarly, machines E and F are operated by a single operator simultaneously. This helps the operator to run two machines simultaneously by utilizing the idle time. 3. A new window is included in the wall between deburring and inspection area to transfer the material directly which reduces transportation and motion wastes. It is shown in the Figure 7 as number 3. Figure 7: Proposed Layout Figure 8: Material movements in the Proposed Layout 126 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) 4. Simulation study The imitation of the operation of a real-world process or system over time is called simulation. Simulation involves the generation of an artificial history of the system and the observation of that artificial history to draw inferences concerning the operational characteristics of the real system that is represented. The simulation is an indispensable problem-solving methodology for the solution of many real-world problems. It is used to describe and analyze the behaviour of a system, ask what-if questions about the real system, and aid in the design of real systems as explained by Adams et al.(1999), Jain and Leong (2005). A simulation study is carried out using WITNESS as simulation software. Both current and proposed systems are modelled and simulated in order to find out the optimum layout strategy. 4.1 Current layout simulation A simulation run for 189000 seconds (one month machine available time) is done for the current layout. The snap shot of the current layout arrangement with the operators and machines are shown in Figure 9. Figure 9: Simulation of Current layout Data regarding number of activities required, uptime details of the machine, the number of operator and their working time are given as input and the logic is based on the operation sequence and number of workers available. The simulated results are shown in Table 6 127 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Opn. No Table 6 Simulation of current layout Current layout simulation Machine Labour Process 10 20 Top and bottom milling Crank ,nut and joint face roughing Nut face milling, drilling and processing 30-A dowel Nut face milling, drilling and processing 30-B dowel 40-A Crank boring, Notch Milling 40-B Crank boring, Notch Milling Joint face milling, Register width 50 finishing 60 Deburring 70 Inspection 80 Washing and Packing Total Efficiency 4.2 %idle %busy %setup %busy %idle 0 52.54 67.19 100 31.81 32.80 0 15.64 0 100 15.64 32.81 0 84.36 67.19 66.48 21.47 12.03 12.03 87.96 46.13 45.06 0.70 45.56 44.81 99.29 8.307 10.11 0 8.307 10.11 99.29 91.69 89.88 0.70 0.82 33.9 60.34 37.32 99.18 66.1 23.14 56.42 0 0 16.52 6.26 99.18 66.1 16.52 46 0.82 33.9 83.48 54 Proposed layout simulation In the proposed layout, a simulation run for 189000 seconds is done. The snap shot of the proposed layout arrangement with the operators and machines are shown in Figure 10. Figure 10: Simulation of proposed layout 128 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) The simulated results are shown in Table 7. Table 7 Simulation of proposed layout PROPOSED LAYOUT SIMUALTION Opn. No PROCESS Machine Labour %idle %busy %setup %busy %idle 10 Top and bottom milling 0 100 0 100 0 20 Crank ,nut and joint face roughing 52.52 31.83 15.65 33.23 66.77 Nut face milling, drilling and 30-B 66.48 21.47 12.03 processing dowel Nut face milling, drilling and 30-A 66.76 33.23 0 27.69 72.31 processing dowel 40-A Crank boring, Notch Milling 43.44 45.27 11.28 21.59 78.40 40-B Crank boring, Notch Milling 43.99 45.68 10.31 Joint face milling, Register width 50 0.70 99.29 0 99.29 0.70 finishing 60 Deburring 0.82 99.18 0 99.18 0.82 70 Inspection 33.9 66.1 0 66.1 33.9 80 Washing and Packing 60.34 23.14 16.52 16.52 83.48 Total Efficiency 36.9 56.52 6.58 57.95 42.05 From the Tables 6 and 7 the machine utilization is observed to be same in both the current and proposed layout but the elimination of operators has increased the labour utilization. The performance measures are Percentage of labour productivity and Percentage of machine utilization. The layout efficiency values are given in Table 8. Table 8 Comparison of layout results Parameters Machine utilization %idle %busy %setup Current Layout 37.32 56.42 6.26 Proposed Layout 36.90 56.52 6.58 %busy 46.00 57.95 %idle 54.00 42.05 Labour productivity Improvements No Change Increased by 11.95 Decreased by 11.95 Figure 11 shows the performance of current and proposed layouts. From this result, it is concluded that there is no change in the machine utilization but the labor productivity is increased by 11.95%. 129 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Figure 11: Comparison of layout efficiency 5. Design of Gravity operated feeder for Bearing Cap In this bearing cap layout, a gravity operated feeder has been designed for the material handling of bearing cap. The main aim of this gravity feeder is to reduce material handling time and transportation in between work stations. The feeder is made up of 3 mm steel sheet which has four supports at its ends. The shape of the feeder to accommodate the bearing cap is shown in Figure 12. This model can carry about 29 parts per meter in the feeder. Figure 12: Gravity feeder model 130 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) 5.1 Structural analysis of gravity feeder A gravity feeder is modeled using solid edge v-19 and structurally analyzed using ANSYS 12.0 with following data, the length of feeder is 1000mm and number of components it carries in one meter is 29. The bearing cap weight varies from minimum 3kg to maximum of 4.25kg. So the maximum weight 4.25 kg is selected and the weight of 29 components is found to be 1209.08 N According to the theory of pure bending [14], bending moment equation is expressed as follows (M/I) = (σ/Y) = (E/R) (1) 2 Using the equation (1), bending stress is estimated to be 8.063N/mm . The yield strength of steel C15 with factor of safety 6 is found to be 39.24N/mm2 [13]. The model is completely meshed with solid brick 8 node 45 and it is shown in Figure 13. Figure 13: Meshed model 5.2 Result and Inference From the analysis, the maximum deformation is found to be 0.001426mm which is reasonably negligible and it is displayed in Figure 14. 131 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Figure 14: ANSYS result 6. Summary and Conclusions An attempt has been made to improve the productivity and profitability of the industry. The design and development of the gravity feeder for the material handling have been done to reduce the motion and transportation wastes. The simulation analysis of current layout is carried out to study the performance in lean perspective and modifications in the layout have been made. A window opening is made between the deburring and inspecting operation which saves time by 30 minutes for 100 parts .The machines are replaced and their orientations are changed for easy transfer of material and for sharing the idle time of the operators with other machines. The modifications in the layout will reduce two operators and increase the utilization of the operators by 11.95%. It saves 640 rupees per shift from the operator’s salary. Hence it saves Rs. 5, 99,040 per year which is a considerable savings in the total revenue. Also the implementation of gravity feeder in between the workstations reduces the motion waste and monotonous efforts of the labours which further enhances the labours’ job satisfaction and goodwill of the organisation. References Adams .M, Componation .P, Czarnecki .H, and Schroer .B. Simulation as a Tool for Continuous Process Improvement, Proceedings of the 1999 Winter Simulation Conference. University of Alabama in Huntsville; 1999. Brown, K.A., Mitchell, T.R. Performance obstacles for direct and indirect labour in high technology manufacturing. International Journal of Production Research 1988; 26; 1819–1832. 132 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) Christopher, M. Logistics and Supply Chain Management: Strategies for Reducing Cost and Improving Service. 2nd ed. Financial Times Prentice-Hall: United Kingdom; 1998. Flynn, B.B., Sakakibara, S., Schroeder, R.G. Relationship between JIT and TQM: practices and performance. Academy of Management Journal 1995; 38 (5); 1325–1360. Imad Alsyouf. The role of maintenance in improving companies’ productivity and profitability. International Journal of Production Economics 2007; 105; 70–78. Introduction to Work Study. International Labour Office: Geneva; 1979. Jain .S and Leong .S. Stress Testing a Supply Chain Using Simulation, Proceedings of the 2005 Winter Simulation Conference, 1650-1657; 2005. James P. Womack and Daniel T. Jones. Lean Thinking: Banish Waste and Create Wealth in Your Corporation. 1st ed. Simon and Schuster: Inc .New York; 1996. Krafcik, J.F. Triumph of the Lean production system. Sloan Management Review 1998; 30 (1); 41–53. Lim, J., Hoffmann, E. Appreciation of the zone of convenient reach by naive operators performing an assembly task. International Journal of Industrial Ergonomics 1997; 19; 187–199. McKone, K.E., Schroeder, R.G., Cua, K.O. The impact of total productive maintenance on manufacturing performance. Journal of Operations Management 2001; 19 (1), 39–58. Paul H.P. Yeowa, Rabindra Nath Senb. Productivity and quality improvements, revenue increment, and rejection cost reduction in the manual component insertion lines through the application of ergonomics. International Journal of Industrial Ergonomics 2006; 36; 367–377. PSG Design Data. PSG College of Technology: Kalaikathir Achchagam; 1978. Ramamrutham.S, Narayanan.R. Strength of Materials. Dhanpat Rai Publishing Company: New Delhi; 2004. Rotaru ana . Teaching Lean Manufacturing Concept, Annals of the oradea university, fascicle of management and technological engineering 2008; 7 (17); 2692-2697. Shah, R., Ward, P. Lean manufacturing: context, practice bundles, and performance. Journal of Operations Management 2003; 21; 129–149. Tyson R. Browning, Ralph D. Heath. Reconceptualizing the effects of lean on production costs with evidence from the F-22 program 2009. Journal of Operations Management 2009; 27; 23–44. 133 HE MA NA ND, A MUT HUS E L V A N, CHI DA MBA R AR A J A , S UNDA R A R A J A/ I n t e r n a t i o n a l J o u r n a l o f L e a nT h i n k i n gV o l u me3 , I s s u e2 ( De c e mb e r2 0 1 2 ) V. Crute, Y. Ward, S. Brown , A. Graves. Implementing Lean in aerospace—challenging the assumptions and understanding the challenges. Technovation 2003; 23; 917–928 White, R.E., Pearson, J.N., Wilson, J.R. JIT manufacturing: a survey of implementations in small and large U.S. manufacturers. Management Science 1999; 45(1); 1–15. Womack, J., Jones, D., Roos, D. The Machine That Changed the World. Rawson Associates: New York; 1990. 134