diagnosis using bayesian networks to enable value
Contents
1. On average approximately 4 9 of the companies turnover in 1991 was spent on maintenance which was similar in percentage as 10 years earlier It is interesting to note that from 1981 to 1991 there were increases in maintenance costs expressed as a percentage of capital value for the overall survey average 0 6 for production transport and storage equipment 0 9 and for spare parts 0 4 The average Danish company represented in the survey spent 32 of its maintenance budget on spare parts 32 on salary and wages and 31 on external services In the average company 23 8 of the maintenance costs were attributed to unforeseen repairs 28 7 to preventive maintenance and 45 5 to planned repairs Approximately 39 of the time spent on maintenance is used for unforeseen repairs 20 for preventive maintenance and 37 for planned repairs Planning and control of preventive maintenance is performed in 45 of the companies Use of the computer to control spare parts increased from 10 to 50 from 1981 to 1991 and 23 computer usage to control preventive maintenance increased from 9 to 60 in the corresponding period However 25 of the companies do not have any inventory control procedures in place for spare parts In Finland the benchmarking survey was based on responses from 80 companies which accounted for approximately 12 of the total Finnish revenues and approximately 14 of industrial employment On averag2. a failure happens shown as Equipment Failure A decision box poses a question whether to replace the tester equipment part with a subsequent need to document the failure This process step known as Document the Failure produces the data source used in this research Failure Report Permission to Proceed Data Copy Root Cause of Tag Tag amp Part Tag amp Part YES Figure 1 1 Universal Data Feedback Model Kindree et al 1994 p 67 This process of capturing the tester eguipment failure information analyzing failure information and providing feedback to fix the tester eguipment issues and improve the tester eguipment reliability and maintainability proposed by Kindree et al adeguately simulates a real world manufacturing process During a particular tester equipment operation a problem may occur unexpectedly which either will stop the process from running entirely or cause the process not to run per the expected performance specifications The operator of the machine running this process will then stop the machine and notify the technician to fix the problem The technician will attempt to diagnose the problem determine and execute the most appropriate troubleshooting steps to fix the problem Bloch H P 2001 p 74 cited the strategy of rational thinking referring to eguipment documentation and occasional recollection of the simpler laws of physics to result in f
3. 17 21 39 40 42 44 52 54 71 83 86 89 Page 38 39 1 1 1 2 1 3 1 4 1 5 1 6 LIST OF ABBREVIATION Page SPC Statistical Process Control 17 20 HTTP Hyper Text Transfer Protocol 16 17 LAN Local Area Network 16 17 Al Artificial Intelligence 32 AVI Automated Visual Inspection 33 MTTR Mean Time to Repair 51 LIST OF PUBLICATIONS amp SEMINARS Wan Muhamad W M Fadzil L M and Samsudin A 2000 The Application Of Statistical Methods Using Web Infrastructure To Enable World Class Manufacturing Processes RESQUA2000 Regional Symposium On Quality amp Automation Proceedings 1st 113 117 Wan Muhamad W M Subari K and Fadzil L M 2002 A Strategy Towards Global Competitiveness Internet Based Quality Assessment Conference On Quality Proceedings 77 vi DIAGNOSA MENGGUNAKAN KAEDAH BAYESIAN NETWORKS UNTUK MENGUPAYAKAN BAIKPULIH KE ATAS PERMASALAHAN PROSES PEMBUATAN ABSTRAK Di dalam proses perkilangan juruteknik selalunya melakukan pembaikpulihan mesin mesin pembuatan menggunakan piawaian Panduan Pembaikpulihan yang sedia ada Apabila mesin mesin pembuatan menjadi lebih canggih dan kerosakan mesin mesin yang berkaitan menjadi bertambah sukar untuk dianalisa dan diselesaikan pengalaman juruteknik menjadi bertambah penting bagi menggantikan piawaian Panduan Pembaikpulihan di dalam membaikpulih kegagalan dan kerosakan mesin mesin yang kompleks dan serious Penyelidikan ini bertujua
4. CHAPTER FIVE RESULTS AND DISCUSSION 5 0 Comparison 5 1 Results 5 2 Discussion CHAPTER SIX CONCLUSION AND RECOMMENDATIONS 6 0 Conclusion 6 1 Recommendations BIBLIOGRAPHY APPENDIX A LIST OF TABLES 2 1 Branches of Artificial Intelligence Jones 2003 2 2 Two of the Five Probability Tables Buntine 1996 p 196 Conditional Probabilities P K P1 P2 For All Possible Values 23 Scheiterer and Obradovic 2005 31 List of Selected Failure Modes with respective MTTR Downtime and Occurrence 32 Raw Equipment Downtime Data Source for BIN 9 Intel Corporation ca 2003 approx 18 lines 33 Raw Eguipment Downtime Data Source for BIN 18 Intel Corporation ca 2003 approx 14 lines 34 Raw Equipment Downtime Data Source for BIN 21 Intel i Corporation ca 2003 approx 31 lines 41 Sample Table for Standard Troubleshooting Steps With The f Degree Of Completion 4 2 Bin 18 Standard Troubleshooting Steps With Respective Degree Of Completion 4 3 Bin 9 Standard Troubleshooting Steps With Respective Degree Of Completion 71 72 72 80 81 90 91 91 96 99 100 102 108 Page 36 41 44 57 60 62 64 74 75 76 4 4 4 5 4 6 4 7 4 8 4 9 410 5 1 5 2 5 3 1 1 2 1 2 2 2 3 2 4 2 5 2 6 3 1 3 2 4 1 4 2 4 3 4 4 1 1 Bin 21 Standard Troubleshooting Steps With Respective Degree Of Completion Bin 18 Standard Troubleshooting Steps Occurrences And Present Percentage Bin 18 B
5. decision support tools to support equipment maintenance The second part is on academic treatment of maintenance terms i e Failure and Downtime including definitions equations and related concepts The third part is on the method to process the data namely Artificial Intelligence Techniques with definitions related concepts and review on available Al techniques with special focus on Bayesian Networks The fourth part is on Theoretical Considerations for Bayesian Networks with definitions concepts and applications This research paper deals with the effort to develop methods and algorithms for resolving equipment failures using Bayesian Networks model and validate them using standard industry metrics Emerging trends in computers and industry case studies and importance of structured data infrastructure for informed decision making in businesses are discussed leading to a review of two maintenance benchmarking studies necessary to provide an understanding of current maintenance issues in industry before proceeding to the next section Initially company information has been accumulated on paper in various forms i e paper ledgers logbooks balance sheets manuals directories data sheets records and other analog forms Goldsmith 2003 states one case study where advances in other American economic sectors in applying digital information and 13 communications technologies are not proliferated successfully to some industries D
6. the amount of information becomes quite large Buntine 1996 p 200 also agreed on the difficulties in determining the number of cases required for the sample which is referred to as Sample Complexity and the time or space required for optimizing the sample into the model which is referred to as Computational Complexity Buntine quoted the computational learning theory where there are roughly three distinct phases depending on the quantity of cases obtained for the sample namely the small sample the medium sample and the large sample phases Initially with a small sample Buntine used the term learning or absorption of information to correspond to one s biases or prior information With a large sample learning is close to the true model possible with high probability Since an error rate known as Bayes optimal error rate is inherent in all three different types of samples 10 this indicates that using a small sample is possible From literature Bayes optimal error rate is proven not to influence the validity of the sample data These files are in the form of spreadsheet that comprises a number of columns The listing contains the associated tester eguipment type and number the root cause of equipment failure equipment type and number secondary supporting equipment equipment downtime and up time dates and times It also contains Mean Time to Repair or MTTR in hours down time or D T in hours equipment failure mode
7. DIAGNOSIS USING BAYESIAN NETWORKS TO ENABLE VALUE ADDED TROUBLESHOOTING TO MANUFACTURING PROCESS PROBLEM LOKMAN MOHD FADZIL UNIVERSITI SAINS MALAYSIA 2007 DIAGNOSIS USING BAYESIAN NETWORKS TO ENABLE VALUE ADDED TROUBLESHOOTING TO MANUFACTURING PROCESS PROBLEM by LOKMAN MOHD FADZIL Thesis submitted in fulfillment of the requirements for the degree of Master of Science SEPTEMBER 2007 ACKNOWLEDGEMENTS All gratitude and praise be to Allah the Almighty who granted the author unlimited bounties and grace with which this work becomes a reality The author wishes to thank his beloved parents Haji Mohd Fadzil Haji Saidon amp Hajjah Sharifah Haji Noor for their encouragement care and prayers Love and special thanks to his lovely wife Nor Azimah Ismail daughters Siti Farah Siti Farhana Siti Farhah and Siti Farzana sons Anmad Farhan and Ahmad Faiz Syakirin for their patience sacrifice understanding and support especially when he needs them most and also to dedicate in memory of deceased daughter Siti Farhain The author also wishes to express his utmost gratitude to his supervisor Dr Zahurin Samad ex supervisors Dr Wan Mansor Wan Muhamad and Encik Jamaluddin Abdullah and Dr Azman Samsuddin for their continuous guidance ideas and support The author also feel indebted to lecturer Adam Baharum student assistants Nik Nor Hishamul Azma Azman Tengku Azeezoo Abdul Mannan Mansor and Armizal Azwan Alias
8. Universiti Sains Malaysia particularly USM Institute of Postgraduate Studies USM School of Mechanical Engineering USM technical support personnel Hishamuddin Endan and Mohd Ali Shahbana Mohd Raof fellow students Wan Azhar Wan Yusoff Mohd Nizam Ahmad Zakri Ghazali and Mohd Zulkarnain and those who are not able to be named here who have provided valuable assistance for completion of this thesis and research and made it possible for the author to complete his graduate studies TABLE OF CONTENTS ACKNOWLEDGEMENTS TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF SYMBOLS LIST OF ABBREVIATION LIST OF PUBLICATIONS amp SEMINARS ABSTRAK ABSTRACT CHAPTER ONE INTRODUCTION 1 0 Introduction 1 1 Problem Statement 12 Research Objectives 1 3 Scope and Limitation 1 4 Approach 15 Thesis Outline CHAPTER TWO LITERATURE REVIEW 2 0 Introduction 2 1 Failure and Downtime 2 2 Artificial Intelligence Techniques 2 3 Theoretical Considerations 2 4 Summary of Literature Review CHAPTER THREE THEORETICAL FRAMEWORK 3 0 Introduction 3 1 Data Collection Stage 3 2 Data Algorithm Stage CHAPTER FOUR DEVELOPMENT OF THE DIAGNOSIS SYSTEM Page vi vi vii o o a A N 13 27 32 37 45 47 49 57 4 0 Introduction 41 Data Processing Stage 4 1 1 Conversion to Standard Troubleshooting Steps 4 2 Data Analysis Stage 4 2 4 Troubleshooting Steps Mapping into Bayesian Networks Diagram 4 3 Summary
9. address issues in maintenance industry 11 Problem Statement Based on a brief introduction on maintenance benchmarking and case studies mentioned in Introduction the problem statement summarized as a need to aid current troubleshooting process using artificial intelligence technigues to generate more accurate decisions to solve a tester eguipment non productive downtime issues This research attempts to address an issue when using the troubleshooting guides to diagnose eguipment issues The guides are static information designed to fix specific failures and cannot be utilized to resolve failures different from those defined in the guides As different machines perform differently over time the ongoing troubleshooting information captured by the technicians might reveal certain patterns or trends that might be able to help troubleshoot future failures According to Bloch H P 2001 p 74 the causes of all process machinery failures without exception can be put into one or more of seven categories faulty design material defects fabrication or processing errors assembly or installation defects off design or unintended service conditions maintenance deficiencies whether procedural or due to neglect and improper operation Kindree et al 1994 p 66 provides a similar troubleshooting concept but the focus is more on the 5 phases of machine and equipment life cycle namely concept development design build and install operation and
10. agai Panduan yang praktikal untuk kegunaan juruteknik viii DIAGNOSIS USING BAYESIAN NETWORKS TO ENABLE VALUE ADDED TROUBLESHOOTING TO MANUFACTURING PROCESS PROBLEM ABSTRACT In current manufacturing process technicians normally perform eguipment troubleshooting using standard Troubleshooting Guides As eguipment gets more sophisticated and associated failures become more difficult to analyze and to solve experience becomes a better substitute than existing Troubleshooting Guides in troubleshooting complex failures This research explores the definition and application of an algorithm to translate historical maintenance repair data to generate seguence of standardized equipment troubleshooting steps The algorithm help determine each troubleshooting steps probability and sequence information to be processed by Netica a Bayesian Networks modeling software The software produces recommended sequence of troubleshooting steps based on the given information Comparison is made between common parameters i e Downtime MTTR and Percentage Effectiveness data with repair cases using existing Troubleshooting Guides Results show that Netica generated troubleshooting steps represent an MTTR improvement over existing Troubleshooting Guide steps of 12 67 for Bin 18 32 43 for Bin 9 34 93 for Bin 21 respectively Downtime improvement of 21 89 for Bin 18 39 10 for Bin 9 of 35 42 for Bin 21 respectively Effectiveness improvement of zero c
11. ailure identification and point to future failure avoidance In a factory where proper the tester equipment record keeping are maintained the technician will record down the machine information failure signature and the troubleshooting steps to fix the problem for future reference This research is only limited to Document the Failure process step where the tester equipment failure information is being captured and Data Analysis process step where the tester equipment failure information is being analyzed The process to define troubleshooting steps recommended to fix the tester equipment issues is similar to Corrective Action Determined amp Executed by Supplier to User Supplier process step However in this step the troubleshooting steps recommendations are provided to the tester equipment technician not to the User Supplier as described in the process step All the other process steps i e the tester Equipment Operation Equipment Failure Store in Files Paper or Magnetic Return Part With Tag to Part Manufacturer or Equipment Supplier Complete Universal Tag amp Attach to Part and Does the Part Require Replacement decision box are not included in this research In short the scope and limitations are clearly defined in this research 1 4 Approach This research approach is divided into several milestones The first step is to analyze current issues facing the tester equipment in manufacturi
12. chnicians Utilize downtime data embedded in the repair or maintenance data to compare troubleshooting steps generated from Netica software with existing Troubleshooting Guide currently in use to evaluate the effectiveness of this technique 1 3 Scope and Limitation The scope of this research is limited to the use of the data source derived from the content of a Web based tester eguipment downtime database accessible at http e db png intel com developed by Intel Corporation for ten production machines for the year 2003 The database is used to capture or document failures that occur during a particular tester equipment operation How a tester equipment fails and how the failures are captured can be explained per the generic high level Universal Data Feedback Model process defined by Kindree et al 1994 p 67 This process comprises a close loop system of various functions The first function is the data collection function where the tester equipment failure information is captured The second function is the analysis function where failure information is analyzed The third function is the feedback function where recommendations are provided to fix the tester equipment issues and improve the tester equipment reliability and maintainability In addition it also specifies how to handle failure in a typical tester equipment process as shown in Figure 1 1 While the tester equipment is in operation shown as Equipment Operation
13. e approximately 4 8 of the companies turnover in 1991 was spent on maintenance The Swedish maintenance survey was based on responses from 71 of 200 large and medium sized companies from varied industries such as chemical paper and pulp steel and metal works machine and transport equipment electromechanical and food The Swedish survey illustrates that despite discussions of decentralization of maintenance resources in the participating organizations the majority of maintenance resources used approximately 70 are centrally organized The companies in the survey identified the highest priorities for improvement as the maintenance skills of the production staff involvement of the production staff in maintenance work continuous use of key figures knowledge of maintenance throughout the organization and control of the effects of maintenance on production volume In addition the survey indicated that the companies with the fewest number of shifts or the shortest production time reported a greater need for improvement Norway received 194 responses to its maintenance benchmarking study approximately 60 of the respondents were from the food engineering and chemical industries Seventy percent 70 of the companies were small and medium sized enterprises SMEs About 56 of the companies had no clear maintenance and availability objectives Most of the companies had a centralized maintenance function 24
14. e already digitizing their way of doing business This is demonstrated by the fact that a typical Fortune 500 company keeps an average of 8 Gigabytes of digital information in 1970 and steadily increases to 27 000 Gigabytes in 1990 and expected to reach 400 000 Gigabytes in 2000 Foy 1996 p 23 However a lot of this information resides on standalone computers or workstations stored in a certain format understood by and benefit only a small number of staff This will make other people difficult to access and analyze the data At that time networked computers were too costly and complex and are only in the domain of very large companies which were financially able and willing to pay for its high cost This is the first wave of digital evolution where there is a surge in industry transition to digital environment As time changed and computer networks become more prevalent these standalone computers or workstations started to connect in form of networks and the 15 digital data are shared among employees around the office Pesko 1999 p 11 noted that by end of the millennium there are 50 million computers in the U S workplace and 12 3 million networks in operation providing broader access to information Within the companies the digital data traffic started to increase but still confines to the small periphery of the network topology it was being designed In reality what this means is that for example office computer networks ca
15. ecision making in the new millennium remains glued to paper the telephone and practitioners memories This includes paper records often unreadable paper prescriptions paper orders paper lab reports paper telephone message slips fax paper verifications and paper bills of guestionable accuracy Retrieving useful data from this compendium can be an intimidating effort Quite often due to the considerable amount of time spent searching for data that data holds less value when it is found for use As Foy 1996 p 24 summed it up the current model for information acquisition storage and access in today s corporations is hopelessly out of date This is the state of an early 1970s information environment With the advancement of computer technologies available at a much lower cost the availability of inexpensive yet powerful computer hardware and software reduces the costs of setting up new types of businesses for example e business and expands the possibilities for setting up electronic portals or Web sites to conduct business Brynjolfsson and Kahin 2000 Companies have started engaging on new business models on digital platform over traditional channels Example companies include VeriSign and GTE CyberTrust that have recently emerged as Certification Authorities CAs or third party companies to provide software authentication services These companies issue digital certificates based on technological mechanisms such as the public ke
16. elief Report Generated From Netica Software Bin 9 Standard Troubleshooting Steps Occurrences And Present Percentage Bin 9 Belief Report Generated From Netica Software Bin 21 Standard Troubleshooting Steps Occurrences And Present Percentage Bin 21 Belief Report Generated From Netica Software Comparison Table for Netica generated Bin 18 Troubleshooting Steps vs Existing Troubleshooting Guide Comparison Table for Netica generated Bin 9 Troubleshooting Steps vs Existing Troubleshooting Guide Comparison Table for Netica generated Bin 21 Troubleshooting Steps vs Existing Troubleshooting Guide LIST OF FIGURES Universal Data Feedback Model Kindree et al 1994 p 67 A Sample Token Ring Local Area Network LAN Bentlage et al 2001 p 216 Block Diagram of Decision Flow Simple Bayesian model Another Simple Bayesian model Buntine 1996 p 196 Bayesian Multiple Fault Model Cause To Effect Model Of Simple Domain With Two Problems And A Single Common Symptom Scheiterer and Obradovic 2005 A Typical product lifecycle phases for semiconductor manufacturing Geng 2005 p 301 Sample Test Program Flow for Bin 9 Bin 18 and Bin 21 Intel Test Methodology Handbook 2002 p 101 Summary Flow Chart of the Research Methodology Bin 18 Netica Bayesian Networks Diagram Bin 9 Netica Bayesian Networks Diagram Bin 21 Netica Bayesian Networks Diagram LIST OF SYMBOLS 77 80 83 86 87 88 90 93 94 95 Page
17. ess 1996 p 8 Most network configurations already employed in companies in either LAN Local Area Network as shown in Figure 2 1 or dial up computer connected to the Internet have started using 16 World Wide Web as a method to disseminate information This typifies the third wave of digital evolution where digital communication is used for serious business purposes Online Spreadsheet Online SPC p aj Online Data Collection SCADA Systems Engineering Workstation Database Servers Figure 2 1 A Sample Token Ring Local Area Network LAN Bentlage et al 2001 p 216 For the next phase the fourth wave of digital evolution envisions all types of electrical or electronic appliances and eguipments available in offices or homes to be connected to the network using the familiar HTTP Protocol Information can be shared easily guickly and understood by common people to make decisions The intimate connection of a computer with the information infrastructure creates the demand for an appliance that can provide specialized access to information hence the name information appliance The real value of an information appliance is the ability to connect to the global repository of information the Internet and the World Wide Web Want and Borriello 2000 p 24 The Internet enabled manufacturing is one breakthrough concept in an attempt to get the manufacturing eguipment and machines in the factories c
18. essible in a timely fashion to decision making people in the company so that the most optimized decisions can be made in the best interest of the 20 company to produce better products and services In essence effective data flow is essential for companies to be successful Moreover Werner and Hermansson 2002 p 131 pointed out the necessary information exists within the company but is too fragmented and complex for a human mind to make efficient conclusions upon Getting the raw data is one thing applying them appropriately to get the job done is another and these issues pose challenges in formulating intelligent business decision making The diagram shown in Figure 2 2 can represent this decision flow The flow starts with Data Collection Process where data coming from a specific monitored process is being collected The flow continues with Data Analysis Process where the collected data is processed and analyzed for patterns or trends The analyzed data is then used as a base for making decisions Foy 1996 p 25 noted an example for an accountant to accomplish a particular audit recommendation a person may need to extract company financial data from which he may construct statistical analysis followed by an executive summary for him or others to make appropriate decisions In this example extracting company financial data constitutes the Data Collection Process constructing statistical analysis comprises the Data Analysis Pr
19. hange for Bin 18 of 26 67 for Bin 9 of 28 24 for Bin 21 respectively over the troubleshooting steps using existing Troubleshooting Guide In summary an improving trend seen across these parameters seen across the failure subgroups shows potential for usage as practical troubleshooting steps for use by maintenance technicians CHAPTER 1 INTRODUCTION 1 0 Introduction In Introduction a brief discussion touches on key motivating factors for this research on developing methods and algorithms for resolving eguipment failures using Bayesian Networks model To begin with there are rising trends in industries which demonstrate the importance of making informed decision making by having highly structured data infrastructure and the method to process and utilize the data in the data repository This transition to structured data infrastructure begins with the transformation of corporate information from paper in its various forms into digital format The new digital platform enables companies to start engaging promising business models over traditional ones Schneier 1994 Significant enhancements in technology have profoundly changed virtually every type of business and the way people do business In other words improvement in computers and communication technologies brings up new businesses opportunities Brynjolfsson and Kahin 2000 By installing sophisticated communications and technology systems to provide value added businesses informa
20. is point to understand current issues in maintenance industry Luxhoj et al 1997 p 437 and Tu and Yeung 1997 p 453 reviewed two major maintenance benchmarking studies from Scandinavia and the United States In February 1992 a EUREKA European Benchmark Study on Maintenance 1993 project was initiated that attempted to benchmark maintenance in Scandinavian countries i e Denmark Norway Sweden and Finland The purpose of the benchmarking study was to establish a trade by trade overview of maintenance methods to assist companies in identifying current issues and general maintenance trends for improving maintenance 22 Actual interpretation of the study s results among countries will largely depends on dynamic factors such as varying age and quality of machinery and buildings interpretation or use of maintenance concepts varying environmental conditions differing forms of production operations due to number of shifts and production technology Luxhoj et al cited that the benchmarking study beginning with Denmark was based on an analysis of questionnaire responses from 43 industrial companies The companies accounted for approximately 12 of the total revenues in Danish industry and approximately 8 of industrial employment The industrial sectors of chemical and petroleum nonmetallic mineral products and manufacturers of food beverages and tobacco accounted for approximately 64 of the industry sector turnover in the sample
21. mpetitiveness technology and cost are key factors to today s companies Miltenburg 2005 cited a case study on Rolls Royce which used to be the most advanced engineering company in the world but eventually lost its cost and technology leadership Companies realize the need to promote data exchange for efficient decision making to drive down cost and introduce new technologies In turn effective data flow across their supply chains will ensure that business information communicated effectively and timely to the correct audience Organizations without well defined data infrastructure Werner and Hermansson 2002 p 131 will find it difficult to maintain and control their own processes resources and inventory in rapidly changing technology industries As Bentlage et al 2001 p 215 stated t is not possible to share data between processes customers and suppliers merge data for analysis and scrutinize the data for improvements The process to enable making informed decisions starts with Data Collection Process where data originating from a certain process is collected The flow continues with Data Analysis Process where the collected data is processed and analyzed for patterns or trends The analyzed data is used as a base for making decisions under Decision making Process as demonstrated by Foy 1996 p 25 Making good decisions is a necessity in maintenance business as well to enable better troubleshooting decisions and higher perf
22. n almost every leading company in almost every industry with the new models producing cost advantages of 10 to 20 for the innovators For the computer industry Compaq reinvented the business model to the dismay of IBM Then Dell reinvented the model again to the dismay of Compaq For the air carriers business Southwest Airlines reinvented the business model to the dismay of American Airlines For steelmakers Nucor reinvented the business model to the dismay of U S Steel To maintain competitiveness technology and cost are key factors to today s companies 18 This is further demonstrated by a case study by Miltenburg 2005 Rolls Royce used to be the most famous engineering company in the world but eventually lost due to cost and technology The company is known to the public as a producer of luxury automobiles It promoted its aircraft engines products against established companies such as Pratt and Whitney and General Electric to win a major order from Lockheed in 1968 After some time Rolls Royce began to realize that it lacked the capabilities reguired for the project The new engine incorporated new unproven technologies which was difficult for Rolls Royce because the company was a technology follower not a leader Unanticipated problems and delays eventually caused development costs originally estimated at 65 million doubled to 135 million by early 1970 It nearly doubled again to 220 million in 1971 In 1971 Rolls R
23. n mendefinisi dan mengaplikasikan satu kaedah algorithma untuk menterjemahkan data pembaikpulihan mesin mesin pembuatan kepada rantaian langkah langkah pembaikpulihan yang piawai Algorithma ini membantu menentukan setiap langkah langkah pembaikpulihan yang dihasilkan mempunyai maklumat kebarangkalian dan rantaian untuk diproses oleh Netica satu perisian Bayesian Networks Perisian ini akan memberikan cadangan rantaian langkah langkah pembaikpulihan berdasarkan maklumat yang diberikan Perbandingan dibuat di antara parameter yang umum seperti Waktu Rosak Downtime Purata Waktu Untuk Baiki MTTR dan Peratusan Kekesanan Percentage Effectiveness dengan kes kes pembaikpulihan yang terdahulu yang menggunakan piawaian Panduan Pembaikpulihan yang sedia ada untuk meninjau keberkesanan teknik tersebut Keputusan menunjukkan piawaian Panduan Pembaikpulihan yang dihasilkan oleh Netica memberikan peningkatan dari segi Purata Waktu Untuk Baiki sebanyak 12 67 untuk Bin 18 32 4396 untuk Bin 9 34 9396 untuk Bin 21 peningkatan dari segi Waktu Rosak sebanyak 21 8996 untuk Bin 18 39 1096 untuk Bin 9 35 4296 untuk Bin 21 peningkatan dari segi Peratusan Kekesanan tidak berubah untuk Bin 18 26 67 untuk Bin 9 28 24 untuk Bin 21 berbanding dengan piawaian Panduan Pembaikpulihan yang sedia ada Satu trend turutan yang dilihat meningkat di vii kalangan parameter parameter tersebut menunjukkan potensi cadangan rantaian langkah langkah pembaikpulihan seb
24. ng processes This is accomplished by reviewing the current literature on the topic Whitney 2004 noted that all current maintenance issues apply to any one of three major approaches concerning eguipment strategic technical and economic The strategic issues focus on choice of method of accomplishing the manufacturing manual robotic and so on plus part presentation flexibility inspection and throughput The technical problems involve detailed technology choice and assurance of proper performance mainly achieved via an error analysis Economic analysis is concerned with choosing a good combination of alternative methods of achieving assembly and controlling error The focus of this research work will be more on technical standpoint as selection of techniques is a matter of technology choice Proper performance will be monitored by a set of pre defined metrics to be explained in Chapter 4 As current issues are understood the second step is to determine the focus of research work to be undertaken to address one of the issues selected for study Once the research focus has been determined the third step is to understand other researches done in this field of study and comprehend how those researchers address the issues At this point a research is proposed that tackles a different aspect of the issue or propose improvements on existing research The fourth step is to make use of existing data collected on target tester equi
25. nnot speak the language used by the computer networks in the manufacturing floor and vice versa Hence these networks are like islands of automation with little or no connection between processes Bentlage et al 2001 p 215 This is the second wave of digital evolution where those seemingly separate digital environments start communicating to each other With the explosion of Internet in 1994 many companies organization governments as well as individuals have started to tap into the power of Internet with the idea that this novel communication medium has the potential to spread the information quickly and in a standardized fashion The open structure of the Internet now allows small firms to conduct businesses previously available only to a select few who had access to EDI Electronic Data Interchange which is the exchange of electronic business documents between two or more businesses With the advent of Internet or World Wide Web publishing information becomes easier with increasing use of HTTP or Hyper Text Transfer Protocol one of the most popular protocols More than 100 million Internet users surf the Web around the world with 27 5 million people exchanging e mail messages every day Pesko 1999 p 11 The efficient distribution of content any information that enabled to be communicated electronically made possible by virtually removing all physical barriers of content distribution promising bright future on the Web Mccandl
26. ocess whereas summarizing the findings to make appropriate decisions falls under Decision making Process Figure 2 2 Block Diagram of Decision Flow 21 Going down to second level detail one important piece of data to a company is in depth eguipment troubleshooting information which can be in the form of paper based file ledgers or records or an eguivalent electronic database used by technicians in Intel Corporation for this research to fix eguipment problems This repository or database of eguipment troubleshooting information taps on the expertise of experienced people acguired over the years on top of generic eguipment training This type of information enables experienced people to make good troubleshooting decisions As for inexperienced people for unfamiliar tasks they will tend to perform trial and error judgment before arriving at the correct decisions unless working under supervision of experienced people When experienced people move out or transition to different positions or in the event that their skills decay after periods of skill disuse Hall et al 1998 p 184 this valuable information goes with them This is considered a loss to the company Luxhoj et al 1997 p 437 stated that the changing needs of modern manufacturing necessitate a reexamination of the role that improved maintenance management plays in achieving key cost and service advantages and maintenance improvements to the organization From th
27. onnected to a company wide network and have the key production parameters and controls hardwired to the central infrastructure The fourth wave indicates ubiguitous computing or any time and any place computing 17 Today a single multinational company can have a multitude of factories and offices spreading across continents These factories usually deploy numerous manufacturing equipments producing a variety of products in various stages of production With the increase in the number of factories spread in various geographical regions the numbers of machines used for production without doubt will increase This phenomenon poses new challenges to businesses As Michael and Thomas 2006 noted the challenges faced are capacity allocation strongly influences supply chain performance and profitability As with so many other supply chain considerations it is a balancing act for manufacturers with multiple locations Allocating too little capacity to a facility creates inability to meet demand and loss of sales Saddling a facility with having to carry too much capacity results in low utilization rates and higher supply chain costs Other challenges include low cost and technology advantage which are important criteria that enable successful companies to compete with and force other companies out of the market Masatsugu 2000 p 178 Slywotzky 1999 p 94 reiterated that new challengers using new business models have risen to take o
28. orming eguipment Luxhoj et al 1997 p 437 pointed out that changing manufacturing reguirements today makes it imperative for maintenance management to contribute to cost and service improvements to the organization With this in mind Luxhoj et al 1997 p 437 and Tu and Yeung 1997 p 453 reviewed two major maintenance benchmarking studies to understand current issues in maintenance industry The purpose of the Scandinavian and US benchmarking studies was to identify issues and general maintenance trends for improving maintenance The survey indicates that industrial firms maintenance costs have increased with Scandinavian firms at 0 5 per year and US firms 10 15 Wireman 1990 noted that the total waste in excessive maintenance expenditures was approximately 200 billion dollars in 1990 which equaled the total maintenance costs in 1979 Wireman 1990 concluded that the survey results illustrate the need for better maintenance planning and the need for more maintenance research and development One of the key needs identified in the studies includes the move toward computer based maintenance systems as the result of emerging developments and advances in maintenance technology information and decision technology and maintenance methods This requires development of expert systems or decision support tools as advocated by Werner and Hermansson 2002 p 131 to support equipment maintenance that will be key driving forces to
29. oyce fell into bankruptcy showing technology and cost is important for maintaining companies viability How these companies can overcome these challenges Foy 1996 p 23 stated The value of a corporation becomes its ability to generate and to effectively communicate needed knowledge throughout the system of suppliers customers employees and communities to which it operates Key learning for companies to take into consideration is facilitating data exchange for efficient decision making to drive cost and technology Corporations should practice effective data flow across their supply chains to ensure that business information is communicated effectively and timely to the correct audience Changes are happening in the industry at a very rapid pace especially for technology companies Without strong data infrastructure organizations are unable to effectively and timely maintain control their own processes resources and inventory In time it renders those organizations to become less and less competitive lose market 19 share and eventually driven out of the marketplace As remarked by Werner and Hermansson 2002 p 130 companies have to utilize all their resources including information and technology and refine and combine them to show patterns and support conclusions that could be used to provide better service to the customers gain market share and increase profit by reducing cost How a well defined data infrastructu
30. pment in the manufacturing process The process of selecting a technique to define an algorithm to process the collected data and to subject to a model to predict systematic troubleshooting guides is considered This output of predicted troubleshooting steps is compared to the existing manual troubleshooting guide using pre defined criteria to determine the effectiveness of the technique The pre defined criteria for comparison will indicate whether the so called the Bayesian Networks models is better at predicting appropriate troubleshooting steps than existing manual troubleshooting guide to solve a particular tester eguipment problem The data source derived from the content of a Web based tester eguipment downtime database is extracted into Microsoft Excel based files All the tester equipment failure information is captured per the Document the Failure process step in Section 1 3 in these files The decision to limit to a number of so called failure data bins for particular tester equipment is due to several factors to be explained further in Chapter 3 Commenting on this Liu and Desmarais 1997 p 991 agreed that constructing a valid knowledge representation is a time consuming task and there are issues on insufficient empirical or meaningful data and or the complexity involved in the network induction in real life applications Jager and Bertsche 2004 p 91 also cautioned that the accumulated information might be very imprecise If
31. r decision making in manufacturing process improvement Chapter 2 focuses on Literature Review with an academic treatment and definition of the ideas terminology and equations for Failure and Downtime Artificial Intelligence Techniques and Theoretical Considerations for Bayesian Networks used in this research Chapter 3 describes the Theoretical Framework or the definition on the algorithms and the data manipulation steps necessary to process the raw data for the proposed system Chapter 4 deals with the Development of the Diagnosis System on how this research is pursued together with the assumptions processing and transforming the data in the model for analysis Chapter 5 discusses on Comparison and Results where tabulated data is compared and interpreted and wraps up with Discussion where analysis made on the data is being discussed In Chapter 6 a Conclusion is made to support the objectives of this research and Recommendation for future proposal is included to provide future directions for this research 12 CHAPTER 2 LITERATURE REVIEW 2 0 Introduction Literature review is divided into four sections in this chapter The first part is on introducing rising trends in industries on making informed decision making by having highly structured data infrastructure and the method to process the data It also includes results of maintenance benchmarking studies that identify the maintenance industry need for development of expert systems or
32. re can improve cost Bentlage et al 2001 p 215 observed that many different processes in companies were islands of automation and being controlled or monitored using unrelated and incompatible tools It was not possible to share data between processes merge data for statistical analyses and gain access to the data from an individual process Many processes have no controls in place and those using paper based SPC or Statistical Process Control charts for example makes acquiring data for further analysis difficult These were regarded as limitations to an effective defect and yield detractors analysis and development of solutions Without the right data collection methodology or accessibility to the required data engineers were constrained in their efforts to improve their processes Bentlage et al 2001 p 215 With this in perspective without well thought data mechanisms in place any changes desired to the manufacturing process either to reduce cost or to simplify the manufacturing process or to shorten the throughput time are too tedious and time consuming to make them happen How to optimize the use of data infrastructure According to Mena et al 2002 p 225 in order for an organization to be competitive it has to deliver value to customers by offering better products and services at reduced costs to be profitable and gain market share To this end the organization needs to organize its data in such a way so that it is easily acc
33. support and conversion and or decommission where upfront engineering diagnosis and continuous improvement done in each of the process For this research the tester equipment non productive downtime issues defined under the problem statement mostly focus on material defects with some issues on assembly or installation defects 1 2 Research Objectives The main objective of this research is to develop a technigue to diagnose or troubleshoot non productive downtime issues for tester eguipment used in a manufacturing process to enable value added troubleshooting by using Bayesian Networks As reflected by the Problem Statement in Section 1 1 the benchmarking studies identifies an established need based on increasing maintenance costs high unforeseen maintenance and high ratio of lost production due to maintenance cost for Scandinavian and United States organizations Luxhoj et al 1997 p 437 The benchmarking studies clearly recommended using artificial intelligence techniques to generate decisions that are more accurate In doing so troubleshooting process can be improved and made more effective in solving tester equipment non productive downtime issues To achieve the main objectives of this research the detailed research objective are defined as follows Develop a model using Bayesian Networks technique by using existing real world repair or maintenance data to produce practical troubleshooting steps for use by maintenance te
34. the employee number of the technician who attended to the problematic equipment technician work shift hours and comments or troubleshooting steps taken by the technician to fix the problem From these files the Failure Mode column column M is filtered to reflect a list of output binning called Bin 9 Bin 18 and Bin 21 to be explained in Chapter 3 They will be used to be taken as sample of the equipment failure mode that contribute to the downtime are taken for further analysis to determine the standard troubleshooting steps taken to resolve the problem A Theoretical Framework for the algorithm to process the data for the model will be defined Once a systematic troubleshooting has been determined this data is plugged into the Norsys Software Corp Netica Bayesian Networks software that will recommend the most effective troubleshooting set of steps to rectify the problem based on evidence using Bayesian Networks algorithm The troubleshooting set of steps derived from the Bayesian Networks model will be compared against the existing troubleshooting steps found in the guides 11 1 5 Thesis Outline This thesis is organized into six main chapters Chapter 1 starts with Introduction that briefly explains the challenges faced by companies doing business on a global level especially on technology and cost and results of maintenance benchmarking studies that advocates effective manufacturing equipment management and usage of data fo
35. tion a company increases its ability to make better and more informed business decisions As time changed and computer networks become widely used standalone computers or workstations started to connect in form of networks and the digital data inside those computers shared among employees in the enterprise Eventually the digital data traffic started to increase not just within the confines of the company but also outside the company to its customers and suppliers through the Internet or World Wide Web as a method to disseminate information Due to increasing connectivity between computers and the information infrastructure previously untapped information for businesses now becomes readily available Pesko 1999 p 11 As this information is critical to get job done and to enable businesses to seize new opportunities it creates demand for appliances with specialized access to information hence the name information appliance Want and Borriello 2000 p 24 This poses new challenges and opportunities to businesses These challenges include low cost and technology advantage that are important to enable companies to successfully compete with and force other players out of the market Masatsugu 2000 p 178 Slywotzky 1999 p 94 noted that computer industry is an excellent example where companies i e Compag reinvented new models to achieve cost and technology leadership to drive giants i e IBM out of PC markets To maintain co
36. y cryptography equivalent to software key to access secure Web sites and databases Schneier 1994 Another company Red Hat functions as a digital intermediary company or middle man company which adds value by testing and assembling customized software components for consumers Brynjolfsson and Kahin 2000 In short improvement in computer technologies enables new businesses opportunities 14 Slywotzky 1999 p 94 commented that some companies suffered through hard ways i e missing profitability projections or losing out market share to competition etc before taking the digital transition Intel for example decided to invest 300 million to digitize its product development process in computer aided design and computer aided manufacturing CAD CAM following a 203 million loss in 1986 That is a key investment as becoming digital in the design and production of chips improves competitive performance Slywotzky also cited Wal Mart making similar investments digitizing its logistics system at about the same time By installing sophisticated communications and technology systems to provide real time sales and ordering information the company moved from atoms to bits As a result Wal Mart outperformed its competitors by offering the right products at the right stores by cutting costs by integrating its operations with its suppliers and by capturing valuable information about its customers Twenty years ago Wal Mart and Intel wer
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