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Lean concept in manufacturing field - Literature review Example

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With the failure of MRP to offer enhanced system performance, the shift has focused to Just-in-time production systems which are driven by customer demand.Hence, the jobs are “pulled through the system” with linkage between stages in the production process (Deleersnyder, et al., 1989). …
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Lean concept in manufacturing field
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? Lean concept in manufacturing field inserts his/her s Department’s Kanban With the failure of MRP to offer enhanced system performance, the shift has focused to Just-in-time production systems which are driven by customer demand. Hence, the jobs are “pulled through the system” with linkage between stages in the production process (Deleersnyder, et al., 1989). The Japanese system of Kanban is required in order to physically implement the pull production system. Kanban is often used in conjunction with Just-in-Time production whereby the right quantity must be manufactured at the appropriate level and at the right time. Literally translated as “a card”, the Kanban signal, which is generated through the master production schedule (MPS) or customer demand, triggers JIT as it works its way backwards through each work centre. Generally, a Kanban is tied to each container of work-in-progress (WIP) which contains specifications pertaining to that WIP such as the lot size, card number, due date etc. Research has demonstrated various benefits associated with the use of Kanban. JIT allows most companies to achieve the benefits of shorter lead times, enhanced quality and low inventory buffer (Cimorelli, 2013). However, choosing the Kanban size often requires tradeoffs. For instance, a large size of Kanban will often result in higher level of stock albeit with a shorter lead time and less time for setting up machines frequently. Furthermore, Kanban acts as a means of communication from usage points to the prior operation as well as serve the purpose of visual signage (Wang, 2011). As far as the types of Kanban are concerned, there are generally two types of Kanban systems: single card and dual card systems. This entails separating the storage of output of a particular stage from the storage of input in the succeeding stage along with the use of extra cards named as “withdrawal” Kanban (Krieg, 2005). This Kanban is defined as one which accompanies the containers that are responsible for storage at the input stage. This is followed by removal of the withdrawal Kanban and its subsequent storage in a “collection box” when the production system uses a container (Krieg, 2005). Subsequently, the withdrawal Kanban is further removed from the collection box by a carrier and moved into the storage for output from the previous stage. On the other hand, the single-card Kanban is more efficient for manufacturing processes that contain high “changeover time” owing to batch production (Basu & Wright, 2005). The major difference between a single-card and dual-card Kanban is that the former lacks a “production” Kanban and specific inventory points (Basu & Wright, 2005). To conclude, the use of Kanban in the Just-in-time production system is fairly old. However, their importance has steadily increased owing to the paradigm shift towards demand-pull manufacturing systems as opposed to push-manufacturing systems. Nevertheless it must be noted that although the Kanban system lead to efficient levels of inventory, shorter lead times and better flow of communication across the production system, it may not always fulfill all order qualifiers at the same time as tradeoffs may be involved. 2. Push/pull systems Lean manufacturing systems are usually split into pull and push production systems. Push systems are based on scheduling work such that it is released on the basis of customer demand (Kimura & Terada, 1981). This is because their aim is to maximize the usage of production capacity. These systems are driven by the system of due-dates. The release date is controlled and the level of Work in Progress is then observed. By using this system, companies are able increase the volume of their production which in turn reduces the cost of production per unit. The push strategy has been used by companies such as Dunkin Donuts for producing their donuts. Customer demand for each of the donuts (such as Glazed, chocolate, cream etc.) is arrived at using forecasted projections as well as historical data (Boyer & Verma, 2010). This is used to arrive at the quantity of donuts that can be sold over a given period (usually in hours). A pull production system, on the other hand, uses the customer demand for planning production rather than pushing the products produced in order to maximize efficiency of resources (Boyer & Verma, 2010). For instance, Subway uses the pull system whereby each customer selects the ingredients of the subway sandwich himself/herself (Boyer & Verma, 2010). The sandwich is then assembled in front of the customer in an aisle. Organizations that offer home delivery often follow this system (Boyer & Verma, 2010). By using pull production system, Wal-Mart has achieved tremendous cost savings as Point of Sale (POS) data is transmitted to the vendors and store supplies are replenished twice a week (Boyer & Verma, 2010). The aim of most manufacturing systems is to reduce the amount of unfinished stock and maximize the rate of production along with higher capacity utilization. To this end, just-in-time manufacturing systems which are used synonymously with pull systems enable companies to reduce work-in-progress (Chang, et al., 1985). Furthermore, some researchers have also defined pull systems as using the Kanban technique whereas, push systems tend to use systems based on scheduling (Schonberger, 1983). Nevertheless, achieving maximum system utilization as well as low inventory may be very challenging as usually a tradeoff is involved. Pull systems often result in lower inventory as well as low system utilization whereas push systems often demonstrate the opposite results (Zhou & Venkatesh, 1999). To conclude, push systems tend to production centric and are in line with the earlier strategy to base production on companies’ resources and not customers’ demand. Pull systems, on the other hand, represent the newer paradigm and are often used in conjunction with Just-in-Time and lean manufacturing systems. The latter results in fewer inventories being held as items arrive on the production line as and when demanded by the customer. Pull systems are particularly suited for companies with high turnover such as Wal-Mart. Therefore, pull systems result in greater cost savings albeit with lower system utilization, whereas the former results in high levels of semi-finished stock with higher system utilization. 3. One-piece flow One-piece flow, often referred to as continuous flow is a concept in production which refers to the movement of work as a whole (in one piece) between various operational procedures within a work cell (Pawley Lean Institute, n.d.). This movement must not be interrupted by parameters such as time, sequence, space or substance (Pawley Lean Institute, n.d.). It is often contrasted from batch production in that it defines the sequential flow of product and operational activities where units are processed one by one. On the other hand, batch production often entails the passing of “batches” or group of items through a single process together (Coletta, 2012). Simply put, one-piece flow involves the movement of one unit of work through the process at a particular time from beginning till the end. Since one-piece flow production involves less changeover time, it is often considered suitable for pull production systems (Salvendy, 2001). At the very least, one-piece production results in reduction of waste as far as logistics including stock, transportation and waiting are concerned. It also results in low cost of management simple because of its stability and predictability. Also, continuous flow results in shorter lead times. Such a production technique is highly agile in that any changes in customer demand, specifically the product mix, can be changed in a relatively short time. Reduced lead time also results in reduced work-in-progress inventory. The hand-off time is also significantly reduced as items do not require queuing in the workstation upstream waiting for the accumulation of a cluster of items before transferring it downstream. It is important to note that one-piece flow often results in greater connection between the various linkages in the supply chain. This is because products move seamlessly from the preceding production link to the next link with zero waiting time. However, such a system will only work where quality control standards are high (The Productivity Development Team, 1999). If several quality issues occur, the “flow” will be essentially disrupted; hence, one-flow will fail to achieve its purpose. Furthermore, a high level of standardization is required as the technique does not allow for variations in process times arising from variation in the product (Miltenburg, 2001). Considering the seamless operation under this technique, any machine breakdown is virtually intolerable and can result in shutdown of the plant. Furthermore, one-piece flow works best in production facilities organized as per cellular layout (Chiarini, 2013). Since workstations are grouped close together, items travel relatively short distances as they move from one workstation to the next. To conclude, one-piece production requires relatively little variety in items produced as well as tight quality control procedures. Any bottleneck of delay in any one stage can disrupt the flow in the process. Because of its seamless nature, this is often used with pull production systems. Most obviously it results in the reduction of lead times and buffer stock which increases the overall efficiency of production process. This is one of the reasons why one-piece flow is often associated with the lean philosophy of waste minimization. 4. Quality control Quality control is a broad concept that entails inspection of products at some stages. However, inspection and quality control are not the same. In fact, it can be considered as a subset of quality control. Quality control, in effect, involves the integration of quality development, maintenance of quality standards as well as improvement of current quality across the organization in order to enable economical manufacturing and customer satisfaction (Murthy, 2005). The notion of quality control goes beyond inspecting the quality of goods already produced (as in the case of quality inspection). It incorporates keeping track of the quality of goods produced in future. Quality can be controlled either during the manufacturing process or after the production has taken place. The former refers to as process control whereas the latter is referred to as product control. There are seven major tools of quality control. Statistical Process Control (SPC) is often used to analyze the quality and variation of a process using a set number of parameters. The resulting control charts, defined by the upper and lower control limits, help to signal the processes out-of-control so that defectives such as reworks and scraps can be reduced (Shamsuzzaman & Wu, 2006). The cause-and-effect diagram for methods, materials, environment, equipment and people is a pictorial representation of root causes of the quality problem. Flow charts also allow a pictorial and sequential representation of the operational procedures required for task completion (Ho, 1999). By comparing the ideal state of the process with the current state, the weaknesses in the process are highlighted. Any non-value added steps are reduced along with removal of potential quality defects through specific targeted steps for improvement. Checksheets serve a similar purpose as they ensure that data is collected and analyzed (Webber & Wallace, 2007). For instance, the number of times the supervisor is called each day may be analyzed. Like cause-and-effect diagrams, checksheets too are aimed at detecting the cause of quality problems. Furthermore, Pareto charts also help to prioritize problems in quality. These are based on the premise that 80 per cent of the problems are caused by 20 per cent of the causes (Webber & Wallace, 2007). Finally, histograms allow the variation in the process to be assessed. However, this is just a starting point for quality control as the hidden causes might need further investigation. Although these tools are widely incorporated in quality control literature, organizations are now moving towards the total quality management and six sigma paradigms whereby “quality at source” is encouraged. The Six Sigma philosophy, mastered by companies such as GM, Motorola and others, aims to achieve 3.4 defects per million parts, thereby improving both product and process quality (Schroeder, et al., 2008). Total quality management further ensures that the right product is made at the right place and right time. In other words, emphasis is on making the product right the first time as opposed to the traditional tools that focused on inspecting quality “after” work was done. To conclude, quality control encompasses not just a reactive approach that focuses on reducing defects through SPS, Pareto charts, Cause and Effect diagrams etc. but a proactive approach demonstrated by TQM and Six Sigma. As noted earlier, the concept of quality control is holistic in that everyone in the organization is responsible for controlling quality not just the quality inspector. References Basu, R. & Wright, J. N., 2005. Total Operations Solutions. Oxford: Elsevier Butterworth-Heinemann. Boyer, K. K. & Verma, R., 2010. Operations and Supply Chain Management for the 21st Century. Mason: South-Western Cengage Learning. Chang, Y. C., Sullivan, R. S., Bagchi, U. & Wilson, J. R., 1985. Experimental Investigation of Real-Time Scheduling in Flexible Manufacturing System. Annals of Operations Research, Volume 3, pp. 355-377. Chiarini, A., 2013. Lean Organization: From the Tools of the Toyota Production System to Lean Office. Heidelberg: Springer-Verlag. Cimorelli, S., 2013. Kanban for the Supply Chain: Fundamental Practices for Manufacturing Management. 2nd ed. Florida: Taylor & Francis. Coletta, A. R., 2012. The Lean 3P Advantage: A Practitioner's Guide to the Production Preparation Process. Florida: Taylor & Francis. Deleersnyder, J.-L., Hodgson, T. J., (-Malek), H. M. & O'Grady, P. J., 1989. Kanban controlled pull systems: An Analytical Approach. Management Science, 35(9), pp. 1079-1091. Ho, S. K. M., 1999. Operations and Quality Management. London: International Thomson Business Press. Kimura, O. & Terada, H., 1981. Design and Analysis of Pull-System: a Method of Multi-Stage Production Control. International Journal of Production Research, Volume 19, pp. 241-253. Krieg, G., 2005. Kanban-Controlled Manufacturing Systems. Heidelberg: Springer-Verlag. Miltenburg, J., 2001. One-piece flow manufacturing on U-shaped production lines: a tutorial. IIE Transactions, Volume 33, pp. 303-321. Murthy, P. R., 2005. Production and Operations Management. 2nd ed. New Delhi: New Delhi. Pawley Lean Institute, n.d. Leaning Enrichment Acitivity: Continuous/one-piece flow, s.l.: Oakland University. Salvendy, G., 2001. Handbook of Industrial Engineering: Technology and Operations Management. 3rd ed. New York: John Wiley & Sons. Schonberger, J. R., 1983. Applications of Single-Card and Dual-Card Kanban. Interfaces, 13(4), pp. 56-67. Schroeder, R. G., Linderman, K. & Ch, A. S., 2008. Six Sigma: Definition and underlying theory. Journal of Operations Management, Volume 26, pp. 536-554. Shamsuzzaman, M. & Wu, Z., 2006. Control Chart Design for Minimizing the Proportion of Defective Units. Journal of Manufacturing Systems, 25(4), pp. 269-278. The Productivity Development Team, 1999. Cellular Manufacturing: One-Piece Flow for Workteams. Oregon: Productivity Press. Wang, J. X., 2011. Lean Manufacturing: Business Bottom-Line Based. Florida: Taylor & Francis. Webber, L. & Wallace, M., 2007. Quality Control for Dummies. New Jersey: Wiley Publishing Inc.. Zhou, M. & Venkatesh, K., 1999. Modeling, Simulation, and Control of Flexible Manufacturing Systems: A Petri Net Approach. New Jersey: World Scientific Publishing Co. Pte. Ltd.. Read More
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