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Glossary of terms • Recovery: see Fault Recovery. • Repair time: the time between the moment of failure and the moment the system is recovered. • Remote Monitoring: the extraction of system parameters (log data) from systems all over the world to a central database. • Robustness: dependability with respect to external faults, which characterizes a system reaction to a specific class of faults [4]. • Runtime Costs: a criterion of diagnostic performance that is used in this thesis, namely all the costs that the company makes to keep the diagnostic process up and running. • Service: in this thesis service refers to diagnosing and repairing of a system. • Service Delivery: correct functioning of the system (no failures occurred), in which it performs its intended function. • Service Engineer: the person that diagnoses and repairs systems. In this thesis the term refers to employees of PMS that diagnose and repair Philips Cardio-Vascular X-Ray Systems. • Service Innovation: a department of PMS - C/V that is responsible to provide service engineers with information that is necessary for diagnosing Philips Cardio-Vascular X-Ray Systems. • Service Specialist: a person that is specialized in the service of a system. In this thesis the term refers to employees of PMS that diagnose and repair the most rare failures of the Philips Cardio-Vascular X-Ray System. • ServiceWAX: current name of the project with as goal to develop the remote monitoring tools. • Speed of diagnoses: a criterion of diagnostic performance that is used in this thesis, namely the time between the moment that a failure occurs and the moment that the root cause of that failure is identified. • SPR: a FRU of the Philips C/V System that contains the MBU and the PEU. • Stand: the mechanical body that has the collimator and flat detector on its far ends. It can be positioned relative to the patient in order to transmit x-ray through the patient. • Strong model: description of the system that defines all modes of operation. • Structure: what enables the system to generate the behavior [4]. • Subsystem: a subset of interrelated components. • Supervisory Controller: entity that uses a diagnosis to recover the system (e.g., replace a component, clean rotating parts, invoke redundant component, etc.). • Symptom: see error. • Symptom-Cause-and-Solution sheets: documents used for fault diagnosis at PMS; quick lookup sheets, each containing symptoms, and their corresponding cause and solution. 82
Glossary of terms • System: an entity that interacts with other entities, i.e., other systems, including hardware, software, humans, and the physical world with its natural phenomena [4]. • System data: all unprocessed digital data that the target system produces. • Target System: a system that is subject to fault diagnosis. • TBCB: a FRU that is used in the power supply example; it needs voltage. • Technical Drawing: drawings that define the structure of the Philips C/V X-Ray System at various levels of detail (e.g., of cable- and FRU-connections). • Troubleshooter: a person that diagnoses and repairs systems (e.g., a service engineer). • Weak model: a model that only defines the nominal behavior of the system, and does not state anything about false modes of operation. • White Box: a model that describes the internally non-observable behavior as well as externally observable behavior. The behavior of the whole system is defined by the structure and the behavior of internal components. • X-ray: a form of ionising radiation used to image some internal structures of the body. 83
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Automated Fault Diagnosis at Philip
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© 2006 W.M. Lindhoud. Document gen
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Preface The work presented in this
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CONTENTS 4.4 Modeling . . . . . . .
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List of Tables 3.1 Evaluation appro
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1.1 Fault Diagnosis Introduction Fi
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1.2 Automated Fault Diagnosis Intro
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1.5 Outline of the Thesis Introduct
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Chapter 2 State-of-the-Practice Fau
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State-of-the-Practice Fault diagnos
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Chapter 3 Automated Fault Diagnosis
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Automated Fault Diagnosis 3.1 Overv
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Automated Fault Diagnosis 3.3 Off-l
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Automated Fault Diagnosis 3.5 Model
Page 45: Automated Fault Diagnosis 3.6 Evalu
Page 48 and 49: 4.1 Fundamentals Model-Based Fault
Page 50 and 51: 4.2 Model-Based Diagnosis with LYDI
Page 52 and 53: 4.3 Basic Assumptions Model-Based F
Page 54 and 55: 4.4 Modeling Model-Based Fault Diag
Page 56 and 57: 4.4 Modeling Model-Based Fault Diag
Page 58 and 59: 4.5 Entropy Gain Model-Based Fault
Page 60 and 61: 4.6 MBD on the Power Supply Model-B
Page 63 and 64: Chapter 5 Diagnosing the Beam Prope
Page 65 and 66: Diagnosing the Beam Propeller Movem
Page 83 and 84: Chapter 6 Conclusions and Recommend
Page 85: Conclusions and Recommendations 6.2
Page 88 and 89: BIBLIOGRAPHY [12] Johan de Kleer an
Page 91 and 92: Appendix A Glossary of terms In thi
Page 93 and 94: Glossary of terms • Diagnostic Pe
Page 95: Glossary of terms • Model: an abs
Page 100 and 101: B.2 System Data Case Study Details
Page 102 and 103: B.4 Full List of Examined Fault Sce
Page 104 and 105: B.5 Discretization of Implementatio
Page 106 and 107: C.1 The Synthetic Models that are U
Page 108 and 109: C.2 Model of the Power Supply Examp
Page 114 and 115: C.3 The Models Constructed for the
Page 131 and 132: Appendix D State-of-the-Future Faul
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