Advanced Process Monitoring for Industry 4.0

This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and “extreme data” conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes

Micro-manufactured Rogowski coils for fault detection of aircraft electrical wiring and interconnection systems (EWIS)

Aircraft wiring failures have increased over the last few years resulting in arc faults and high-energy flashover on the wiring bundle, which can propagate down through aircraft Electrical Wiring and Interconnect Systems (EWIS). It is considered cost prohibitive to completely rewire a plane in terms of man hours and operational time lost to do this, and most faults are only detectable whilst the aircraft is in flight. Temperature, humidity and vibration all accelerate ageing and failure effects on EWIS. This research investigates methods of in-situ non-invasive testing of aircraft wiring during fight. Failure Mode Effects and Analysis (FMEA) was performed on legacy aircraft EWIS using data obtained from RAF Brize Norton. Micro-Electro-mechanical- Systems (MEMS) were evaluated for use in a wire monitoring system that measures the environmental parameters responsible for ageing and failure of EWIS. Such MEMS can be developed into a Health and Usage Monitoring MicroSystem (HUMMS) by incorporating advanced signal processing and prognostic software. Current and humidity sensors were chosen for further investigation in this thesis. These sensors can be positioned inside and outside cable connectors of EWIS so that arc faults can be reliably detected and located. This thesis presents the design, manufacture and test of micro-manufactured Rogowski sensors. The manufactured sensors were benchmarked against commercial high frequency current transformers (HFCT), as these devices can also detect high frequency current signature due to wire insulation failure. Results indicate that these sensors possess superior voltage output compared to the HFCT. The design, manufacture and test of a polymer capacitive humidity sensor is also presented. Two different types of polymer were reviewed as part of the evaluation. A feature of the sensor design is recovery from exposure to chemicals found on wiring bundles. Current and humidity sensors were demonstrated to be suitable for integrating onto a common substrate with accelerometers, temperature sensors and pressure sensors for health monitoring and prognostics of aircraft EWIS.Engineering and Physical Sciences Research Council (EPSRC

Micro-manufactured Rogowski coils for fault detection of aircraft electrical wiring and interconnect systems (EWIS)

Aircraft wiring failures have increased over the last few years resulting in arc faults and high-energy flashover on the wiring bundle, which can propagate down through aircraft Electrical Wiring and Interconnect Systems (EWIS). It is considered cost prohibitive to completely rewire a plane in terms of man hours and operational time lost to do this, and most faults are only detectable whilst the aircraft is in flight. Temperature, humidity and vibration all accelerate ageing and failure effects on EWIS. This research investigates methods of in-situ non-invasive testing of aircraft wiring during fight. Failure Mode Effects and Analysis (FMEA) was performed on legacy aircraft EWIS using data obtained from RAF Brize Norton. Micro-Electro-mechanical- Systems (MEMS) were evaluated for use in a wire monitoring system that measures the environmental parameters responsible for ageing and failure of EWIS. Such MEMS can be developed into a Health and Usage Monitoring MicroSystem (HUMMS) by incorporating advanced signal processing and prognostic software. Current and humidity sensors were chosen for further investigation in this thesis. These sensors can be positioned inside and outside cable connectors of EWIS so that arc faults can be reliably detected and located. This thesis presents the design, manufacture and test of micro-manufactured Rogowski sensors. The manufactured sensors were benchmarked against commercial high frequency current transformers (HFCT), as these devices can also detect high frequency current signature due to wire insulation failure. Results indicate that these sensors possess superior voltage output compared to the HFCT. The design, manufacture and test of a polymer capacitive humidity sensor is also presented. Two different types of polymer were reviewed as part of the evaluation. A feature of the sensor design is recovery from exposure to chemicals found on wiring bundles. Current and humidity sensors were demonstrated to be suitable for integrating onto a common substrate with accelerometers, temperature sensors and pressure sensors for health monitoring and prognostics of aircraft EWIS

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results

Testability and redundancy techniques for improved yield and reliability of CMOS VLSI circuits

The research presented in this thesis is concerned with the design of fault-tolerant integrated circuits as a contribution to the design of fault-tolerant systems. The economical manufacture of very large area ICs will necessitate the incorporation of fault-tolerance features which are routinely employed in current high density dynamic random access memories. Furthermore, the growing use of ICs in safety-critical applications and/or hostile environments in addition to the prospect of single-chip systems will mandate the use of fault-tolerance for improved reliability. A fault-tolerant IC must be able to detect and correct all possible faults that may affect its operation. The ability of a chip to detect its own faults is not only necessary for fault-tolerance, but it is also regarded as the ultimate solution to the problem of testing. Off-line periodic testing is selected for this research because it achieves better coverage of physical faults and it requires less extra hardware than on-line error detection techniques. Tests for CMOS stuck-open faults are shown to detect all other faults. Simple test sequence generation procedures for the detection of all faults are derived. The test sequences generated by these procedures produce a trivial output, thereby, greatly simplifying the task of test response analysis. A further advantage of the proposed test generation procedures is that they do not require the enumeration of faults. The implementation of built-in self-test is considered and it is shown that the hardware overhead is comparable to that associated with pseudo-random and pseudo-exhaustive techniques while achieving a much higher fault coverage through-the use of the proposed test generation procedures. The consideration of the problem of testing the test circuitry led to the conclusion that complete test coverage may be achieved if separate chips cooperate in testing each other's untested parts. An alternative approach towards complete test coverage would be to design the test circuitry so that it is as distributed as possible and so that it is tested as it performs its function. Fault correction relies on the provision of spare units and a means of reconfiguring the circuit so that the faulty units are discarded. This raises the question of what is the optimum size of a unit? A mathematical model, linking yield and reliability is therefore developed to answer such a question and also to study the effects of such parameters as the amount of redundancy, the size of the additional circuitry required for testing and reconfiguration, and the effect of periodic testing on reliability. The stringent requirement on the size of the reconfiguration logic is illustrated by the application of the model to a typical example. Another important result concerns the effect of periodic testing on reliability. It is shown that periodic off-line testing can achieve approximately the same level of reliability as on-line testing, even when the time between tests is many hundreds of hours

Automatic Control and Fault Diagnosis of MEMS Lateral Comb Resonators

Recent advancements in microfabrication of Micro Electro Mechanical Systems have made MEMS an important part of many applications such as safety and sensor/control devices. Miniature structure of MEMS makes them very sensitive to the environmental and operating conditions. In addition, fault in the device might change the parameters and result in unwanted behavioral variations. Therefore, imperfect device structure, fault and operating point dependencies suggest for active control of MEMS.;This research is focused on two main areas of control and fault diagnosis of MEMS devices. In the control part, the application of adaptive controllers is introduced for trajectory control of the device under health and fault conditions. Fault in different forms in the structure of the device are modeled and foundry manufactured for experimental verifications. Pull-in voltage effect in the MEMS Lateral Comb Resonators are investigated and controlled by variable structure controllers. Reliability of operation is enhanced by active control of the device under fault conditions.;The second part of this research is focused on the fault diagnosis of the MEMS devices. Fault is introduced and investigated for better understanding of the system behavioral changes. Modeling of the device in different operating conditions suggests for the multiple-model adaptive estimation (MMAE) fault diagnosis technique. Application of Kalman filters in MMAE is investigated and the performance of the fault diagnosis is compared with other techniques such as self-tuning and auto self-tuning techniques. According to the varying parameters of the system, online parameter identification systems are required to monitor the parameter variations and model the system accurately. Self-tuning banks are applied and combined with MMAE to provide accurate fault diagnosis systems. Different parameter identification techniques result in different system performances. In this regard, this research investigates the application of Recursive Least Square with Forgetting Factor. Different techniques for tuning of forgetting factor value are introduced and their results are compared for better performance. The organization of this dissertation is as follows:;Chapter I introduces the structure of the MEMS Lateral Comb Resonator; Chapter II introduces the application of control techniques and displacement feedback approach. Chapter III investigates the control approach and experimental results. In chapter IV, a new controller is introduced and designed for the MEMS trajectory controls. Chapter V is about the fault and different techniques of fault diagnosis in MEMS LCRs. Chapter 6 is the future work suggested through the current results and observations. Each chapter contains a section to summarize the concluding remarks

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point