OEE Evaluation of Long Life Food Product Line

Transcription

1 OEE Evaluation of Long Life Food Product Line Zafar Mohammad Senior Supervisor Planner, FMCG Company, Kingdom of Saudi Arabia. Gaurav Aggarwal Dairy technologist, FMCG Company, Kingdom of Saudi Arabia. Abstract Overall equipment effectiveness (OEE) is a pioneer methodology to asses performance in industry. This study formulates and analyzes relationship between factory management & operations of cheese production line. Overall effectiveness of machine and line are computed. In addition, components of OEE i.e. on product time (OPT), rate (R) and quality (Q) are also calculated. Downtimes, mean time between failures (MTBF) & mean time to repair data (MTTR) are analyzed to identify the bottlenecks in the production system. The study shows that issues related to on product time (OPT) & quality (Q) should be resolved immediately to optimize productivity and efficiency of the lines. Study which is carried out in 21 weeks have concluded that OEE is 67%, on product time is 80%, rate is 84%, and quality is 96%. Average mean time to repair (MTTR) & Average mean time between failures (MTBF) are calculated as 16 minutes & 32 minutes respectively. This study can be utilized by other beverage and FMCG companies to analyze & improve their production system, design & operations management. Index Terms Overall equipment effectiveness, on time product, rate, quality, mean time to repair, mean time between failure & efficiency. 1. INTRODUCTION Overall equipment effectiveness (OEE) is a controlling & monitoring methodology widely used in industries for continuous improvement in their systems. It acts as a driver for process improvement in production system. OEE is one of the best indicators of performance in line production system. OEE consists of three components on product time (OPT), rate (R) and quality (Q) which measure every aspect of production environment and give a wholesome picture of system efficiency. In present manufacturing scenario, OEE is most widely accepted quantitative tool to measure productivity (Samuel ET la.2002).oee is a Japanese concept introduced by Nakajima (1988). Nakajima introduced OEE as a metric system for total productive maintenance (TPM). TPM is a tool, associated with machinery & equipment. OEE provide actual performance of machines, which act as foundation to formulate strategy for TPM implementation (Ljungberg 1988). OEE provides a central method to decide production & improvement targets for TPM experts. OEE help in incorporating continuous improvement tools with production to achieve a balanced optimization of on product time (OPT), rate (R) and quality (Q) (Bulent et al. 2000).TPM & OEE was implemented by Tsarouhas (2007) on a pizza line to increase its productivity, quality and work environment. Tsarouhas (2007) also emphasized on influence of OEE & TPM to provide healthier & safer work environment. Lots of studies and papers are published reviewing & exploring the benefits of OEE & its components - on product time (OPT), rate (R) and quality (Q). A study is carried out by Muthiah et al (2008) proved that Overall equipment effectiveness (OEE) is very powerful tool to quantify performance at equipment level. Overall equipment effectiveness (OEE) is used to measure the performance of a manufacturing line in his studies by Bragila et al (2009).Nachiappan and Anantharam (2006) described the behavior of OEE and equipment effectiveness as performance measure for a continuous production line. In other study, De Ron and Rooda (2006) defined overall equipment effectiveness (OEE) and equipment efficiency as performance measure of manufacturing equipment. Fleischer et al. (2006) stated that the ability of competitiveness of any company will largely depends on the components of OEE, i.e. on product time (OPT), rate (R) and quality (Q) at its production unit. In this study, the analysis of downtimes & failure data of cheese line is carried out over a period of time. Descriptive performance of machines is carried out on production line. This study also includes all major component of on product time (OPT), rate (R) and quality (Q). The analysis of the data provides a useful insight for managers to make better solution and root cause analysis of the problems. This will also help to reduce breakdowns and improve work improvement. 2. BACKGROUND OEE is a concept introduced by Nakajima in 1988 as a metric system for total productive maintenance. Nakajima have discussed six major losses in his studies. They are as following -: a) The first one is breakdown in equipment. It includes all the engineering failures on machines leading to loss of production time and quality product. ISSN: EverScience Publications 61

2 b) The second loss is change over time, set up time or adjustment of machine parts. This loss is majorly contributed by misalignment of equipments and conveyors. c) Short intervals breakdown during running time leads to ramp up & ramp down loss. This is due to minor malfunction or blockage in machine. d) Slow production and product yield loss is occurred during start up & end up of the machines. e) Defective items & rework produced by the machine is another type of loss generated due to malfunction of machines. These are six losses that are calculated in the components of OEE i.e. - on product time (OPT), rate (R) and quality (Q). Calculation of on product time (OPT) considers first two losses mentioned that are breakdown of equipments and changeover/set up time. Short intervals & slow productions are measured as rate (R) loss. Last type of loss in the list which is production of defective/rework products is considered in quality. The calculations of these components are as following -: On product time = Total time Total downtime X 100 Total time Rate = Total pieces/on product time X 100 Rated speed of machine Quality = Total product Defective product X 100 Total Product These three components give reflection of overall equipment effectiveness as -: O.E.E. = On product time * Rate * Quality O.E.E. = OPT * R * Q This is the expression of OEE, used globally as a metrics of equipment performance & TPM. OEE has a benchmark of 85% for world class. Breakdowns <3 %, on product time> 90 %, rate > 95%, quality>99% is used as the target for world class standard in organizations across the global. The OEE measures provide a strong impetus for introducing manufacturing focus & operations excellence strategy. 3. STUDY OF PRODUCTION PROCESS & OPERATIONS OF CHEESE LINE Cheese is a dairy product which is processed to give variety of flavors and tastes. This study is going to discuss Cheese square portion. Cheese square portion is a breakfast spreadable cheese packed in small packing of 18 grams per serve. This production line consists of six independent machines, kept in a series connect to create smooth flow of product. Each machine has nearly same capacity but have different failure modes & rationales. In case of failure, production department call technical staff to resolve the issue. Production operator is responsible to monitor and collect all the data required calculating OEE. This include -: number of product produced, downtime & repair time on machine, rated capacity of machine & reason of breakdown. This all data collected on log sheet by operator, is then uploaded by department clerk on computer at the end of every shift. Figure 1 Line diagram of Cheese square portion line The above picture shows line diagram for Cheese square portion production line. These machines are -: Blending unit This unit weighs & mixes several types of butter, cheese, cream & powder at different proportions. Blending unit mixes all different ingredients to give homogenous mixture. This gives a perfect blended cheese ready to cook. Heat Treatment Unit This is heating & cooking unit. Heat treatment unit will pasteurizer cheese to kill microorganism. Cooking will bring out the flavor of chesses. Filling unit Pasteurized cheese is packed in foil as 18 grams portion. This portion in foil is sealed with visual tear strips. Secondary Packaging Unit This machine collates 18 grams cheese square portions in array of 6 portions and packs them in secondary box packaging. Spiral Cooling Unit This is a cooling system which consists of spiral conveyors inside a cooling chamber. Cooling of packed cheese square portion is carried out in ISSN: EverScience Publications 62

3 inverted position at 15 degree Celsius. Coding is also carried out after this unit. Palletizer Packed & cooled cheese are now placed in crates manually and crates are palletized by robot. The configuration is 16 crates per pallets. Sale of cheese square portion is quite good. Generally, it has plan but planned downtime is provided regularly for clean in place (CIP) & preventive maintenance activity. Preventive maintenance is one of the important tools of TPM. It not only eliminates breakdowns but also reduces the deterioration, wear and tear in machine. This increases reliability of the cheese square portion line and reduces probability of having breakdown during production. The other kind of planned down time is clean in place (CIP). In food industry, cleanness and hygiene is very important. Clean in process is an exhaustive process of cleaning every part of machine which comes in direct contact or near product. Clean is place is a quality mandate which must be scheduled after every 12 hour of production run. 4. FAILURE DATA DESCRIPTION AND DISCUSSIONS Cheese square portion is batch type production system which is governed by planning team. Planning team updates production plan as per sales demand. Sale of cheese square portion is quite high hence its production lines are busy. But once in a while there is time when no plan is there. Data is collected only for the production time of cheese square portion. This data is collected over the time span of 20 weeks i.e. 140 days. During this period, line runs as per production plan. If there is no plan, then preventive maintenance & CIP was carried out. During production time data is collected by machine operator in the form of log sheet. This study is identifying different component of OEE including on product time (OPT), rate and quality. Mean time to repair (MTTR) & Mean time between failures (MTBF) are also calculated for down time analysis. Mean time to repair (MTTR) is defined as average time required for starting a machine under breakdown. MTTR is the measure of the average time required to repair/start a machine again. It is average time elapse of the machine/line from the time it goes down and once it is again start production. MTTR is only calculated when production is scheduled. If there is no plan or planned downtime, MTTR is not calculated. Less the MTTR better is the machine and its maintenance. Mean time between failures (MTBF) is defined as average time that machine/line run without any major breakdown. It is the time between two consecutive failures that occur on machine/line. MTBF is the measure of reliability on machine/line. It represents how much time a machine/line can run continuously without failures. More the value of mean time between failures, better the machine is. It is calculated on the basis of downtime data provided by operator. 5. FAILURE DATA ANALYSIS & STATISTICS Data for this study is collected for line Cheese square production line over a period of 21 weeks from a FMCG company. Data collected by machine operator uploaded by department clerk on computer. Microsoft access is used as a tool to provide form based data input mechanism to the clerks. Once this data is captured, then Microsoft Excel is used to generate data as per need. Data is presented week wise in following table -: From the above table following observation can be made on the basis of data collected over the period of 5 months -: 1. Cheese square portion line may run continuously for 32 minutes and there may be a breakdown of 16 minutes. 2. Mean time between failures for Cheese square portion line is 32 minutes ranging between 18 minutes to 54 minutes on weekly basis. 3. There is highest continuous run of average 54 minutes is observed in week 6 and second highest continuous run is of 44 minutes in week 12 & week 25. Important point to mention here is - preventive maintenance is carried out in the previous week i.e. in week 4, week 11 & week Mean time to repair for Cheese production line is 16 minutes with very high variation ranging from maximum 68 minutes to minimum 10 minutes. ISSN: EverScience Publications 63

4 5. High variation in mean time to repair represents that line is not operating smoothly. Breakdown maintenance is major type of maintenance carried out on production line. On product time is very much affected by these breakdowns and resulted in low OEE. 6. Count of breakdown is highest in week 21 with value of 343 and lowest in week 20 with value 112. Total number of breakdowns is 4,821 with average of 230 breakdowns per week. This is high count have influenced the rate and quality of the production. This will increase short interval, ramp up & down of machine & defective/ rework production. Water fall model is an advanced presentation tool used to present contribution of each week in total breakdown percentage. It clearly indicated that week 21 has the highest number of breakdowns with total contribution of 7 %. Mean time between failure and Mean time to repair are presented on Histogram. Above graph consists, weeks on absassica and time in minutes at ordinate. Highest MTTR is noticed in week 20 & lowest in week 11. Highest MTBF is noticed in week 6 & lowest in week STUDY OF OVERALL EQUIPMENT EFFECTIVENESS As discussed earlier, overall equipment efficiency consists of three components namely on product time, rate & quality which is presented here on weekly basis. On product time is subjective to breakdowns on machine. On product time is directly related to unscheduled downtime, process set-up, unplanned stoppages and changeovers. It is highly influenced by MTTR & MTBF of line. Rate of Cheese square production line is influenced by number of breakdowns, short intervals and ramp up & down time. Average rate of weeks does not show high variation. Quality is not much influenced because machines are not producing much of defective/rework items. Quality represents good product vs defective product produced by the line. More the value of this component represents better quality system. Overall equipment efficiency is calculated over the period of 21 weeks. To calculate OEE, data for-on product time, rate, quality is collected over the duration. Required data was collected by production staff which is responsible for efficient running of line. OEE data is present on weekly basis. Once data is presented, some improvement steps are taken by departments to control breakdowns or optimize the production rate. Following table represents calculated values of OEE, on product time, rate & time over a period of 21 weeks. ISSN: EverScience Publications 64

5 major reason of drop in overall quality value in study. The graphical represents clearly indicates the best week and worst week for OEE, on product line, rate & quality in Cheese square portion line. For each component the highest and the lowest value are week wise presented. 7. CONCLUSION Above data reveal information about effectiveness of Cheese square portion production line in meeting its target in given time. Following observation can be carried out from above table -: 1. Overall equipment effectiveness of Cheese square portion production line is 67%. It is much below the target OEE of 85%. OEE ranges between maximum 84% to minimum 8% in week 16 & week 20 respectively. It is because of continuous breakdowns, unplanned stoppages & rejection on line. 2. On product time of line is 80% during these months which is low to the target on product time which is 90%. On product time of machine is worst performing component of OEE in this study. OPT is not improved throughout the study because of long breakdowns & improper maintenance of machine. 3. Rate is the performance factor of line. It shows that line can run up to 84% of its rated speed. Rate of the line remains more or less same. Variation is less but still it remains below target of 95%. Rate is low because of unaccounted minor stoppages and ramp up & down in machine. 4. Food industries are very conscious about quality of product. Quality of the production is near the target of 99%. Quality is observed as 96% with very high consistency of 99% per week. In fact due to some major breakdowns in week 20 is considered as the This study represents an approach to find efficiency and effectiveness of Cheese square production line. This study uses on product time, rate & quality as components to examine the ability of the current process to deliver products as per plan. It provides identification of bottlenecks in process. This case study presents performance evaluating mechanism of production line in a multinational FMCG company. The study calculated the value of mean time to repair & mean time between failures using data compiled by machine operators over the period of 21 weeks. Data is further used to calculate OPT, rate, quality & OEE to monitor & present real time scenario on floor. Study carried out in 5 months concluded that OEE, on product time, rate, and quality are 67%, 80%, 84% & 96% respectively. Average mean time to repair (MTTR) is calculated as 16 minutes & Average mean time between failures (MTBF) is calculated as 32 minutes. These low figures of OEE, OPT, rate, quality & MTBF indicates towards the need of improvements on production & maintenance system. It also represents that line is under breakdown maintenance and lots of work is required to be done to improve OEE. This study has provided ground for implementing Total productive maintenance (TPM) on this production line. In addition of TPM, Short Interval Control (SIC) & DMAIC are to also be introduced for better OEE in upcoming days. REFERENCES [1] Samuel, H.H., et al., Manufacturing system modeling for productive improvement. Journal of manufacturing systems, 21(4), ISSN: EverScience Publications 65

6 [2] Nakajima, S., Introduction of TPM: total productive maintenance. Cambridge, MA: Productivity Press Inc. [3] Ljungberg, O., Measurement of overall equipment effectiveness as a basis for TPM activities. International Journal of Operations & Production Management, 18 (5), [4] Bulent, D., Tugwell, P., and Greatbanks, R., Overall equipment effectiveness as a measure of operational improvement a practical analysis. International Journal of Operations & production management, 20 (12), [5] Tsarouhas, P., Implementation of total productive maintenance in food industry: a case study. Journal of Quality in Maintenance Engineering, 13(1), [6] Muthiah, K.M.N., Huang, S.H., and Mahadevan, S., Automating factory performance diagnostic using overall throughput effectiveness (OTE) metrics. Internation Journal of Advanced Manufacturing Technology, 36 (13), [7] Braglia, M, Frosoline., and Zammori, F., Overall equipment effectiveness of a manufacturing line (OEEML): an integrated approach to asses systems performance. Journal of Manufacturing Technology, Management, 20 (1), [8] Nachiappan, R.N. and Anantharam, N., Evaluation of overall line effectiveness (OLE) in a continuous product line manufacturing system. Journal of Manufacturing Technology Management, 17(7), ISSN: EverScience Publications 66