Implementation of Autonomous Maintenance and Kaizen to Enhance Overall Equipment Efficiency in an Apparel Manufacturing Unit.

Transcription

1 Implementation of Autonomous Maintenance and Kaizen to Enhance Overall Equipment Efficiency in an Apparel Manufacturing Unit. By MD.AL-AMIN BIN KHALIL This thesis has been submitted in partial fulfilment of the requirement for the degree of Master of Engineering in Advanced Engineering Management (AEM). Department of Industrial and Production Engineering (IPE) Bangladesh University of Engineering & Technology (BUET), Dhaka-1000, Bangladesh. December 08, 2015 i

2 CERTIFICATE OF APPROVAL The thesis titled- Implementation of Autonomous Maintenance and Kaizen to Enhance Overall Equipment Efficiency in an Apparel Manufacturing Unit submitted by Md. Al-Amin Bin Khalil, Roll No , Session April 2011 has been accepted as satisfactory towards partial fulfilment of the requirement for the degree of Master of Engineering in Advanced Engineering Management on December 08, BOARD OF EXAMINERS Dr. A. K. M. Masud Professor Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology Chairman (Supervisor) Dr. Md. Ahsan Akhtar Hasin Professor Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology Member Dr. Abdullahil Azeem Professor Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology Member ii

3 DECLARATION It is hereby declared that this thesis paper or any part of it has not been submitted elsewhere for the award of any degree or diploma. Counter Signed, Dr. A. K. M. Masud Supervisor, Professor, Department of Industrial and Production Engineering, BUET, Dhaka-1000 Md. Al-Amin Bin Khalil iii

4 ACKNOWLEDGEMENT First of all I am very much grateful to almighty Allah, the most merciful, for giving me the knowledge, energy, patience or ability to successfully complete the thesis paper and to attain a Master degree of Advanced Engineering Management (AEM). I would like to express my deep indebtedness and gratitude to my teacher and thesis supervisor Dr. A. K. M. Masud,professor, Department of Industrial and Production Engineering, BUET, for his constant inspiration, guidance, valuable and constructive suggestions and supervision in preparation and completion of this thesis paper. My sincerest gratitude to all the individuals of East West Industrial Park Limited, Gazipur, who directly or indirectly helped me in many instance through giving their support to find out the outcomes from pilot line. In addition, I would like to thank and would be grateful to my project director, Tanvir Ziaur Rashid, East West Industrial Park Limited who assist me to sanction a time for higher study. In spite of being a regular employee I got the opportunity from him to complete my thesis work as a like as full time student. Finally I would like to thank my respected teachers of the department, classmates, friends and family members who directly or indirectly gave encouragement and suggestions to complete my thesis work. iv

5 ABSTRACT Proper utilization of resources can increase the potential benefit of an organization. Like all other organization, apparel manufacturing industry also works with different resources (Man, machine, material, method and money) from individual sectors such as knitting, dyeing, cutting, sewing, finishing etc. Where still there are lots of hidden opportunities are remaining to explore. Hence, Kaizen and autonomous maintenance are likely to be more applicable progress tool to increase the overall equipment efficiency (OEE) percentage for such types of organizations. Taking into consideration of the importance of kaizen and autonomous maintenance (AM) for apparel manufacturing industry specially in cutting and sewing section, this thesis paper explains the implementation procedure of kaizen and AM in a pilot line to increase the OEE percentage. The present study is performed with a well reputed apparel industry in Bangladesh named East West Industrial Park Limited. It is explained here how OEE percentage can be increased by applying kaizen and increasing the number of trained motivated worker for basic maintenance work along with other related techniques. A sewing floor and its cutting section are considered to implement this study, and OEE percentages as well as AM ratio are compared before and after implementing the mentioned techniques. The study reveals some root causes in the system, which hinders efficiency level. On the basis of this study, some improvement strategies are presented. Analytical results from the study confirm that the company can achieve substantial improvement in their existing OEE percentage, if it implements the proposed techniques in rest of the line also. v

6 TABLE OF CONTENTS Acknowledgement Abstract Table of Contents List of Figures List of Tables Nomenclature iv v vi viiii ix x Chapter One: Introduction Introduction Objectives 2 Chapter Two: Literature Review Introduction Maintenance and its Types TPM and its Pillars Overall Equipment Efficiency (OEE) Six major losses that can impede equipment effectiveness 17 Chapter Three: Research methodology Introduction Design of the thesis Identification of losses and their Measurement Data Collection & Data Analysis Monthly Loss Identification & Classification Calculation &comparison of OEE during first three month (1 st stage) Problem Identification & Possible solution Stage-2 34 vi

7 3.3.1 Pareto Analysis for significant losses Vital few causes Identification Analytical Technique to minimize the losses Why Why Because Logical Analysis (WWBLA) Why Why Because Logical Analysis (WWBLA) Why Why Because Logical Analysis (WWBLA) Summary of root causes Summary of countermeasures taken & their impact Autonomous maintenance details Result comparison and evaluation Stage Impact of WWBLA for loss reduction Comparison of vital few causes Impact of WWBLA for OEE improvement 56 Chapter Four: Findings and Analysis Introduction Six big losses in stage-1 & stage Comparison of vital few causes in stage-1 and stage Monthly Significant Loss status Monthly OEE Status 60 Chapter Five: Conclusions and Recommendations Conclusion Recommendation 64 References 66 vii

8 Figures LIST OF FIGURES Page No Figure 2.1: TPM Pillars 7 Figure 2.2: Cleaning Circle 10 Figure 2.3: The Role of cleaning in autonomous maintenance 10 Figure 2.4: Three Factors of OEE 15 Figure 3.1: Thesis activity in framework 21 Figure 3.2: Loss Pareto Chart 34 Figure 3.3: Cause Pareto Chart 36 Figure 3.4: Cutting Section WI 42 Figure 3.5: Uses of pinches during cutiing 47 Figure 3.6: Basic maintenance training & skill upgrading chart 45 Figure 3.7: Buddy for new worker 46 Figure 3.8 Basic Maintenance (BM) Flow diagram 47 Figure 3.9: Maintenance Signal 48 Figure 3.10: Maintenance Signal with before after comparison 48 Figure 3.11: Redesign of workstation 50 Figure 3.12: Autonomous Maintenance Details 50 Figure 3.13: Continuous Improvement Newsletter 53 Figure 3.14: Loss comparison with stage 1 & stage 2 54 Figure 3.15: Causes of production loses comparison with stage 1 & stage 2 55 viii

9 Figure 4.1: Loss comparison with stage 1 & stage 2 58 Figure 4.2: Causes of production losses comparison with stage 1 & stage 2 59 Figure 4.3: Month wise significant loss status 60 Figure 4.4: Monthly status of Availability, Performance, Quality 61 Figure 4.5: Month wise three factors of OEE 62 Figure 4.6: Monthly OEE Status 62 ix

10 Table LIST OF TABLES Page no Table 3.1: Six Major Losses 22 Table 3.2: Monthly Data Collection Sheet 24 Table 3.3: Six major Losses in chart (1 st stage) 25 Table 3.4: Six major losses in chart (2 nd stage) 29 Table 3.5: Overall Equipment Efficiency (OEE) Calculation 33 Table 3.6: Production Losses in stage-1 34 Table 3.7: Causes of production loss in Stage-1 35 Table 3.8: Tentative standard for Autonomous maintenance 51 Table 3.9: Loss comparison chart with stage-1 & stage-2 54 Table 3.10: Vital few causes comparison chart with stage-1 & stage-2 55 Table 3.11: Overall Equipment Efficiency (OEE) Calculation 56 Table 4.1: Loss comparison chart with stage-1 & stage-2 57 Table 4.2: Vital few causes comparison chart with stage-1 & stage-2 58 Table 4.3: Monthly Status of Major Losses 59 Table 4.4: Monthly OEE Status 60 Table 4.5: KPI Follow up chart 63 x

11 NOMENCLATURE AM APW BM DNLS EWIPL GSM KPI M/C NPT OEE RCA RMG SNLS SMV TPM WWBLA WI Autonomous Maintenance Automatic Pocket Welt Basic Maintenance Double Needle Lock Stitch East West Industrial Park Limited Gram per square meter Key performance Indicator Machine Non Productive time Overall Equipment Efficiency Root Cause Analysis Ready Made Garments Single Needle Lock Stitch Standard Minute Value Total Productive maintenance Why Why Because Logical Analysis Work Instruction xi

12 Chapter 1 Introduction 1.1 Introduction In industrial environment it has been seen that some challenges have been faced such as rapidly changing products, changing style, colour, changing technologies, complex product flow, reworks etc. Along with some other challenges have to face regard the correct efficient use of the resources available both operational and manpower for the production. To survive in global competitive market most manufacturing companies focus their manufacturing strategies on minimizing their production costs, increasing productivity, improving product quality, resources utilization, and increasing customer satisfaction. In apparel industry high productivity through appropriate distribution of these resources and adequate operational procedures becomes a priority. However productivity in such production systems depends directly on the efficiency of their critical operations or bottlenecks [1].In this competitive world total elimination of every waste is necessary for the endurance of any apparel industry. The wastes generated due to the failure, shutdown of facilities that have been built with huge investment and also waste such as defective products should be absolutely eliminated. In a manufacturing scenario, the desirable productivity, cost, inventory, quality and delivery all depend on the efficient functioning of the company s facilities. The philosophies like, total quality management (TQM), just in time (JIT), flexible manufacturing systems (FMS),etc have led to a comprehensive maintenance technique known as total productive maintenance (TPM) that can ensure efficient functioning and optimum utilization of resources [2]. TPM is a unique Japanese system of plant management, developed from preventive maintenance concept. This approach emphasizes the role of teamwork, small group activities, and the participation of all employees to accomplish equipment improvement objectives [3]. It challenges a sense of joint responsibility between operators and maintenance workers, not only to keep the machines running smoothly, but also to extend and optimize their overall performance [4]. TPM is intended to bring both functions (production and maintenance) together by a combination of good working practices, team working and continuous improvement [5]. 1

13 Total productive maintenance (TPM) methodology is a proven approach to increase overall equipment efficiency (OEE) of equipment. It consists of eight pillars; focused improvement and autonomous maintenance are two important pillars amongst them to enhance overall equipment efficiency. These pillars aim to educate the participants in the concepts and philosophy of equipment maintenance and give them an opportunity to develop their skills and confidence level. East west Industrial Park Limited (EWIPL), an apparel manufacturing industry in Bangladesh, was experiencing low productivity and less profit. But in reality, exports of textiles, clothing, and ready-made garments (RMG) accounted for 77 percent of Bangladesh s total merchandise exports in By 2005 the apparel manufacturing was the multibillion-dollar manufacturing and export industry in Bangladesh, accounting for 75 percent of the country s earnings in that year. Bangladesh s export trade is now dominated by the apparel industry. In 2012 Bangladesh s garment exports- mainly to the US and Europe- made up nearly 80 percent of the country s export income. By 2014 RMG represented percent of Bangladesh s total export [15]. The reasons of low productivity and possible means of improvement were then investigated by applying Total Productive Maintenance (TPM). This study explains the activities of implementing two important pillars of TPM concepts (Autonomous maintenance and Kaizen) at cutting and sewing section of EWIPL. Overall equipment Efficiency (OEE) is used to measure the overall performance of the sewing and cutting equipment and suitable data is considered for the analysis. The areas of equipment improvement are identified and why-why method of root cause analysis (RCA) is used for elimination of equipment problems. Kaizen, WWBLA and Autonomous Maintenance ratio (AM ratio) are used to enhance the OEE. The improved OEE resulted increase in availability, better utilization of resources, high quality products and also raised employee morale and confidence. 1.2 Objectives of this Study The main objectives of this study are: a. To improve AM ratio. b. To apply WWBLA methodology for analysis of failures and production line downtimes in order to optimize the efficiency of resources used in cutting and sewing section. c. To reduce the rework percentage from sewing and cutting section. d. To improve OEE of cutting and sewing equipments. 2

14 Chapter 2 Literature Review 2.1 Introduction In competitive market, modern manufacturing concept always tries to minimize the waste from entire workplace. These wastes are causes due to unplanned material distribution, poor work plan, manpower absenteeism, machine break down and mainly poor or having no proper maintenance activities. Equipment that does not operate well or is always breaking down causes more work for everyone and can cause customer dissatisfaction. If equipment breaks down during production, many other processes can be affected. Production equipment not being able to produce products with normal equipment performance is due to six major losses like Start up Loss, Setup/Adjustment Loss, Reduced Yield loss, Reduced Speed Loss, Breakdown Loss, and Defect Loss. If repetitive breakdown of machineries can reduce it brings result in two ways by decreasing the waiting time and improving the productivity. According Hansen (2001) performance evaluation is one of the key tools to determine world class companies. The OEE metric launched by Nakajima (1988), in order to measures productivity of individual production equipment, in a factory. The OEE is defined as a measure of total equipment performance, that is, the degree to which the equipment is doing what it is supposed to do (Williamson). OEE metric identifies and measures main production losses such as availability, performance and quality. Therefore OEE can be used as a key tool to improve equipments efficiency and consequently increase productivity. According to the presentation at the 1999 Society maintenance reliability professional conference, Rohm and Haas Corporation determined that developing hidden capacity of existing factories was ten times less expensive than building new capacity (Hansen 2001). On the other hands if the OEE is 50%, means half the factory is not contributing, but still consumes resource (shiresystem 2011) [6]. To increase overall equipment efficiency production department can participates in Total productive maintenance through autonomous maintenance performed by operators. The purpose of an autonomous maintenance program is threefold [7]. First, it brings production and maintenance people together to accomplish a common goal to stabilize equipment conditions and halt accelerated deterioration. Operators learn to carry out important daily tasks that maintenance personnel rarely have time for. These tasks include cleaning and inspection, 3

15 lubrication, precision checks, and other light maintenance tasks, including simple replacements and repairs in some environments. Second, an autonomous maintenance program is designed to help operators learn more about how their equipment functions, what common problems can occur and why and how those problems can be prevented by the early detection and treatment of abnormal conditions. Third, the program prepares operators to be active partners with maintenance and engineering personnel in improving the overall performance and reliability of equipment. Traditionally, the general attitude on the shop floor has been I run it, you fix it [7]. Operators were responsible only for setting up workplaces, operating the equipment, and checking the quality of processed work. All management of the equipment s condition was the responsibility of maintenance staff. By now it should be clear that this way of thinking does not promote optimal equipment performance. The alternatives are sad indeed, because operators can easily prevent many breakdowns and quality problems by learning how to recognize abnormal conditions. A great deal of this learning can come about simply through physical contact with the equipment by taking a little time to tighten loose bolts, lubricating dry parts and cleaning away dirt, and by noticing dirt or grime on friction surfaces and switches conditions that can shorten equipment life. This approach is becoming increasingly important as factories introduce more robots and automated systems. Most important things are the ability to look at the quality of the products and the performance of the equipment and notice when something is not right [7]. This depends on the following three skills: 1. Knowing how to distinguish between normal and abnormal conditions (the ability to establish equipment conditions). 2. Knowing how to ensure that normal equipment conditions are met (the ability to maintain equipment conditions). 3. Knowing how to respond quickly to abnormalities (the ability to restore equipment conditions). 4

16 When operators have mastered all three skills, they will understand the equipment well enough to recognize the causes of future problems. They will realise when the machine is about to produce defects or break down and will also be able to respond quickly [7]. 2.2 Maintenance and its types: Maintenance Maintenance can be viewed as a combination of actions carried out in order to replace, repair or modify the components, items, and units of a plant so that it will continue to operate at specified availability over a specified time. 1. Breakdown maintenance: It means that people waits until equipment fails and repair it. Such a thing could be used when the equipment failure does not significantly affect the operation or production or generate any significant loss other than repair cost [8]. 2. Preventive maintenance (1951): It is a daily maintenance (cleaning, inspection, oiling and re-tightening), design to retain the healthy condition of equipment and prevent failure through the prevention of deterioration, periodic inspection or equipment condition diagnosis, to measure deterioration. It is further divided into periodic maintenance, predictive maintenance and autonomous maintenance also. Just like human life is extended by preventive medicine, the equipment service life can be prolonged by doing preventive maintenance [8]. 2a. Periodic maintenance (Time based maintenance - TBM): Time based maintenance consists of periodically inspecting, servicing and cleaning equipment and replacing parts to prevent sudden failure and process problems [8]. 2b. Predictive maintenance: This is a method in which the service life of important part is predicted based on inspection or diagnosis, in order to use the parts to the limit of their service life. Compared to periodic 5

17 maintenance, predictive maintenance is condition based maintenance. It manages trend values, by measuring and analyzing data about deterioration and employs a surveillance system, designed to monitor conditions through an on-line system [8]. 3. Corrective maintenance (1957): It improves equipment and its components so that preventive maintenance can be carried out reliably. Equipment with design weakness must be redesigned to improve reliability or improving maintainability [8]. 4. Maintenance prevention (1960): It indicates the design of new equipment. Weakness of current machines are sufficiently studied (on site information leading to failure prevention, easier maintenance and prevents of defects, safety and ease of manufacturing) and are incorporated before commissioning a new equipment [8]. 5. Total Productive Maintenance (TPM) Total Productive Maintenance (TPM) is a practise that combines preventive maintenance with total quality management and total employee involvement. Operations and maintenance team work together to identify areas in equipment maintenance. In a TPM implementation operators take ownership of their equipment for better maintenance and improved productivity. This approach emphasizes the role of team work, small group activities, and the participation of all employees to accomplish equipment improvement objectives. It challenges a sense of joint responsibility between operators and maintenance workers, not only to keep the machines running smoothly, but also to extend and optimize their overall performance [8]. 2.3 TPM and its pillars: Total Productive Maintenance is an innovative Japanese concept, the origin of which can be traced back to the early 1950s when preventive maintenance was introduced in Japan. The concept of preventive maintenance originated in the USA. Preventive maintenance is the concept of daily maintenance designed to maintain equipment in good condition and prevent failure 6

18 through the prevention of deterioration and periodic inspections. Nippondenso was the first company to introduce plant-wide preventive maintenance in 1960 [9]. The principle activities of TPM are organized as pillars. Depending on the author, the naming and number of the pillars may differ slightly; however, the generally accepted model is based on Nakajima s eight pillars (Nakajima 1984; Nakajima 1988) [10]. As presented in Figure 2.1 Figure 2.1: TPM Pillars 5 S TPM starts with 5S. Problems cannot be clearly seen when the work place is unorganized. Cleaning and organizing the workplace helps the team to uncover problems. Making problems visible is the first step of improvement. SEIRI - Sort: Seiri means sorting and organizing the items as critical, important, frequently used items, or items that are not currently needed. Unwanted items can be salvaged. Critical items should be 7

19 kept for use nearby and items that are not needed in near future should be stored someplace else. For this step, the priority of the item should be decided based upon utility and not cost. As a result of this step, the search time is reduced SEITON - Organize: The concept here is that "A place for everything, and everything in its place". After usage items should be stored in their designated storage location. To identify items easily, name plates and colored tags can be used. Vertical racks can be used for organization. SEISO - Shine: Seiso involves cleaning the workplace and ensuring equipment is free of burrs, loose wires, grease, oil, waste, scrap, etc. SEIKETSU - Standardization: Associates decide together on standards for keeping the workplace, machines, and pathways neat and clean. These standards are implemented for whole organization and are regularly checked. SHITSUKE - Self Discipline: Accepting 5S as a way of life forms self-discipline among the associates. This includes wearing badges, following work procedures, punctuality, dedication to the organization, etc. Autonomous Maintenance Jishu Hozen, which means autonomous or self-maintenance is daily preventive maintenance (cleaning, inspection, lubrication and re-tightening) performed by the equipment operator. Autonomous maintenance is one of the most important basic building blocks of TPM program.autonomous maintenance, promotes development of production operators to be able to take care of small maintenance tasks, such as cleaning, inspecting, and lubricating their equipment, thus freeing the maintenance associates to spend time on more value-added activities and technical repairs. The operators are responsible for upkeep of their equipment to prevent it from deteriorating. Jishu Hozen (JH) has been shown to reduce oil consumption by 50% and process time by 50%.Autonomous maintenance does have a valid role in the modern maintenance strategy. Historically, maintenance has been done by dedicated, highly skilled employees. But machine operators are around the equipment all of the time, and should be the first to identify oil/grease and air leaks and vibrations because of lose nuts and bolts. It means that operators perform certain equipment maintenance activities and that maintenance crafts get closely involved in the daily operation of equipment. The focus of the operating team is on 8

20 cleaning, inspecting, lubricating, monitoring and other such essential daily tasks traditionally within the domain of the maintenance department.the operators are responsible for upkeep of their equipment to prevent it from deteriorating According to Mobley, operators can make or break maintenance effectiveness. When implemented fully, Autonomous Maintenance could dramatically improve productivity, quality and reduce costs. Autonomous Maintenance is an approach to eliminate/reduce losses in the plant (time & cost) and equipment management that involves all employees (officers, supervisors & operators) from production, maintenance and administration departments. So the operators should work closely together with the maintenance people, and they can do this in 3 ways: 1. They can alert maintenance people 2. They can provide excellent information 3. They can perform routine maintenance Autonomous Maintenance is a critical first step of TPM, and operators must be trained to close the gap between them and the maintenance staff, making it easier for both to work as one team. Steps in autonomous maintenance: The below mentioned steps should be taken to implement autonomous maintenance 1. Training of the employees: Employees should be educated about the TPM, its advantages, AM advantages, and steps in AM and also about the equipment they use, the frequency of oiling, day-to-day maintenance activities required and the abnormalities that could occur in the machine and way to find out the abnormalities. 2. Initial clean up of machines: Management should arrange all items needed for cleaning. On the very first day, operators clean the equipment with the help of maintenance department. A TPM jingle associated with Initial Clean summarizes the driving concept. Below figure 2.2 is for the explanation of cleaning circle. 9

21 Figure 2.2: Cleaning Circle This Concept can be presented graphically as in figure 2.3 Clean To Inspect Equipment Inspect Equipment To discover abnormalities Discover Abnormalities To restore equipment Restore Equipment To improve performance Improve performance To increase pride in operation Figure 2.3: The Role of cleaning in autonomous maintenance 10

22 3. Counter measures: Inaccessible regions had to be reached easily. 4. Tentative standard: A standard schedule has to be made and followed strictly. Schedule should be made regarding cleaning, inspection, and lubrication and it also should include details like when what and how. 5. General Inspection: The employees are trained in discipline like pneumatics, electrical, hydraulics, lubricant and coolant, drives, bolts, nuts and safety. This is necessary to improve the technical skills of employees and to use inspections manuals correctly. 6. Autonomous Inspection: New methods of cleaning and lubricating are used. Each employee prepares his own autonomous chart/ schedule in consultation with supervisor. Parts, which have never given problem, or part, which don t need any inspection, are removed from list permanently based on experience including good quality machine parts. 7. Standardization: Up to the previous step only the machinery/ equipment was the concentration. However in this step the surroundings of machinery are organized. Necessary items should be organized, such that there is no searching and searching time is reduced. Everybody should follow the work instructions strictly. Necessary spares for equipments is planned and procured. 8. Autonomous management: OEE and OPE and other TPM targets must be achieved by continuous improve through Kaizen. PDCA (Plan Do Check Act) cycle must be implemented for Kaizen [11]. Focused Improvement Pillar (Kobetsu Kaizen) "Kai" means change, and "Zen" means good (for the better). Basically kaizen is for small improvements, but carried out on a continual basis and involve all people in the organization. Kaizen is opposite to big spectacular innovations. Kaizen requires no or little investment. The principle behind is that "a very large number of small improvements are more effective in an organizational environment than a few improvements of large value. This pillar is aimed at reducing losses in the workplace that affect our efficiencies. By using a detailed and thorough procedure we eliminate losses in a systematic method using various Kaizen tools. Some basic tools are commonly used in TPM to analyze & Improvement [12]. These are following: 11

23 1) Pareto Charts. 2) 5-Why Analysis. 3) Fishbone Diagrams. 4) P-M Analysis. 5) Fault Tree Analysis (FTA). 6) Failure Mode and Effects Analysis (FMEA). Planned Maintenance Pillar The goal of planned maintenance is to have trouble-free machines and equipment that produce defect-free products for total customer satisfaction. Planned Maintenance achieves and sustains availability of machines at an optimum maintenance cost, reduces spares inventory, and improves reliability and maintainability of machines. With Planned Maintenance the associates efforts evolve from a reactive approach to a proactive method and trained maintenance staff helps train the operators to better maintain their equipment. Steps in Planned Maintenance include: 1. Evaluate and record present equipment status. 2. Restore deterioration and improve weaknesses. 3. Build information management system. 4. Prepare time-based data system, select equipment, parts, and team, and make plan. 5. Prepare predictive maintenance system by introducing equipment diagnostic techniques. 6. Evaluate planned maintenance. Quality Maintenance Pillar Quality Maintenance (QM) targets customer satisfaction through defect free manufacturing of the highest quality products. The focus is on eliminating non-conformances in a systematic manner. Through QM we gain an understanding of what parts of the equipment affect product quality, eliminate quality concerns, and then move to potential quality concerns. The transition is from reactive to proactive (From Quality Control to Quality Assurance). QM activities control equipment conditions to prevent quality defects, based on the concept of maintaining perfect equipment to maintain perfect quality of products. These conditions are 12

24 checked and measured in time series to verify that measured values are within standard values to prevent defects. The transition of measured values is trended to predict possibilities of defects occurring and to take countermeasures before defects occur. QM activities to support Quality Assurance through defect free conditions and control of equipment. The focus is on effective implementation of operator quality assurance and detection and segregation of defects at the source. Opportunities for designing Poka-Yoke (foolproof system) are investigated and implemented as practicable. Training Pillar The goal of training is to have multi-skilled revitalized employees whose morale is high and who are eager to come to work and perform all required functions effectively and independently. The focus is on achieving and sustaining zero losses due to lack of knowledge / skills / techniques. Ideally, we would create a factory full of experts. Operators must upgrade their skills through education and training. It is not sufficient for operators to learn how to do something; they should also learn why they are doing it and when it should be done. Through experience operators gain know-how to address a specific problem, but they do so without knowing the root cause of the problem and when and why they should be doing it. Hence it becomes necessary to train operators on knowing why. This will enable the operators to maintain their own machines, understand why failures occur, and suggest ways of avoiding the failures occurring again. Office TPM Office TPM should be started after activating four other pillars of TPM (Jishu Hozen, Kobetsu Kaizen, Quality Maintenance, and Planned Maintenance). Office TPM must be followed to improve productivity, efficiency in the administrative functions, and identify and eliminate losses. This includes analyzing processes and procedures towards increased office automation. Office TPM addresses twelve major losses: 1. Processing loss 2. Cost loss including in areas such as procurement, accounts, marketing, sales leading to high inventories 3. Communication loss 4. Idle loss 13

25 5. Set-up loss 6. Accuracy loss 7. Office equipment breakdown 8. Communication channel breakdown, telephone and fax lines 9. Time spent on retrieval of information 10. Unavailability of correct on-line stock status 11. Customer complaints due to logistics 12. Expenses on emergency dispatches/purchases Improving the office efficiency by eliminating the above-listed losses helps in achieving Total Productive Maintenance. Safety, Health and Environment Pillar The target of the Safety, Health & Environment pillar is: 1. Zero accidents, 2. Zero health damage, and 3. Zero fires. The focus is on creating a safe workplace and surrounding areas that are not damaged by our process or procedures. This pillar plays an active role in each of the other pillars on a regular basis. 2.4 Overall equipment efficiency (OEE) Overall equipment efficiency is used as an indicator of how well equipment is used in batch/lot production. The overall equipment efficiency is obtained in relation to losses that can impede equipment efficiency. The magnitude of stoppage less is expressed availability, that of performance less as performance rate, and that of defect loss as quality products rate ratio. The product of the three ratios is called overall equipment efficiency. OEE is the most effective measure for driving plant improvement. It continuously focuses the plant on the concept of zero-waste [13]. 14

26 Components of OEE OEE is a function of availability, performance rate and quality rate of the machine, production line or factory [14]. These factors are following, which has been presented in figure 2.4 Availability (A) Performance (P) Quality (Q) Availability OEE Performance Quality Figure 2.4: Three factors of OEE Empirically, the targets have been 90% or higher in the case of availability, 95% or higher in the case of performance rate, and 99% or higher in the case of quality products rate. The overall equipment efficiency has been targeted at 85% or higher. 15

27 Availability The percentage of time that a machine is actually able to produce parts out of the total time that it should be able to produce parts. This number includes breakdowns, setups, and adjustments. The calculation for availability is simply the actual production time, including set up, out of the planned production time. Examples include equipment failures, material shortages, and changeover time. Changeover time is included in OEE analysis, since it is a form of down time. While it may not be possible to eliminate changeover time, in most cases it can be reduced. The remaining available time is called Operating Time. Performance Performance is in theory very simple. It is the actual achieved run rate against the ideal run rate for the machine. Often the machine ideal or optimum run rate may be the figure published by the machine manufacturer. However, we all know that the ideal run rate may be affected by the situation of the machine, heat, cold, product running through etc. Performance takes into account Speed Loss, which includes any factors that cause the process to operate at less than the maximum possible speed, when running. Examples include machine wear, substandard materials, and operator inefficiency. The remaining available time is called Net Operating Time. Quality The final factor on the overall OEE calculation is quality. This is simply a measure of good product divided by the total product (for the job, shift, day, week etc). Quality takes into account Quality Loss, which accounts for produced pieces that do not meet quality standards, including pieces that require rework. The remaining time is called Fully Productive Time. 16

28 2.5 Six major losses that can impede equipment effectiveness In TPM, 16 major losses are addressed as problems hampering production system effectiveness. Of these, the following six losses are addressed as the ones that impede equipment effectiveness [8]: [1] Failure losses [2] Set-up/adjustment losses [3] Start-up losses [4] Minor stoppage/idling losses [5] Speed loss [6] Defect and rework losses Downtime losses (1) Breakdown losses categorized as time losses and quantity losses caused by equipment failure or breakdown. For example, a breakdown of generator in an apparel industry leads to downtime and thus production loss. (2) Set-up and adjustment losses occur when production is changing over from requirement of one item to another. In apparel sector, this type of loss is encountered during new lay out, set-ups between different styles, and fine-tuning of machines and instruments. Speed losses (3) Idling and minor stoppage losses occur when production is interrupted by temporary malfunction or when machine is idling. For example dirty photocells on Automatic Pocket Welting (APW) machines cause minor stoppages. Though they are quickly fixed, much capacity is lost due to their frequency. Reduced speed losses (4) Reduced speed losses refer to the difference between equipment design speed and actual operating speed. In apparel industry, uses of poor quality materials such as needle, thread etc. causes longer processing time that leads to speed losses of machines. 17

29 Quality Losses (5) Quality defects and rework are losses in quality caused by malfunctioning production equipment. For example, poor condition of cutting table and bend knife are responsible to supply defective fabric cut panel in sewing section. Reduced yield (6) Reduced yield during start-up are yield losses that occur from machine start-up to stabilization. For example, in apparel industry any types of alteration at the initial stage of production, at the time of layout leads to reduced yields. The six big losses are measured by OEE, which is a function of availability (A), performance (P) and Quality rate (Q). Therefore: O E E = A * P * Q Calculation of OEE OEE calculation procedure has been presented as below: Equipment Six Big Losses Computation of OEE Loading Time Equipment failure Availability=Operating Time/Loading time Operating Time Net Operating Time Perfor mance Loss Downtime Loss Set Up & Adjustment Idling & Minor Stoppage Reduced Speed Performance Rate= (Standard cycle time* Product unit processed/operating time) Effective Operating Time Defect Loss Defects in Process Reduced Yield Quality Rate= (Product unit processed Defect Units/ Product unit processed) Overall equipment efficiency = AvailabilityPerformance ratequality products rate 18

30 Chapter 3 Research Methodology 3.1 Introduction This chapter contains the discussion of the methodology of this research. A research methodology defines what the activity of research is, how to proceed, how to measure progress, and what constitutes success. This chapter highlights how the problems ware explored, with specific reference made to how the work stations were selected and the procedure followed to gather the data. The chapter concludes with the analytical techniques utilized for the data analysis Design of the thesis Repetitive machine breakdown and hence unwanted waiting time were increasing in East West Industrial Park Limited, an apparel manufacturing industry in Bangladesh. The causes of machine breakdown and its effect on product quality were then investigated to find out possible means of improvement by applying second and third pillars of TPM. All sections of the factory have been studied to identify and reduce equipment losses. First target was to identify which machine actually fall into breakdown on a regular basis and due to this breakdown which types of losses occur. Since there were different buyer with variety of order from them so all the products are not same according to their respective product design. They vary from style to style based on their fabric construction, fabric composition, some fabric is thick and some are thin based on their GSM. Also some products need more operation for completing the product. As a result maintenance personnel need to consider the style change and according to this they need to adjust the required machine. In swing section single needle lockstitch machine are more sensitive in the time of adjustment. And four vital parts were found that may break very easily due to the improper adjustment. These parts are Needle, Needle Plate, Feed Dog and Rotary Hook. On the other hand cutting section suffers from rapid decline of sharpness from cutting blade. 19

31 Data collection was continued as well as discussion was going on with maintenance personnel, they also talk similarly according to the findings of data collection. Usually in sewing floor Single Needle lock stitch machine are much more needed compare to other sewing machine for completing the layout; and cutting machines are much more vital for cutting section. Then vital few losses are identified using Pareto analysis. WWBLA technique was used to measure the causes & give possible solution as well as autonomous maintenance system were planned and implemented to reduce equipment breakdown and downtime Finally, Overall equipment efficiency (OEE) was calculated and compared the improvement percentage with the initial stage OEE. So the steps that were followed are as below: i. Identify the major losses that occur in sewing and cutting section ii. Collect data on loss time regarding the major losses iii. Identification of Vital few losses using Pareto analysis iv. Calculation of Overall Equipment Efficiency based on present condition v. WWBLA of the measured causes & give possible solution vi. vii. Collect data regarding more frequently needed spare parts & machine breakdown time from maintenance Root cause analysis for equipment breakdown viii. Make a plan & train up all operators for autonomous maintenance ix. OEE calculation at the final stage & compare with previous calculation 20

32 So the total activities can be categorized as following three stages in Figure 3.1 Figure 3.1: Thesis activity in Frame work Identification of losses and their Measurement: A production floor was selected randomly to consider as a pilot project where there was five production line comprising of total two hundred machines (Single needle lock stitch, Double needle chain stitch, Pocket welting machine, Edge cutter machine). To feed these five lines there was a fabric cutting section that includes four cutting machine with a cutting table. Product that produces in this floor named Waist Coat; whose SMV is 30 minutes. Based on this SMV and existing setup, Floor actual capacity (considering 100% efficiency) is 6000 pieces per day (11 Hour), where floor was producing only 3000 pieces i.e. another 3000 pieces productions were 21

33 losses due to various reasons that was considered as Non Productive Time (NPT).Three work study executive were fully responsible to collect all NPT during the working hour. For this purpose they used a pre generated NPT format and filled this format daily basis. For the accuracy of data collection they took support from individual SMV of product, Line existing efficiency percentage and daily output quantity. Any breakdown of machine and hence waiting time were signed by line supervisor and maintenance personal after the repair of machine breakdown. Actual defect quantity and due to this NPT were taken from end line quality table where a daily basis data sheets were maintained also. The details about six major losses (how they are classified and measured) are listed in below table 3.1: Down Time Loss: Table 3.1: Six Major Losses S/L Major losses Loss category Loss Details 1 Equipment Failure Causes production downtime Equal or More than 30 minutes All types of m/c, generator, boiler, compressor failure or break down when maximum m/c or whole process remain shut down 2 Set Up/ Adjustment Failure Until first end product comes out & the loss during this time is termed as setup or adjustment loss Time require more than minor stoppage, that means >10 minutes but below 30 minutes New layout, learning stage, initial sample making stage, New Lay spreading, warm up time, change over time, New guide, folder, pressure feet adjustment time etc Down time loss 22

34 Speed Loss: S/L Major losses Loss category Loss Details 3 4 Idling or minor stoppage failure Reduced speed loss Small stops less than 5-10 minutes Speed less than the optimum or required Minor adjustment in running condition, Needle break, Bobbin case change, m/c cleaning, false stitch removing time etc M/c wear or, operator in efficiency, Loss due to the uses of poor quality materials such as needle, thread etc Speed Loss Loss due To Defect: S/L Major losses Loss category Loss Details 5 Defect loss Loss due to rework or reject Any types of alteration at running production 6 Reduced yield Loss between m/c start to reach stable condition Any types of alteration at the initial stage of production. At the time of layout. Normally it takes 5 hours to start production at optimum speed Loss due to defect 23

35 3.2 Data Collection & Data Analysis: Data was accumulated on daily basis and summarized as monthly report. The monthly report was the basis of all analysis. One of the monthly reports is given below as a sample: Table 3.2: Monthly Data Collection Sheet 24

36 3.2.1 Monthly Loss Identification & Classification: In the first three month (Stage-1) six different losses are classified based on the monthly data sheet as per below inserted table a) Downtime Loss 1. Equipment Failure Month 1 Machine Table 3.3: Six major Losses in chart (1 st stage) No of machine Reason Frequency Loss (Pcs) Downtime (Hr) SNLS 13 Rotary Hook damage SNLS,DNLS 3 Motor Burn APW 1 Solinoid valve Damage Sub Total SNLS 6 Rotary Hook damage SNLS 3 Motor Burn APW 1 Solinoid valve Damage Sub Total SNLS 6 Rotary Hook damage SNLS 3 Motor Burn Sub Total Total Setup or Adjustment Failure Month Machine No of Loss Downtime Reason Frequency machine (Pcs) (Hr) SNLS 60 Fabric lay spreading SNLS 90 Embroidary Delay Sub Total SNLS 20 Fabric lay spreading SNLS 65 Embroidary Delay Sub Total SNLS 15 Fabric lay spreading SNLS 25 Embroidary Delay Sub Total Total

37 b) Speed Loss 3. Minor Stoppage or Idling Failure Month Machine No of machine Reason Frequency Loss (Pcs) Downtime (Hr) SNLS 275 Needle Broken SNLS 29 Bobbin Case damage SNLS 32 Needle Plate Damage SNLS 33 Bobbin Change SNLS,DNLS 17 Guide change Sub Total SNLS,DNLS 150 Needle Broken SNLS 14 SNLS 20 Bobbin Case damage Needle Plate Damage SNLS 25 Bobbin Change SNLS,DNLS 12 Guide change Sub Total SNLS,DNLS 70 Needle Broken SNLS 6 SNLS 16 Bobbin Case damage Needle Plate Damage SNLS 13 Bobbin Change SNLS,DNLS 10 Guide change Sub Total Total

38 4. Reduced Speed Loss Month Machine No of machine Reason Frequency Loss (Pcs) Downtime (Hr) Cutting m/c 5 Cutting Blade in Poor condition Cutting m/c 2 Cutting Blade damage SNLS 15 Cutting Delay Cutting m/c 5 Cutting m/c 5 Sub Total Cutting Blade in Poor condition Cutting Blade damage SNLS 16 Cutting Delay Sub Total Cutting m/c 3 Cutting Blade in Poor condition Cutting m/c 2 Cutting Blade damage SNLS 5 Cutting Delay Sub Total 80 8 Total

39 C) Loss Due to Defects 5. Defect Loss Month Machine No of machine Reason Frequency Loss (Pcs) Downtime (Hr) Cutting mc/snls 7+15 Yarn missing Cutting m/c 10 Fabric damage Sub Total Cutting mc/snls 7+13 Yarn missing Cutting m/c 8 Fabric damage Sub Total Cutting mc/snls 6+8 Yarn missing Cutting m/c 10 Fabric damage Sub Total Total Reduced Yield Loss Month Machine No of Loss Downtime Reason Frequency machine (Pcs) (Hr) SNLS,DNLS 7 Stitching Fault SNLS 7 Stitching Fault Sub Total SNLS,DNLS 7 Stitching Fault SNLS 6 Stitching Fault Sub Total SNLS,DNLS 7 Stitching Fault SNLS 5 Stitching Fault Sub Total Total

40 In Stage-2 six different losses are classified based on the monthly data sheet as per below inserted table a) Downtime Loss Table 3.4: Six major losses in chart (2 nd stage) 1.Equipment Failure Month 1 2 Machine No of machine Reason Frequency Loss (Pcs) Downtime (Hr) SNLS 10 Rotary Hook damage SNLS,DNL S 3 Motor Burn APW 1 Solinoid valve Damage Sub Total SNLS 7 Rotary Hook damage SNLS 1 Motor Burn APW 1 Solinoid valve Damage Sub Total SNLS 7 Rotary Hook damage APW 1 Solinoid valve Damage Sub Total 80 6 Total Setup or Adjustment Failure Month Machine No of Loss Downtime Reason Frequency machine (Pcs) (Hr) SNLS 30 Fabric lay spreading SNLS 45 Embroidary Delay Sub Total SNLS 15 Fabric lay spreading SNLS 15 Embroidary Delay Sub Total SNLS 15 Fabric lay spreading SNLS 25 Embroidary Delay Sub Total Total

41 b) Speed Loss 3. Minor Stoppage Failure Month Machine SNLS,DNL S No of machine Reason Frequency Loss (Pcs) Downtim e (Hr) 147 Needle Broken SNLS 13 Bobbin Case damage SNLS 15 Needle Plate Damage SNLS 13 Bobbin Change SNLS,DNL S 6 Guide change Sub Total SNLS,DNL S 90 Needle Broken SNLS 6 Bobbin Case damage SNLS 16 Needle Plate Damage SNLS 13 Bobbin Change SNLS,DNL S 10 Guide change Sub Total SNLS,DNL S 70 Needle Broken SNLS 6 Bobbin Case damage SNLS 16 Needle Plate Damage SNLS 13 Bobbin Change SNLS,DNL S 6 Guide change Sub Total Total

42 4. Reduced Speed Loss Month Machine Cutting m/c Cutting m/c Cutting m/c Cutting m/c Cutting m/c Cutting m/c No of machine 2 Reason Cutting Blade in Poor condition Frequency Loss (Pcs) Downtime (Hr) Cutting Blade damage Sub Total 60 5 Cutting Blade in Poor condition Cutting Blade damage Sub Total 60 5 Cutting Blade in Poor condition Cutting Blade damage Sub Total 70 6 Total C) Loss due to defects 5.Defect Loss Month Machine Cutting mc/snls No of machine Reason Frequenc y Loss (Pcs) Downtim e (Hr) 82 Yarn missing Sub Total SNLS 60 Yarn missing Cutting m/c 5 Fabric damage Sub Total Cutting mc/snls 60 Yarn missing Cutting m/c 5 Fabric damage Sub Total Total

43 6. Reduced Yield Loss Month 1 Machine No of machine DNLS 13 SNLS 10 Reason Stitching Fault Stitching Fault Frequency Loss (Pcs) Downtime (Hr) Sub Total DNLS 7 SNLS 6 Stitching Fault Stitching Fault Sub Total DNLS 7 SNLS 5 Stitching Fault Stitching Fault Sub Total Total

44 3.2.2 Calculation & comparison of OEE during first three month (1 st stage) OEE is calculated in every month & table 3.5 will explain average OEE status during stage-1 Table 3.5: Overall Equipment Efficiency (OEE) Calculation Month-1 Month-2 Month-3 Stage-1 A Total Production Pcs B Average Prod. Per day Pcs C Working time[11 Hr per day] Hour D Schedule Downtime Hour E Loading Time [c-d] Hour F G Down time due to equipment failure Down time due to setup/ Adjustment failure Hour Hour H Operating Time[e-f-g] Hour I Availability[h/e] J Actual Cycle time[(h+g+f)/a] Hr/pcs K Standard Cycle Time Hr/pcs L Operating Speed rate[k/j] M Net operating rate[(j*a)/h] N Performance Rate[l*m] O Defect Pcs P Reduced Yield Pcs Q Quality Rate[(a-o-p)/a] r Overall Equipment Efficiency (OEE) 59% 62% 69% 63% From the above calculation its showing 63% OEE; which are found after the first three months during data collection stage. Now next stage target is to improve the OEE percentage by identifying & eliminating the root causes with some possible solutions. 33

45 3.3 Problem Identification & Possible solution Stage-2: To identify & prioritize the significant losses Pareto Analysis is used. Along with WWBLA Tool is used to find out the root causes & eliminate the causes Pareto Analysis for significant losses Here Pareto Analysis is used to identify the most Significant losses. Table 3.6 will explain the details about major losses & based on it Pareto chart (Figure 2.1) is showing the most significant losses. Table 3.6: Production Losses in stage-1 Loss Category Production Pcs Cumulative Percentage Defect Loss % Minor Stoppage or idling failure % Reduced yield % Equipment Failure % Setup/Adjustment Failure % Reduced Speed Loss % Total 5541 Figure 3.2: Loss Pareto Chart 34

46 From the above chart it s showing that most significance losses are Defect loss that causes maximum losses in production. It s occurring 42% loss from total loss percentage. Then second significant loss is Minor stoppage that contributes 25% loss and the third loss percentage is 10% contribution which comes from Reduced Yield. These three losses are considered as most significant losses as these contribute almost 80% loss of total losses. So these are vital few losses that mainly affecting on OEE improvement Vital few causes Identification Using Pareto analysis main causes for significant losses are listed in below table 3.7. Table 3.7: Causes of production loss in Stage-1 Causes of production Losses Frequency Loss (Pcs) Cumulative percentage Yarn missing % Needle Broken % Stitching fault % Fabric damage % Embroidary Delay % Rotary Hook damage % Cutting Blade in Poor condition % Fabric lay spreading % Motor Burn % Bobbin Change % Cutting Blade damage % Needle Plate Damage % Cutting Delay % Solinoid valve Damage % Bobin case damage % Guide change % Total

47 Here is the Pareto chart presented in Figure 3.3 to explain the major causes. Figure 3.3: Cause Pareto Chart Cause Pareto chart shows us Yarn missing from fabric is the most significant causes for production losses while it s contribution is 35%. Then Needle broken, stitching fault, Fabric damage, embroidery delay & rotary hook damage are the causes that contributes another 45%, altogether 80%. So this 80% contribution comes from the mentioned five causes which will be the main target to work. In next part of this work target will be to eliminate these vital few causes by using WWBLA to improve the OEE percentage as well as to improve the AM ratio Analytical Technique to minimize the losses WWBLA is an analytical tool used systematically to identify root causes of production losses with a view to minimize them. WWBLA technique is a worksheet which identifies the root causes of a problem. In this technique, each major problem is considered separately and a worksheet is prepared. For each major problem, a cause is identified and called it first factor for problem. Then it is verified whether it can be divided into further root causes. If it is possible, then it is marked as G. Here, G stands for Go. Then a second factor for problem is identified and verified. In this way, a third, fourth problems are identified. If it is not possible to identify further, then verification is marked as NG (Stand for No Go). Finally, countermeasures are identified for each root causes of the problem [11]. We used WWBLA to eliminate the first three causes of the significant losses. They are Yarn missing, Stitching fault, Needle broken. 36

48 a) Yarn Missing from the product, 43% Size of problem: 1950 Pcs of Waist coat production loss in 1 st step (3 months) Mechanism: Polyester (PES) fabric is used as a raw material to make waist coat. Loss may occur from cutting section to sewing floor, mainly in cutting section for wrong spreading of lay, sharp edges of spreading table & cutting blade, along with wrong working method by the cutting operator. b) Stitching Fault during production, 12% Size of problem: 530 Pcs of Waist coat production loss in 1 st step (3 months) Mechanism: Single needle Lock stitch & chain stitch machine is used to complete the line layout for waist coat production. Machine abnormalities, operating skill with wrong working method from sewing operator may cause the production losses from the line. c) Needle broken during production, 9% Size of problem: 378 Pcs of Waist coat production loss in 1 st step (3 months) Mechanism: Required fabric gsm for waist coat is <300 gr/m2. So the recommended needle is round point sharp edge, size is 10. Inaccurate needle size with wrong adjustment in machine can bring the needle breakage. Also lack of awareness from machine operator can also bring the needle damage. The detailed analysis of first three causes of most significant losses was structured as WWBLA chart. Now it will be explained one after another, to understand how these causes were verified to get the root causes, along with all the countermeasures that were taken as a solution. All three WWBLA analyses are given below: 37

49 WHY WHY BECAUSE LOGICAL ANALYSIS 1 38

50 WHY WHY BECAUSE LOGICAL ANALYSIS 2 39

51 WHY WHY BECAUSE LOGICAL ANALYSIS 3 40

52 Summary of root causes: WWBLA technique helped to find out the root causes for the three significant losses. Here root causes are mentioned; at the same time some countermeasures were taken & the impact was observed up to the end of second stage. A. No work instruction to follow. B. Insufficient Pinches to use. C. No proper arrangement for training module to upgrade their skill level. D. No proper counselling for worker motivation. E. Lack of knowledge regarding autonomous maintenance. F. No signalling system for maintenance. G. No scheduled maintenance. H. Lack of proper lubrication. I. Poor design of workstation. J. Lack of communication between mechanic & machine operator. K. Rotary hook become damaged. L. Tension was not adjusted. M. Needle height was not adjusted & tested before operation. N. Needle was not mounted with right eye position. O. Operator speeding up machine too rapidly. P. Operator holding back or pulling fabric through in variance with correct machine feed. Q. Unavailability of cleaning material with checklist. 41

53 Summary of countermeasures taken & their impact: Before: There was no Work Instruction at Cutting section; After: WI implemented as below: 1. No work instruction to follow at cutting table during spreading of lay. Countermeasure: To avoid wrong cutting of the lay & to maintain beginning and end of the lay perpendicular to the selvedge required WI for Cutting section was implemented, as in Figure 3.4 Figure 3.4: Cutting section WI 42

54 To have a lay without tension, fold & irregularity, the table must be larger and longer than the lay. Also the table, sticker and the spreader need to be clean, well adjusted and not damaged. Below pictures are expressing the required work instruction during cutting. Figure 3.4: Cutting section WI To avoid to cut outside of the lay, and to respect the consumption, the marker has to be aligned with the lay, to avoid cutting outside of the usable width. 43

55 Also During spreading process, each layer must have to cut straight, neatly aligned one on top of each other, cut with the same length, and the beginning and end of the lay, must be perpendicular to the selvedge. Below work instruction is explaining the same. Figure 3.4: Cutting section WI Impact: Before implementation of WI cutting fault occurring chance was more which has reduced & became more work friendly for the operator after implementing WI. The result shows frequency of cutting fault has been reduced up to 10% 44

56 2. Insufficient Pinches to use during spreading of lay. Countermeasure: To respect the shape of the pattern pieces pinches are used with a heavy & flat tool to hold the paper during cutting. Before After Figure 3.5: Uses of Pinches during cutting Impact: Without pinch, paper marker can be displace from the fabric lay, which brings cutting fault. After implementing of pinches with heavy & flat tool; reduced the frequency cutting fault. 3. No proper arrangement for training module to upgrade operator skill level. Before: No arrangement for upskilling training; After: Weekly Training has been arranged for up skilling. Countermeasure: Up skilling program has been arranged & 70% cutting assistant promotes as cutting operator. Figure 3.6: Basic maintenance training & skill upgrading chart. 45

57 Impact: Number of cutting helper was reduced & they were promoted as operator after the up skilling program, as well as rate of cutting fault also reduced. 4. No proper counselling for worker motivation. Before: No system for proper counselling; After: Buddy system has been implemented Countermeasure: Buddy System has been placed for newly joined operator & to give them motivation. Figure 3.7: Buddy for new worker Impact: Before introduction of buddy system worker found dissatisfied with their work & performed more defective work, along with switch the factory within three months. Buddy system helped operator to find a better workplace to work & to plan for a long term career with proper motivation & better quality work. So this helps & motivates new worker to adapt with the new environment quickly and reduces worker migration. & develop worker skill in a good manner. 5. Lack of knowledge regarding autonomous maintenance. Countermeasure: Autonomous maintenance has been introduced, now worker can do their basic maintenance for his own machine. In figure 3.8, BM flow diagram has explained. Impact: Minor adjustment in running condition like (Needle installation after Needle breakage, Bobbin case change, Machine cleaning, Thread tension adjustment, SPI adjustment) that take normally 5 to 10 minutes was decided as basic maintenance and management also convinced to train the worker on basic maintenance and make them autonomous. 46

58 Figure 3.8: Basic Maintenance (BM) Flow Diagram Before Condition: Total number of machine=200 Daily average number of machine found for minor stoppage=15 After Autonomous maintenance program: Total number of machine=200 Daily average number of machine found for minor stoppage=8 Maintenance work percentage reduction from (15/200) =8% to (8/200) =4% Number of machine maintenance done by operator=7 Autonomous maintenance (AM) ratio improvement up to; (7/15) =47% 47

59 6. No signalling system for maintenance people Countermeasure: A maintenance signal system has been developed presented in figure 3.9 and implemented for the mechanic person in case of any emergency maintenance. Figure 3.9: Maintenance Signal Impact: Before implementing signalling system problem was not well communicated with the mechanic which increased the downtime. To decrease the down time & to repair the machine immediately three layers light has been installed in front of the line, as presented in figure 3.10 it gives solution of minor stoppage within five minutes previously which was up to 10 minutes. Before After Figure 3.10: Maintenance Signal with before after comparison 48

60 7. Unavailability of cleaning material with checklist. Countermeasure: Shining checklist has been implemented for each line (section wise) with different cleaning leader. All machines is provided cleaning material & machine is now cleaned daily before and after lunch (with a maintenance song). Impact: Stitching fault found due to machine abnormalities, poor performance from operator with faulty working method. On which faulty working method plays major rule to create defective product during lay out stage in apparel production floor. Maximum defective product was due to dirty spot on the product. After providing the cleaning materials with checklist in each machine, defective product due to dirty spot, reduced significantly. 8. Poor design of workstation. Countermeasure: Work station has been redesigned as below. First picture shows before redesigning of work station & second picture is the after condition 49

61 Figure 3.11: Redesign of workstation Impact: There was a small box to keep the semi finished product & no centre table for worker to pass the product after stitching. Also workers were used to right hand pick up and dispose the product by pulling under the pressure feet. Management is being convinced for centre table & worker is being trained for left hand disposal (without pulling) which has reduced the needle breakdown than the initial stage AM details: To implement AM all required activities are listed in below Figure 3.12 AM Training Cleaning time with jingle Maintenance Signal Line wise Tool Keeping Box for BM Figure 3.12: Autonomous maintenance Details 50

62 Tentative standard: Below chart shown in table 3.8 is a template about autonomous inspection, it s mainly to set a tentative standard which needs to perform by sewing operator daily. Table 3.8: Tentative standard for Autonomous maintenance 51

63 Autonomous Management: Monthly newsletter was published from the selected floor so that everyone can recognize the improvement; one of template is given in below Figure

64 Figure 3.13: Continuous Improvement newsletter 3.4 Result comparison and evaluation Stage At the end of stage-2 we checked the impact of WWBLA and compare the losses between the stage 1 and stage 2. AM ratio improvement and its impact on OEE improvement also compared 53