STEP COMPLIANT APPROACH FOR TURN-MILL OPERATIONS

Current machine tools have incurred challenges on limitation such as part programming complexity of G and M code, weak integration of digital machine tools and coverage of universal data modeling for product and manufacturing resources. In response to this manufacturing system requirement, Standard for Exchange of Product data (STEP) and its implementation on developing an interface for the next generation of machine tool controllers (STEP-NC) has become a concern of research interest and performed on basic manufacturing technology limited to a unit domain such as turning, milling or Wire EDM. Therefore; extending this STEP implementation on multipurpose machine tools such as turn-mill machines is mandatory since the machines are the main component in these industries. The research work offers a STEP-NC compliant interface supporting turn-mill machining environment identified as SCSTMO

On flexibly integrating machine vision inspection systems in PCB manufacture

The objective of this research is to advance computer vision techniques and their applications in the electronics manufacturing industry. The research has been carried out with specific reference to the design of automatic optical inspection (AOI) systems and their role in the manufacture of printed circuit boards (PCBs). To achieve this objective, application areas of AOI systems in PCB manufacture have been examined. As a result, a requirement for enhanced performance characteristics has been identified and novel approaches and image processing algorithms have been evolved which can be used within next generation of AOI systems. The approaches are based on gaining an understanding of ways in which manufacturing information can be used to support AOI operations. Through providing information support, an AOI system has access to product models and associated information which can be used to enhance the execution of visual inspection tasks. Manufacturing systems integration, or more accurately controlled access to electronic information, is the key to the approaches. Also in the thesis methods are proposed to achieve the flexible integration of AOI systems (and computer vision systems in general) within their host PCB manufacturing environment. Furthermore, potential applications of information supported AOI systems at various stages of PCB manufacturing have been studied. It is envisaged that more efficient and cost-effective applications of AOI can be attained through adopting the flexible integration methods proposed, since AOI-generated information can now be accessed and utilized by other processes

Automated feature recognition system for supporting engineering activities downstream of conceptual design.

Transfer of information between CAD models and downstream manufacturing process planning software typically involves redundant user interaction. Many existing tools are process-centric and unsuited for selection of a "best process" in the context of existing concurrent engineering design tools. A computer based Feature-Recognition (FR) process is developed to extract critical manufacturing features from engineering product CAD models. FR technology is used for automating the extraction of data from CAD product models and uses wire-frame geometry extracted from an IGES neutral file format. Existing hint-based feature recognition techniques have been extended to encompass a broader range of manufacturing domains than typical in the literature, by utilizing a combination of algorithms, each successful at a limited range of features. Use of wire-frame models simplifies product geometry and has the potential to support rapid manufacturing shape evaluation at the conceptual design stage. Native CAD files are converted to IGES neutral files to provide geometry data marshalling to remove variations in user modelling practice, and to provide a consistent starting point for FR operations. Wire-frame models are investigated to reduce computer resources compared to surface and solid models, and provide a means to recover intellectual property in terms of manufacturing design intent from legacy and contemporary product models. Geometric ambiguity in regard to what is ?solid? and what is not has plagued wire-frame FR development in the past. A new application of crossing number theory (CNT) has been developed to solve the wire-frame ambiguity problem for a range of test parts. The CNT approach works satisfactorily for products where all faces of the product can be recovered and is tested using a variety of mechanical engineering parts. Platform independent tools like Extensible Mark-up Language are used to capture data from the FR application and provide a means to separate FR and decision support applications. Separate applications are composed of reusable software modules that may be combined as required. Combining rule-based and case-based reasoning provides decision support to the manufacturing application as a means of rejecting unsuitable processes on functional and economic grounds while retaining verifiable decision pathways to satisfy industry regulators

Combining business process and failure modelling to increase yield in electronics manufacturing

The prediction and capturing of defects in low-volume assembly of electronics is a technical challenge that is a prerequisite for design for manufacturing (DfM) and business process improvement (BPI) to increase first-time yields and reduce production costs. Failures at the component-level (component defects) and system-level (such as defects in design and manufacturing) have not been incorporated in combined prediction models. BPI efforts should have predictive capability while supporting flexible production and changes in business models. This research was aimed at the integration of enterprise modelling (EM) and failure models (FM) to support business decision making by predicting system-level defects. An enhanced business modelling approach which provides a set of accessible failure models at a given business process level is presented in this article. This model-driven approach allows the evaluation of product and process performance and hence feedback to design and manufacturing activities hence improving first-time yield and product quality. A case in low-volume, high-complexity electronics assembly industry shows how the approach leverages standard modelling techniques and facilitates the understanding of the causes of poor manufacturing performance using a set of surface mount technology (SMT) process failure models. A prototype application tool was developed and tested in a collaborator site to evaluate the integration of business process models with the execution entities, such as software tools, business database, and simulation engines. The proposed concept was tested for the defect data collection and prediction in the described case study

Process Comprehension for Interoperable CNC Manufacturing

Over the last 40 years manufacturing industry has enjoyed a rapid growth with the support of various computer-aided systems (CAD, CAPP, CAM etc.) known as CAx. Since the first Numerically Controlled (NC) machine appeared in 1952, there have been many advances in CAx resource capabilities. The information integration and interoperability between different manufacturing resources has become an important and popular research area over the last decade. Computer Numerically Controlled (CNC) machines are an important link in the manufacturing chain and the major contributor to the production capacity of manufacturing industry today. However, most of the research has focused on the information integration of upper systems in the CAD/CAPP /CAM/CNC manufacturing chain, leaving the shop floor as an isolated information island. In particular, there is limited opportunity to capture and feed shopfloor knowledge back to the upper systems. Furthermore, the part programs for the machines are not exchangeable due to the. machine specific postprocessors. Thus there is a further need to consider information interoperability between different CNC machine and other systems. This research investigates the reverse transformation of the CNC part programmes into higher level of process information, entitled process comprehension, to enable the shopfloor interoperability. A novel framework of universal process comprehension is specified and designed. The framework provides a reverse direction of information flow from the CNC machine to upper CAx systems, enabling the interoperability and recycling of the shopfloor knowledge. A prototype implementation of the framework is realised and utilised to demonstrate the functionalities through three industrially inspired test components. The major contribution of this research to knowledge is the new vision of the shopfloor interoperability associated with process knowledge capture and reuse. The research shows that process comprehension of part programmes can provide an effective solution to the issues of the shopfloor interoperability and knowledge reuse in manufacturing industries.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Feature-based representation for assembly modelling

The need for a product model which can support the modelling requirements of a broad range of applications leads to the application of a feature-based model. An important requirement in feature-based design and manufacture is that a single feature representation should be capable of supporting a number of different applications. The capability of representing products composed of assemblies is seen to be necessary to serve the information needs of those applications. To achieve this aim it is an essential prerequisite to develop a formal structure for the representation of assembly information in a feature-based design system. This research addresses two basic questions related to the lack of a unified definition for features and the problem of representing assemblies in a feature-based representation. The intention is to extend the concept of designing with features by incorporating assembly information in addition to the geometrical and topological details of component parts. This allows models to be assembled using the assembly information within the feature definitions. Features in this research are defined as machined volumes which are represented in a hierarchical taxonomy. The taxonomy includes several types and profiles of features which cover a general range of machined parts. A hierarchical assembly structure is also defined in which features form basic entities in the assembly. Each feature includes information needed to establish assembly relationships among features in the form of mating relationships. An analysis of typical assemblies shows that assembly interfaces occur at the face level of the mating features and between features themselves. Three mating relationships between pairs of features have been defined (against, fits and align) and are represented in the form of expressions that can be used for evaluations. Various sub-types of these major mating relationships can be identified (e.g. tight fit, clearance fit, etc.) and represented through the use of qualifying attributes. Component Relation Graphs, Feature Relation Graphs and Face Mating Graphs have been developed to represent each level of interaction in an assembly, and assembly relationships are combined with knowledge on process planning into a Component Connectivity Graph. These graphs are used as the basis for deriving an integrated data structure which is used for defining classes for each level in the assembly hierarchy. The implementation of a prototype system has been facilitated by use of an object-oriented programming technique which provides a natural method of adding functionality to the geometric reasoning process of features and the complex relationships between the parts that make up the assembly. The feature-based model is embedded in an object-oriented solid modeller kernel, ACIS®. The research demonstrates the possibilities for a single feature representation to support multiple activities within a computer integrated manufacturing environment. Such a representation can form the basis of design improvement techniques and manufacturing planning as well as be a model to support the life cycle of the product

Short Wave Infrared Imaging System for Night and Day Long Range Facial Recognition and Surveillance

The capability to detect, observe, and positively identify people at a distance is important to numerous security and defense applications. Traditional solutions for human detection and observation include long-range visible imagers for daytime and thermal infrared imagers for night-time use. Positive identification, through computer face recognition, requires facial imagery that can be repeatably matched to a database of visible spectrum facial mug shots. Nighttime identification at large distances is not possible with visible imagers due to lack of light, or with thermal infrared imagers due to poor correlation with visible facial imagery. An active-SWIR imaging system was developed that is eye-safe, invisible, and capable of producing close-up facial imagery at distances of several hundred meters and full body images to thousands of meters, even in total darkness. The SWIR images correlate well to the visible spectrum allowing for biometric facial recognition and long range target detection either day or night. The process of researching existing technologies, establishing requirements of a suitable system, design process, and hardware implementation will be discussed in great detail. Once the system is assembled, it will be used to acquire data not yet produced by any existing technology. The results will be examined and a discussion made into future work

Development of a manufacturability analysis system for reinforced plastics components.

This thesis describes the research and development of a systematic and consistent methodology to perform manufacturability analysis of Reinforced Plastic Parts (RPP). The proposed methodology evaluates the part model in the early stages of the product development process considering the capabilities and constraints of available manufacturing processes, materials and tooling required in standard RPP production. Critical Manufacturing Part Features (CMPF) are identified and the relationship between the model's geometrical information, the expert's geometric reasoning, and the knowledge about the involved manufacturing processes are clarified and set together in an efficient feature-rule-based manufacturability analysis system. The prototype system named 'FEBAMAPP', combines solid modelling (SM), automatic feature recognition (AFR), object oriented programming (OOP), and a rule-based system (RBS) in order to assess the manufacturability of the proposed design. The novelty of this research is based in the use of a Face Vector (FVector) concept to transform geometrical and topological information of the solid model into a suitable input data to be used in the Neural Network Feature Recognition System. Further novelty arises from the fact that this is the first attempt to use neural networks in the recognition of 3-D features in hollow parts including the presence of fillets along the edges of the part. The manufacturability evaluation can be performed considering different combinations of materials along with different manufacturing processes giving the designer the opportunity of selecting an appropriate combination for any specific application. Promising results have been obtained during the test of the system, where 100 % recognition of trained features with 90% confidence has been achieved. Also, good results have been obtained in the recognition of non-trained features such as the Cross-Slot feature, which is recognised as a Slot feature. After automatic feature recognition, Manufacturability Analysis is focused on internal and external characteristics of the model's features, where potential manufacturing difficulties are identified and feedback in terms of design suggestions is then used to advise the design process and improve the overall manufacturability of the part. This manufacturability evaluation in terms of internal and external characteristics of the features has proved to be efficient in detecting detailed design errors that can be costly in further manufacturing stages in the product development process