The Improvement of Maintenance System and Documentation

Transcription

1 The Improvement of Maintenance System and Documentation Supachai TAEWANG, Thammasat University, Thailand. Sawat PARARACH, Thammasat University, Thailand. Abstract This paper presents the improvement of the efficiency of the maintenance system and preparation of documentation. The case study is fastening production factory that the production rate could not reach the expectations which resulted in higher costs of production because the workers had to work overtime to serve customer s orders. Using 4 from 8 pillars of the Total Productive Maintenance (TPM) and Six sigma (DMAIC), and documents are implemented. The result shows the machine break downtime decreased by 25% and the OEE rate has risen from 43.38% to 52.15% (increase by 20.22%) which resulted in higher overall efficiency of the machines and made them available to produce more products to serve the quantity that customers need. Key Words: Futures markets, volatility, causality dynamics, volatility transmission, emerging markets JEL Classification: C 19, G13, G 14 1

2 1. Introduction From the study the case and data collection on the sample factory, factory produced steel bolts, fastening device, in the automobile industry. The part production process was semiautomatic. Most of the problems that cause the production to not meet the target was due to break downtime and stopping machine for maintenance resulting increasing the overtime costs, availability efficiency, performance efficiency, and the quality rate of all three decline as well. The overall equipment effectiveness (OEE) is normally the index for TPM implementation. The calculation is as following. OEE = Equipment availability* Performance efficiency*quality rate (1) When the 3 types of information were calculated for the overall equipment effectiveness (OEE), the output was very low. Therefore, the Overall Equipment Effectiveness was used as the index for all extrusion machines in the sample factory. The prototype machine selection criteria to be improved were the machine stopping most, high monthly production, and high value of defects. The prototype machine improvement was done with Total Productive Maintenance as guidelines (Figure 1). Pillars of TPM were also applied in this research to reduce break downtime and to improve the overall equipment effectiveness (OEE). The process of solving the problem with break downtime and to reduce the time for emergency machine repairs and maintenance was done by using the 4 pillars of TPM as guidelines. Pillar 1 is the specific improvement (prototypes improvement), Pillar 2 is self-maintenance (establishing the manual for basic inspection and preventive maintenance machines for machine operating staffs), Pillar 3 is the maintenance plan (establishing the manual for preventive maintenance to reduce the time to perform maintenance with issue reviews and time to perform preventive maintenance every year), Pillar 4 is training (Training on manuals for production and maintenance staffs). The Six Sigma (DMAIC) and QC 7 Tools were also used to help in analyzing and solving problems for corrective action and to improve the overall productivity and continuously. 2. Literature Review Ahuja et al (2008) have been present an overview the literature on Total Productive Maintenance (TPM) implementation practices adopted by the manufacturing organization. The Total Productive Maintenance under the framework of participation of all parties is the overall machine system maintenance by developing human and machine basic. That is by cultivating our love for the machine to think that the machine we are responsible for is ours. Then the skills, knowledge, and the ability to work with others are developed. When human development is done, he machine basic development will be performed. This is done by cleaning the machines and small repairing on machines. It can be seen that cleaning can also increase efficiency of the machines. 2

3 The 8 pillars of TPM are guidelines to systemize the process of laying the structure and guidelines of the management system of the ideas of people in the organization to be moving in the same direction by focusing on the management of the organization and group work to be systematic. The 8 pillars he connection for the operation success. To make the maintenance planning system effective, it is essential to keep track of all the corrective maintenance jobs and preventive maintenance inspections (Aaditya C., 2012). Figure 1: 8 Pillars of TPM, From Japan Institute of Plant Management (JIPM) Pakinai (2012) conducted a study on the introduction of TPM activity for industrial applications. By way of improving performance to enhance the overall equipment effectiveness and to reduce time wasted on machine break downtime by using TPM theory and guidelines in the study by exploring the problems, scopes, and diversity of production factors in the seafood processing industry coupled with (P-M Analysis), QC 7 Tools and 6W 1H techniques to analyze problems. Then the TPM 8 pillars as used as the guideline for solution to set the guideline for improving the machine performance comprised of specific improvements, self-maintenance, and training. Then measure the result from the valuations on OEE, the MTBF, and MTTR. The research findings indicated that TPM performed on machine in seafood production process can increase the OEE value of the sample machine. The value before the improvement was at 54.16%, 67.54% and 58.54%, and after the improvement with Specific improvements, cleaning, and solving problem by TPM Tagging could increase the OEE value to 57.18%, 69.35%, and 78.95%. The implementation of selfmaintenance, skill training, and OPL could increase the MTBF to 9.77, , hours and reduce MTTR by 2.06, and hours. The improvement activities on machines were able to increase the OEE f the sample machines at an average of about 4.58%. Manoon et al (2015) conducted a study on improvement and maintenance of machines in precast concrete manufacturing factory. The researcher conducted the study on system maintenance with the Side shifter as the sample example to analyze the problem. These Six sigma tools (DMAIC) were used to carry 3

4 out activities to improve the system's maintenance sequence, define the problem information, measure the problem sequence grading, and the highest number of break downtime, etc. The analysis on the cause of the problems was done using fishbone chart. When the cause of the problem was known, the improvement was performed. The problem found in the research was usage of bearing that could not handle the weight causing problems with Machine Break downtime that was corrected by replacing the Bearing with more strength and can be used longer. The documentation was improved in the aspect of the maintenance plan, plans to replace machines in the future, and increase in the analysis of the recurring problem. If the problem last longer than one hour, maintenance method standard should be set so that more people can learn and additional updates on other machines. This will make the improvement result in the ability to achieve the set target of Machine downtime% being averagely reduced by 1.96% from the before the improvement of about 5.54% to 3.58%. The researches mentioned above are the application of the pillars of TPM and Six sigma systems as approaches to the research process, which aimed to increase the efficiency of the machines making the machines reliable and able to the produce at the full capacity of the machine. 3. Methodology This research was conducted in two stages by performing activities according to guidelines of TPM with everyone involved. The first, the 4 pillars of TPM: from pillar 1 to pillar 4 and the 6 sigma (DMAIC), OC 7 Tools were used to analyze and improvement implementations. The prototype machine of the sample factory was used to investigate the implementation of activities to improve the efficiency of the machines. The second, the expanding of the results after the improvement were considered. The team apply the 3 pillars of TPM (2-4) to be implemented on the remaining 14 machines, by planning the appropriate maintenance process to be the factory standards on machine inspection, correct procedures, and working methods to meet the goals of the organization by focusing on developing staffs involved with maintenance to have more cognitive maintenance management system used according to the TPM principles to achieve continuous improvement. 3.1 Data Collection Tools Data collection on extrusion machine was done in accordance with the QC 7 theory Machine break downtime was analyzed by bringing the inspection sheet to collect data or machine information that had already been recorded. Pareto chart was used to assist the data analysis. The fish bone was used to analyze problems and find the root cause of the problem to find ways to prevent the recurrence and extension to other. The data collection was done on 15 extrusion machines. The data collected comprised of working hours, stopping hours, stopping cause / symptoms, and yield of good / bad products using data dating back to April. 4

5 This was done to analyze the issues and trends that have been occurring from past to present before proceeding with the plan to fix the problem. The collection and analysis of past to resent data resulted in the awareness of the problems likely cause of Machine break downtime. Machine that was increasingly high when compared with the decreased volume of production. Therefore, the team has not started the machines improvement in August with the machine break downtime was as high as 9,490 minutes using the August data as the data for before updating machines as shown in Figure 2. Figure 2: Monthly Extrusion Machine Break Downtime in 2015 From the preliminary analysis of data from Figure 3: the Machine break downtime distribution from high to low, it can be seen that BP-430 machine had the highest downtime at 1,780 minutes so it was used as the prototype to be improved in order to enhance the productivity of machines in the sample factory. Figure 3: Machine Break Downtime of Extrusion Machine in August 2015 by Machines From Figure 3, the team haก selected a prototype machine, and continue to collect information on problems to be analyzed to figure out the cause of some of the machines 5

6 stopping production. The team proposes the list of items to implement the solutions as shown in Table 1. Table 1: Break Downtime Details of Machines (BP-430 in August 2015) No.1 Equipment Problem Detail Cause of Problem Improvement method 1 2 Machine Equipment Lubrication Systems Machine cycle stop Oil pump supply to machine not smoot alarm error code #5 oil filter dirty Bolt of counter scale loose & tear out Oil Filter dirty, Oil can not flow in machine Take out counter scale of machine & cancel use counter scale Cleaning tank machine oil separate & Cleaning oil filter in machine Time (Min) 920 Remark (results if unuse) Makes configuration work harder. Because there is no indication of the scale takes a long time transfer system Belt conveyer not move Motor damage (coil burn) Send supplier to wire new coil of motor 180 Used spare part 4 transfer system Belt conveyer not move Plate support conveyer to loose Relock Plate support belt conveyer Plate support wear away then product 5 transfer system Plate support wear away Making new plate support with protect product impact with steel (product is demaged) 6 Electric system Machine stop alarm PLC battery low PLC low Battery show Change a new Battery of PLC (Mitsubishi ER17330V/3.6V Type A6BAT) transfer system Belt conveyer not move Magnatic overload relay trip Reset magnatic overload relay & Check electric Down time Total 1780 Table 2: The Average OEE of Machines before Improvement Measurement index OEE Before improvement Machine running rates (A) Machine performance (P) Quality rate (Q) Average From implementing the activities and concluding the preliminary results, those related in the sample factory were informed of the results on machines. When the results were compared with the standard OEE average at 85%, the sample factory OEE was very low at 43.38%, this resulted in the establishment of policies with the administrators and researcher to study the concept of improving to reduce the Machine break downtime and to increase the OEE. The researcher conducted the data collection during improvement implementation starting from April to December, 2015 totaling 9 months with 15 extrusion machines to perform machine system maintenance to be the same approach. 3.2 Implementation of TPM The study was conducted on information of machines used in the production process. The operation plan guidelines were prepared according to TPM. The prototype machine cleaning was arranged. The detection of defects and abnormality were conducted and recorded to plan and find ways to improve. Specific improvements in Table 3 were performed. The problems of high machine break downtime were analyzed to find ways for improvement. Trainings on basic maintenance knowledge that can be practiced by everyone were conducted. Trainings on how to inspect the machine and established preventive 6

7 maintenance were conducted. The staffs correctly and consistently cleaned and performed maintenance on machines. Table 3: The Specific Improvement and Manual Maintenance Implementation 1. The study on machine basic information. 2. Plan for TPM activity application 3. Machine cleaning 4. Specific improvement 5. Monitoring overall machines. 6. Prepare standard inspection / maintenance machines. 7. Training basic knowledge / training standards prepared. 8. To manually check / maintenance manual introduction. 9. Controls the area around the machine clean. 10. Continues self-maintenance The analysis on Figure 4., Fishbone chart was used to help determine the root of cause of the problem. Then, propose specific improvement on the prototype machine are in stopping resulted in the highest downtime at 920-minutes problems caused by the counter scale set falling off the brackets and getting stuck the dye mold. This caused the machine to be unable to produce the piece of work (STD. M x1.25). The fishbone chart was used to analyze the cause to lead to further protection using four main elements: man, machine, method, and material. When the 4 fish bones were achieved, we made assumptions on the possible causes of the scales falling to be tested or to see the actual work site at the machine with the problems and returned to perform summary together with the team to carefully select the topic that was the cause to be used for planning and further improvement. There 3 causes for the counter scale falling: 1) the inappropriate depth of the bolts that held the podium (STD. M x 1.25), 2) lacking of the counter scale installation standard, and 3) lack of the counter scale inspection point as shown in the fishbone chart shown. 7

8 Figure 4: Fishbone Chart Analysis to Find the Cause of the Problem Fishbone Diagram for analysis of Machine BP-430ss Counter Scale Damage From the analysis on the cause of the problem, we take the cause of the problem to be resolved by establishing the counter scales machines installation standard, with the size of the bolts locked into the standard installation methods to prevent non-compliance bolts lock length. Then we improved the machine inspection documentation with appropriated topics added to prevent machine from breaking down. 4. Results and Discussion The results of the research to enhance the overall performance of the machine by Applying TPM with everyone involved by using the 4 pillars of TPM; the specific improvements, manual maintenance, maintenance planning, and training to clarify the document, ways to inspect, and basic maintenance procedures to employees so that employees can solve little fault with the machine. The prototype was implemented with the 4 pillars of TPM activities. The integration the highest machine problem to be improved was done by using the Six sigma (DMAIC) and QC 7 Tools for improving the prototype, preparing the check sheet, preventive maintenance documents. The documents were used for trainings on employees who take care of prototype machines. The improvement activities can reduce the occurrence of Machine break downtime. Machine break downtime before the implementation of activities in August was 1,780 minutes. The activities reduced it by 1360 minutes (76%t) to 420 minutes in December for the prototype. 8

9 Figure 6: Times the Number of Downtime before - After the Implementation The TPM activities with everyone involved rusted so well so the team has expanded the update to the other 14 extrusion machines by adopting Pillar 2, 3, and 4 as operational guidelines to improve the overall efficiency of all extrusion machines of the sample factory. The improvements reduced the Machine break downtime from the Machine break downtime in August was at 9,490 hours and after improvements it was reduced by 2370 minutes for 25% in December to 7,120 minutes. Table 4: Comparison of OEE before- After Improvement OEE Measurement index Before After Machine working rate (A) Machine performance (P) Quality rates (Q) Average Figure 7: Number of Machine Break Downtime before - after on all 15 Extrusion Machines 9

10 The OEE after the improvement increased from 43.38% to 52.15% (20.22%) making the overall performance increased, the results was shown in Table Conclusions and Recommendations This study, applying the Total Productive Maintenance (TPM) on the prototype machine of the sample factory, shows that the production rate could not reach the expectations which resulted in higher costs of production because the workers had to work overtime to serve customer s orders. This Total Productive Maintenance (TPM) application on the machine maintenance aims for the higher efficiency of production by using 4 from 8 pillars of the TPM to reduce machine breakdown time and to improve the efficiency of the machine in order to produce continuously. Researchers have made daily, weekly, and monthly check sheets and also the preventive maintenance manual for the prototype machine of this factory which will lead to standardized and reliable maintenance system. Also, they would help workers to repair the machine by themselves (Autonomous Maintenance). By following the operations plan, the overall efficiency of the prototype machine is better than before. The machine breakdown time before applying the TPM was 1,780 minutes and after applying the TPM was only 420 minutes (1,360 minutes or76%lower). Researchers have also applied the TPM, check sheets and preventive maintenance (PM) manual on compression molding machines so that the machine breakdown time fell from 9,490 minutes to 7,120 minutes. This can reduce crashes of the machines by 2,370 minutes which equals to 25% of OEE (Overall Equipment Effectiveness). By calculating the machines availability, performance efficiency, and quality rate, researchers found that the OEE rate has risen from 43.38% to 52.15% (an increase of 20.22%) which resulted in higher overall efficiency of the machines and made them available to produce more products to serve the quantity that customers need on time. Acknowledgement The researchers would like to thank the sample factory management, Head of Maintenance Department and a team of workers who helped support various activities done to accomplish the goals. References Ahuja I.PS., and Khamba J.S., 2008, Total Productive maintenance: literature review and directions. International Journal of Quality & Reliability Management, Vol. 25 No.7, Aaditya C., 2012, Study the Initiation Steps of Total Productivity Maintenance In An Organization and Its Effect in Improvement of Overall Equipment Efficiency. International Journal of Engineering Research and Applications (IJERA) ISSN: Vol. 2, Issue4, July-August 2012, pp Lixin, M., Shicheng, D., Yunqi, G., and Guiwen, Y. 2011, Study on application of TPM in small and medium-sized enterprises. International Conference on Management Science and Industrial Engineering (MSIE),

11 Phoonpon Saengpa Production enhancement by TPM. Chulalongkorn University Press. Bangkok. Thanee Aumor The TPM with everyone involved (Total Productive Maintenance-TPM). Thailand Productivity Institute. Bangkok. Pakinai M., 2012, Improving of Overall Effectiveness of the Machines in Seafood Production Processes. IE Network Conference, Manoon S., and Sawat P., 2015, Improvement of machine maintenance efficiency of precast concrete factory. 8 th Rajamangala University of Technology International Conference 2015,