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<p> The experience shows that any shortcoming in defining the requirements for computer based systems imperils the deliverables of all the subsequent stages of their development. This importance is undeniable when dealing with manufacturing software-systems due to their significant role in all spheres of human life. These systems have very stringent non-functional requirements such as accuracy and real-time constraints. The development of manufacturing software-systems is very challenging and requires special caution, since any mistake might have broad impact on very expensive work-pieces or might lead to a machining accident with irreparable effects. The success of their development depends largely on the quality of their Software Requirements Specification Document (SRSD).</p> <p> We propose a new requirements template specifically designed for manufacturing systems. The template is structured to reflect their characteristics including multi-constraints and multi-disciplinary problems, multi-stage processes, multi-tasking, dynamic behavior, evolutionary nature, time-varying physical characteristics, and the usage of complex scientific models. A complementary usage of goal-driven, viewpoint oriented, and scenario-based approach is adopted for structuring the template content. To provide a high quality SRSD, the template is designed to enhance unambiguity, consistency, completeness, precision, non-redundancy, and good organization of the requirements document as well as other criteria including breadth of applicability and methodology independence.</p> <p> An automated tool for requirements management according to the proposed template has been designed and implemented. The requirements management tool provides relatively secure and easy-to-use capabilities for the documentation and the retrieval of the requirements. It accelerates capturing the requirements, improves system quality by enhancing the reduction of requirements errors, and helps in establishing a common understanding between the system builders and the stakeholders. In addition to a user friendly environment for changing the information, we developed a powerful dynamic report generator that can be configured by the user and that provides a simple way for retrieving the requirements and formatting them.</p> <p> Both the template and the tool have been validated using the requirements for a Tool Trajectory Planning for High Speed Machining system developed at the Aerospace Manufacturing Technology Centre, Institute for Aerospace Research (Montreal).</p> / Thesis / Master of Science (MSc)

No / This paper presents Reconfigurable Manufacturing System (RMS) characteristics through comparison with conventional manufacturing systems in order to address a design strategy towards a RMS. The strategy is considered as apart of a RMS design loop to achieve a reconfigurable strategy over its implementation period. As another part of the design loop, a reconfiguration link between market and manufacturing is presented in order to group products into families (reconfiguring products) and then assign them to the required manufacturing processes over configuration stages. In particular, the Analytical Hierarchical Process (AHP) is employed for structuring the decision making process for the selection of a manufacturing system among feasible alternatives based on the RMS study. Manufacturing responsiveness is considered as the ability of using existing resources to reflect new environmental and technological changes quickly. The AHP model highlights manufacturing responsiveness as a new economic objective along with classical objectives such as low cost and high quality. The forward-backward process is then proposed to direct and control the design strategy under uncertain conditions during its implementation period. The proposed hierarchy is generic in structure and could be applicable to many firms by means of restructuring the criteria. This work is based on a case study in a manufacturing environment. Expert Choice software (Expert Choice 1999) is applied to examine the structure of the proposed model and achieve synthesise/ graphical results considering inconsistency ratios. The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Finally, to allocate available resources to the alternative solutions, a (0-1) knapsack formulation algorithm is represented.

In real-word manufacturing environments, finding the right job sequences and their associated schedules when resource, precedence, and timing constraints are imposed is a difficult task. For most practical problems classical scheduling easily leads to an exponential growth in the number of possible schedules. Moreover, a decision time period of hours or even minutes is too long. Good solutions are often needed in real-time. The problem becomes even more complicated if changes, such as new orders or resource breakdowns, occur within the manufacturing system. One approach to overcome the challenges of solving classical scheduling problems is the use of distributed schemes such as agent or holonic-based control architectures. This dissertation presents an innovative control architecture that uses the holonic concept, capable of delivering good solutions when applied in dynamic environments. The general holonic control framework presented in this research has specific characteristics not found in others reported so far. Using a modular approach it takes into account all the categories of hardware and software resources of a manufacturing system. Due to its modularity, the holonic control framework can be used for assigning and scheduling different task types, separately or simultaneously. Thus, it can be used not only for assigning and scheduling transport tasks, but also for finding feasible solutions to the job assignment and scheduling of processing tasks, or to better utilize the auxiliary equipment and devices in a manufacturing system. In the holonic system, under real-time constraints, a feasible schedule for the material handling resources emerges from the combination of individual holon's schedules. Internal evaluation algorithms and coordination mechanisms between the entities in the architecture form the basis for the resultant schedules. The experimental results obtained show a percentage difference between the makespan values obtained using the holonic scheduling approach and the optimal values of under seven percent. Since current control systems in use in industry lack the ability to adapt to dynamic manufacturing environments, the holonic architecture designed and the tests performed in this research could be a part in the effort to build the foundations for the control systems of the next generation manufacturing systems. / Ph. D.

Manufacturing systems are usually nonlinear, nonstationary, highly corrupted with outliers, and oftentimes constrained by physical laws. Modeling and approximation of their underly- ing response surface functions are extremely challenging. Bayesian optimization is a great statistical tool, based on Bayes rule, used to optimize and model these expensive-to-evaluate functions. Bayesian optimization comprises of two important components namely, a sur- rogate model often the Gaussian process and an acquisition function often the expected improvement. The Gaussian process, known for its outstanding modeling and uncertainty quantification capabilities, is used to represent the underlying response surface function, while the expected improvement is used to select the next point to be evaluated by trading- off exploitation and exploration. Although Bayesian optimization has been extensively used in optimizing unknown and expensive-to-evaluate functions and in hyperparameter tuning of deep learning models, mod- eling highly outlier-corrupted, nonstationary, and stress-induced response surface functions hinder the use of conventional Bayesian optimization models in manufacturing systems. To overcome these limitations, we propose a series of systematic methodologies to improve Bayesian optimization for engineering design and quality control of manufacturing systems. Specifically, the contributions of this dissertation can be summarized as follows. 1. A novel asymmetric robust kernel function, called AEN-RBF, is proposed to model highly outlier-corrupted functions. Two new hyperparameters are introduced to im- prove the flexibility and robustness of the Gaussian process model. 2. A nonstationary surrogate model that utilizes deep multi-layer Gaussian processes, called MGP-CBO, is developed to improve the modeling of complex anisotropic con- strained nonstationary functions. 3. A Stress-Aware Optimal Actuator Placement framework is designed to model and op- timize stress-induced nonlinear constrained functions. Through extensive evaluations, the proposed methodologies have shown outstanding and significant improvements when compared to state-of-the-art models. Although these pro- posed methodologies have been applied to certain manufacturing systems, they can be easily adapted to other broad ranges of problems. / Doctor of Philosophy / Modeling advanced manufacturing systems, such as engineering design and quality moni- toring and control, is extremely challenging. The underlying response surface functions of these manufacturing systems are often nonlinear, nonstationary, and expensive-to-evaluate. Bayesian optimization, a statistical modeling approach based on Bayes rule, is used to rep- resent and model those complex (i.e., black-box) objective functions. A Bayesian optimiza- tion model consists of a surrogate model, often the Gaussian process, and an acquisition function, often the expected improvement. Conventional Bayesian optimization models do not accurately represent non-stationary and outlier-corrupted functions. To overcome these limitations, we propose a new asymmetric robust kernel function to improve the model- ing capabilities of the Gaussian process model in process quality control through improved defect detection and classification. We also propose a non-stationary surrogate model to improve the performance of Bayesian optimization in aerospace process design problems. Finally, we develop a new optimization framework that models and optimizes stress-induced constrained aerospace manufacturing systems correctly. Our extensive experiments show significant improvements of these three proposed models when compared to state-of-the-art methodologies.

Industry's move towards automated manufacturing has been rapid during this decade. In a typical flexible manufacturing environment, a variety of automated manufacturing equipment is linked together with a communication network and a part transportation system. Since vendors of automation equipment have no communication standards to adhere to, integrating these machines becomes a problem. This project addressed the problem by creating a software interface between robots, CNC machines and a workcell controller. The library of functions created for the Dyna CNC machine and the IBM 7545/7547 robots will aid the future user to create software for the workcell. By using the library functions, a user will be insulated from the lower level functioning of the machines and need only be concerned about the operation of these functions. / Master of Science

This thesis is an initial attempt at analyzing the "product-process matrix," a framework suggesting the interaction of product and process life cycles. The objectives of this thesis were to test the theory surrounding the "product-process matrix" and also test theories concerning the transition of strategic objectives between "product-process matrix" regions. The methodology included conducting a survey of Virginia manufacturing firms on strategic concerns, constructing a database into which survey responses were loaded, and analyzing survey responses. Results of this survey suggested that the theory surrounding the "product-process matrix" may be inappropriate. Results also indicated the possibility that row and column descriptions of the current "product-process matrix" may need alterations in order to be more applicable to manufacturing firms. Further research is necessary to examine possible biases associated with the survey instrument and survey sample. After such research has been undertaken, it is recommended that continued work in this area may help to improve understanding the interaction between markets and manufacturing processes. / Master of Science

The planning and control of manufacturing systems is a complex activity involving a myriad of decisions and optimization algorithms. ln a Computer Integrated Manufacturing System (CIMS) these decisions and algorithms span several functions, require information from several sources, and have consequences in several sectors of the manufacturing system. This dissertation is concerned with the development of a structured methodology for executing this activity. Therefore, the primary activities are first, to develop the framework for a Computer Integrated Production Planning and Control (ClPP&C) system, and second, to formulate and solve specific mathematical models which are nested in the developed framework. The framework functions as a "city plan" for the production control activity in a CIMS environment, while the mathematical methodologies are pieces of the decision architecture. Achieving a CIMS implies achieving an integrated manufacturing system. Implying the production control system needs to be designed with specific consideration of the concepts, issues, and principles of integrated manufacturing. As such, these concepts, issues and principles are identified and developed in this research. A model of CIMS is developed and the role of ClPP&C is analyzed. A framework for integration in manufacturing is developed and used to guide the modeling efforts. . The ClPP&C "city plan" is developed using an adaptation of the IDEF methodology. The objective of the plan is to define the separate problems which are to be solved in production control, the interrelationships between these problems, and the synergy which causes them to behave as a single system. This research specifically addresses the master aggregate scheduling (MA-Schedule) and the coordinating production scheduling (CP-Schedule) problems within the CIPP&C plan. The MA-Scheduling problem prescribes how much of a family is to be produced in a time period, and is formulated in detail as a non-linear 0-1 mixed integer program. The formulation aggregates capacity, time, and products; models routing and capacity flexibility; and considers the availability of material transporters. The solution procedure incorporates linearization methods, preprocessing algorithms, and large-scale MIP solvers. The CP-Schedule is formulated as two separate problems. The first disaggregates time and product and is to be solved as a MIP. The second problem determines the start time of each product batch at a cell. lt is equivalent to the minimum makespan problem and solution approaches are discussed. A network of programs was designed to execute the scheduling methodology. Experimental results with the methodology are reported. These results provide insights into system performance in various conditions. Specifically, the impact of flexibility, loading, transporter availability, and cost dimensions are analyzed. / Ph. D.

The purpose of this study was to examine and compare the flexibilities of three apparel production systems to variations in products manufactured on them. The production system used by a company was determined based on five system attributes (i.e., type of workflow, level of WIP inventory, number of tasks, mode of transportation between workstations, and level of interaction between operators). The product line of the company (i.e., staple, semi-staple, fashion, and high-fashion) was determined based on the number and type of collar designs manufactured by the company. Flexibility of a system was determined by the range of collar designs manufactured by the system. A stratified proportionate random sample of manufacturers producing men's and women's shirts and blouses was selected for the survey. The questionnaire was pilot tested for content validity and reliability. The adjusted response rate was 39% (n = 52). Non-parametric tests were performed to test the statistical significance of the hypothesized relationships. Three production systems (i.e., bundle system, progressive bundle system [PBS], and modular system) were compared for their volume of production. The size of the company (i.e., number of employees and the total volume of production) was compared between the three production systems. The five system attributes were found to be significantly related to the system used. The procedure adopted for determining the product line of the company was also found to be significant. The relationship between production systems and product lines was significant in some of the cases and not significant in others. PBS was found to be most flexible due to its ability to accommodate a greater style variation followed by bundle system and modular system. The relationship between production systems and the volume of production and also between the system and the size of the company were not significant. / Master of Science

There exists today a variety of Computer Aided Process Planning (CAPP) systems that have been designed, developed, and implemented irrespective of the facility's condition and status. It is often found in practice that Computer Integrated Manufacturing (CIM) constituents such as production control, loading, sequencing, scheduling, etc. do not interact with Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), or CAPP. They operate as stand alone techniques that are not interrelated in the CIM scenario. This could be overcome through increased, improved communication between CAD, CAPP, CAM, and other CIM constituents. CAPP has to be tied into the computerization of other CIM functions. An approach in this direction is what this research presents. Its uniqueness is that it relates CAPP in a flexible manufacturing system atmosphere with scheduling, in effect relating CAPP with production control. It integrates process selection and route generation with factors such as facility congestion, work in process, flowtime, machine utilization and dynamic shop conditions. The generation of alternate routes, and the incorporation of this technique in a CAPP system is an unique approach to the problem of interrelating CAPP with other CIM components. This involved the design and development of software that can model facility capacity, understand part construction, maintain and track shop status, reason through the facility capacity to arrive at possible machining sequences and job routes, and apply a heuristic to arrive at the job route through the facility. This results in the introduction and implementation of the concept of dynamic scheduling and alternate route generation in CAPP systems. The objective in global terms was to construct a CAPP system that considers routing and production control for a FMS that consists of several high capacity, modern machines. The concepts mentioned above are combined and coalesced in a CAPP system that truly provides computerized assistance to the process planning function at a macro-level. This research attempts to create a truly integrated CAPP system within a CIM atmosphere. / Ph. D.