S. B. Tor

An object-oriented intelligent disassembly sequence planner for maintenance

This paper presents a prototype object-oriented intelligent disassembly sequence planner for maintenance. A novel disassembly representation scheme known as disassembly constraint graph (DCG) has been proposed and implemented as a prototype system in this work. Using the DCG, all the possible disassembly operations that are needed for the maintenance of certain components or subassemblies can be deduced. Subsequently, a sequence-based optimisation technique, genetic algorithms, is employed to generate near optimal disassembly sequence from all the feasible combination of these disassembly operations. Based on the DCG, an object-oriented intelligent disassembly sequence planner for maintenance has been developed. The prototype system comprises three modules each having a set of objects. Users are able to view the entire disassembly process in accordance to the near optimal sequence generated by the planner via a graphical user interface. Two case studies, which are used to illustrate the effectiveness of the planner, are presented.

Feature-based CAD-CAE integration model for injection-moulded product design

One prominent characteristic of product design for injection-moulded parts is that design and analysis (e.g. flow simulation) go hand in hand to ensure that the design is manufacturable by the injection-moulding process. Despite the wide use of CAD and CAE systems, the two processes are still not integrated. There is no generic, unified model that allows both design and analysis information to be specified. In this paper, a feature-based CAD-CAE integration model is proposed to tackle the problem. The model comprises a hierarchy of CAD-CAE features such as part, wall, hole, rib, boss and treatment. The features are defined by their attributes and behaviours. With this model, information relating to both design and analysis can be specified and modified. The specified information from the design process is used to activate relevant CAE analysis routines, thus supporting integration from the CAD to the CAE process. If any of the specified design constraints is not satisfied from the CAE results, the initial model can be modified and the CAE analysis executed again. Hence, the model also supports integration from the CAE to the CAD process. A design case illustrates the bidirectional integration process.

A Tabu-enhanced genetic algorithm approach for assembly process planning

Over the past decade, much work has been done to optimize assembly process plans to improve productivity. Among them, genetic algorithms (GAs) are one of the most widely used techniques. Basically, GAs are optimization methodologies based on a direct analogy to Darwinian natural selection and genetics in biological systems. They can deal with complex product assembly planning. However, during the process, the neighborhood may converge too fast and limit the search to a local optimum prematurely. In a similar domain, Tabu search (TS) constitutes a meta-procedure that organizes and directs the operation of a search process. It is able to systematically impose and release constraints so as to permit the exploration of otherwise forbidden regions in a search space. This study attempts to combine the strengths of GAs and TS to realize a hybrid approach for optimal assembly process planning. More robust search behavior can possibly be obtained by incorporating the Tabu’s intensification and diversification strategies into GAs. The hybrid approach also takes into account assembly guidelines and assembly constraints in the derivation of near optimal assembly process plans. A case study on a cordless telephone assembly is used to demonstrate the approach. Results show that the assembly process plans obtained are superior to those derived by GA alone. The details of the hybrid approach and the case study are presented.

Automated functional design of engineering systems

This paper presents a prototype intelligent system, the knowledge-based functional design automation system (KBFDA) for automating the functional design process of engineering products/systems. An integrated knowledge representation scheme combines rule-based and object-oriented representation methods to represent functions and function related design characteristics in an intelligent design environment. A knowledge-based functional reasoning strategy uses this representation to automatically generate physical behaviors from desired functions or behaviors. The required behaviors are then combined in different configurations to develop a set of potential concept variants that meet the functional requirements and functional constraints given in a design specification. Finally, the variants are ranked according to the degree to which they meet non-functional constraints. The variant with the lowest rank (score) is selected as the best solution. A case study design of a terminal insertion unit is presented to demonstrate the practicality of the proposed approach.

Guiding functional design of mechanical products through rule-based causal behavioural reasoning

The paper presents a behaviour-driven functional (B-FES) modelling framework for functional design of mechanical products based on a rule-based causal behavioural reasoning step to guide the design process. A new representation scheme called rule-based behavioural representation (causal behavioural rules) was developed to facilitate causal behavioural reasoning, with which the interconnected physical behaviours can be reasoned out from a desired function. The behaviour schema was then used to select and arrange embodiments (abstractions of physical artefacts) to develop a set of potential concept variants. The proposed approach was not only useful in the creation of new configurations (combinations) from a library of standard physical behaviours, but also it might be used to generate specifications of new physical behaviours. A design case study of a terminal feeding unit is presented to demonstrate the practicality of the proposed approach.

RMINE: A Rough Set Based Data Mining Prototype for the Reasoning of Incomplete Data in Condition-based Fault Diagnosis

Condition-based fault diagnosis aims at identifying the root cause of a system malfunction from vast amount of condition-based monitoring information and knowledge. The needs of extracting knowledge from vast amount of information have spurred the interest in data mining, which can be categorized into two stages data preparation and knowledge extraction. It has been established that most of the current data mining approaches to fault diagnosis focus on the latter stage. In reality, condition-based monitoring data may, most of the time, contain incomplete, or missing data, which have an adverse effect on the knowledge or diagnostic rules extracted. Several approaches to deal with missing data can be found in literature. Unfortunately, all of which have serious drawbacks. In this paper, a novel approach to the treatment of incomplete data is proposed for the data preparation stage, while a rough set based approach has been developed to pre-process the data for the extraction of diagnostic rules. The two-stage data mining technique is implemented into a prototype system, RMINE, which also possesses a self-learning ability to cope with the changing condition-based data. A real industrial case study of a pump system is used to demonstrate the fault diagnosis process using RMINE. The result has shown the potential of RMINE as a general data mining prototype to condition-based fault diagnosis.

An Industrial Implementation of Computer-Aided Tolerance Charting

This paper argues that tolerance charting is not relevant for design tolerancing, but that it is an effective tool for process planning. It also argues that the tolerance charting algorithm based on rooted tree graphs, developed by the authors, provides a very general and powerful representation technique for tolerance charting. The technique is explained in detail to show how it can encompass all practical manufacturing processes that affect dimensions. A computer-based implementation of this technique, called CATCH, has been developed and is currently being used by a company in Singapore for process planning.

Development of an object-oriented blackboard model for stamping process planning in progressive die design

This paper reports preliminary work to investigate the suitability of using a blackboard framework as a problem-solving model for stamping process planning in progressive die design. The model is described at two levels: knowledge level and computational level. The knowledge level describes how the stamping process planning domain is represented in a blackboard architecture. The computational level describes how the blackboard architecture is modeled and implemented using object technology. A software prototype has been developed using CLIPS and C++ interfaced with Solid Edge CAD system. An example is presented to illustrate the feasibility and practicality of the proposed approach.

Graph theoretic algorithm for automatic operation sequencing for progressive die design

The paper presents a formal graph representation scheme for stamping operation sequencing for sheetmetal progressive dies and a graph theoretic method for automatic determination of the stamping operation sequence. Operation relations are represented by two graphs: an operation precedence graph and an adjacency graph. The first represents precedence constraints defined by best manufacturing practices. The second represents geometric infeasibility relations between operations. Each operation is a member of both graphs. The graphs are automatically generated from a set of stamping operations, which in turn are associated with stamping features of a part. The operation precedence graph is then verified to be acyclic using a coloured Depth First Search. Based on the operation precedence graph, a modified topological sort algorithm is applied to cluster the operations into partially ordered sets. Finally, a graph-colouring algorithm is applied to the operation adjacency graph on the partially ordered operation sets. The algorithm is implemented in C++ and is fully integrated with SolidWorks computer-aided design system. A case study is presented to illustrate the algorithm.

Design of a Feature-object-based Mechanical Assembly Library

AbstractIn this paper, a new feature-based assembly library for injection mould bases is presented. Assembly design feature-object modeling and configuration management are the key technologies developed. This library is an important functional module of QuickMould, which is a productivity software tool for plastic injection mould design. Interactions between the library and mould design processes are realized. This paper also covers the details about the design of the system and the realization of some major functions, with which, the process of traditional mould design is simplified and standardized. Consequently, the lead-time for plastic injection mould can be significantly shortened.