Temporal management using relative time in knowledge-based process control

In this paper, a knowledge-based approach is proposed for the management of temporal information in process control. A common-sense theory of temporal constraints over processes/events, allowing relative temporal knowledge, is employed here as the temporal basis for the system. This theory supports duration reasoning and consistency checking, and accepts relative temporal knowledge which is in a form normally used by human operators. An architecture for process control is proposed which centres on an historical database consisting of events and processes, together with the qualitative temporal relationships between their occurrences. The dynamics of the system is expressed by means of three types of rule: database updating rules, process control rules, and data deletion rules. An example is provided in the form of a life scheduler, to illustrate the database and the rule sets. The example demonstrates the transitions of the database over time, and identifies the procedure in terms of a state transition model for the application. The dividing instant problem for logical inference is discussed with reference to this process control example, and it is shown how the temporal theory employed can be used to deal with the problem.

A qualitative temporal information system for process control

A general system is presented in this paper which supports the expression of relative temporal knowledge in process control and management. This system allows knowledge of Allen's temporal relations over time elements, which may be both intervals and points. The objectives and characteristics of two major temporal attributes, i.e. ‘transaction time’ and ‘valid time’, are described. A graphical representation for the temporal network is presented, and inference over the network may be made by means of a consistency checker in terms of the graphical representation. An illustrative example of the system as applied to process control and management is provided.

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Risk mitigation framework for a robust design process

The increasing complexity of new manufacturing processes and the continuously growing range of fabrication options mean that critical decisions about the insertion of new technologies must be made as early as possible in the design process. Mitigating the technology risks under limited knowledge is a key factor and major requirement to secure a successful development of the new technologies. In order to address this challenge, a risk mitigation methodology that incorporates both qualitative and quantitative analysis is required. This paper outlines the methodology being developed under a major UK grand challenge project - 3D-Mintegration. The main focus is on identifying the risks through identification of the product key characteristics using a product breakdown approach. The assessment of the identified risks uses quantification and prioritisation techniques to evaluate and rank the risks. Traditional statistical process control based on process capability and six sigma concepts are applied to measure the process capability as a result of the risks that have been identified. This paper also details a numerical approach that can be used to undertake risk analysis. This methodology is based on computational framework where modelling and statistical techniques are integrated. Also, an example of modeling and simulation technique is given using focused ion beam which is among the investigated in the project manufacturing processes.

Uncertainty analysis to minimise risk in designing micro-electronics manufacturing processes

A design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the process control of micro and nano-electronics based manufacturing processes is presented in this paper. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to help understand how a pre-defined geometry of micro- and nano- structures can be achieved using this technology. The process performance is characterised on the basis of developed Reduced Order Models (ROM) and are generated using results from a mathematical model of the Focused Ion Beam and Design of Experiment (DoE) methods. Two ion beam sources, Argon and Gallium ions, have been used to compare and quantify the process variable uncertainties that can be observed during the milling process. The evaluations of the process performance takes into account the uncertainties and variations of the process variables and are used to identify their impact on the reliability and quality of the fabricated structure. An optimisation based design task is to identify the optimal process conditions, by varying the process variables, so that certain quality objectives and requirements are achieved and imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Modelling the effect of temperature on product reliability

Reliability of electronic parts is a major concern for many manufacturers, since early failures in the field can cost an enormous amount to repair - in many cases far more than the original cost of the product. A great deal of effort is expended by manufacturers to determine the failure rates for a process or the fraction of parts that will fail in a period of time. It is widely recognized that the traditional approach to reliability predictions for electronic systems are not suitable for today's products. This approach, based on statistical methods only, does not address the physics governing the failure mechanisms in electronic systems. This paper discusses virtual prototyping technologies which can predict the physics taking place and relate this to appropriate failure mechanisms. Simulation results illustrate the effect of temperature on the assembly process of an electronic package and the lifetime of a flip-chip package.

Optimisation methodology for risk mitigation in advanced micro-system electronics manufacturing

This paper presents a design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the development of new advanced technologies in the area of micro and nano systems. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to provide knowledge of how a pre-defined geometry can be achieved through this direct milling. The geometry characterisation is obtained using a Reduced Order Models (ROM), generated from the results of a mathematical model of the Focused Ion Beam, and Design of Experiment (DoE) methods. In this work, the focus is on the design flow methodology which includes an approach on how to include process parameter uncertainties into the process optimisation modelling framework. A discussion on the impact of the process parameters, and their variations, on the quality and performance of the fabricated structure is also presented. The design task is to identify the optimal process conditions, by altering the process parameters, so that certain reliability and confidence of the application is achieved and the imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

The Jama legal narrative. Part II: A foray into concepts of improbability

In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, we reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: "The Jama Model. On Legal Narratives and Interpretation Patterns"), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story, is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability was infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for AI researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially bayesian probability) in accounts of evidence has been flouishing among legal scholars. Nowadays both the the Bayesians (e.g. Peter Tillers) and Bayesioskeptics (e.g. Ron Allen) among those legal scholars whoare involved in the controversy are willing to give AI researchers a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application or probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making (Rosoni 1995). Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

The Jama legal narrative part II: A foray into concepts of improbability

In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches, which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, I reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: 'The JAMA Model and Narrative Interpretation Patterns'), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability were infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for Artificial Intelligence (AI) researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially Bayesian probability) in accounts of evidence has been flourishing among legal scholars; nowadays both the Bayesians (e.g. Peter Tillers) and the Bayesio-skeptics (e.g. Ron Allen), among those legal scholars who are involved in the controversy, are willing to give AI research a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application of probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making. Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

Modeling the dynamics of electromagnetically agitated metallurgical flows: levitation, cold crucible, aluminium electrolysis, etc.

We present practical modelling techniques for electromagnetically agitated liquid metal flows involving dynamic change of the fluid volume and shape during melting and the free surface oscillation. Typically the electromagnetic field is strongly coupled to the free surface dynamics and the heat-mass transfer. Accurate pseudo-spectral code and the k-omega turbulence model modified for complex and transitional flows with free surfaces are used for these simulations. The considered examples include magnetic suspension melting, induction scull remelting (cold crucible), levitation and aluminium electrolysis cells. The process control and the energy savings issues are analysed.

Computer modelling of the reliability of flip chips with metal column bumping

Recently, research has been carried out to test a novel bumping method which omits the under bump metallurgy forming process by bonding copper columns directly onto the Al pads of the silicon dies. This bumping method could be adopted to simplify the flip chip manufacturing process, increase the productivity and achieve a higher I/O count. This paper describes an investigation of the solder joint reliability of flip-chips based on this new bumping process. Computer modelling methods are used to predict the shape of solder joints and response of flip chips to thermal cyclic loading. The accumulated plastic strain energy at the comer solder joints is used as the damage indicator. Models with a range of design parameters have been compared for their reliability. The parameters that have been investigated are the copper column height, radius and solder volume. The ranking of the relative importance of these parameters is given. For most of the results presented in the paper, the solder material has been assumed to be the lead-free 96.5Sn3.5Ag alloy but some results for 60Sn40Pb solder joints have also been presented.

Computational approach for reliable and robust system-in-package design

A computational modelling approach integrated with optimisation and statistical methods that can aid the development of reliable and robust electronic packages and systems is presented. The design for reliability methodology is demonstrated for the design of a SiP structure. In this study the focus is on the procedure for representing the uncertainties in the package design parameters, their impact on reliability and robustness of the package design and how these can be included in the design optimisation modelling framework. The analysis of thermo-mechanical behaviour of the package is conducted using non-linear transient finite element simulations. Key system responses of interest, the fatigue life-time of the lead-free solder interconnects and warpage of the package, are predicted and used subsequently for design purposes. The design tasks are to identify the optimal SiP designs by varying several package input parameters so that the reliability and the robustness of the package are improved and in the same time specified performance criteria are also satisfied