Surface quality control using biocomputational algorithms

The visual inspection of three-dimensional parts is one task within manufacturing that has been automated at a comparatively slow pace. Inspection is the process of determining if a product deviates from a given set of specifications. Inspection usually involves measurement of specific features of a part, such as assembly integrity, geometric dimensions and surface finish. A main goal of the Project NATHAN was to design and simulate the behaviour of a new generation of algorithms based on results in the discipline of biocomputing.     

Drawing curves onto a cloud of points for point-based modelling

Point-based geometric models are gaining popularity in both the computer graphics and CAD fields. A related design/modelling problem is the focus of the reported research: drawing curves onto digital surfaces represented by clouds of points. The problem is analyzed and solved, and a set of ‘design tools’ are proposed which allow the user/designer to efficiently perform ‘product development’ (alternative name: ‘detail design’) tasks which require efficient processing of a ‘digital surface’. The primary tool is a robust and efficient point projection algorithm combined with a smoothing technique for producing smooth ‘digital curves’ lying onto the cloud surface. The new design tools are tested on a real-life industrial example with very satisfactory results, which are thoroughly presented in the paper.     

Standardized data exchange of CAD models with design intent

Modern CAD systems generate feature-based product shape models with parameterization and constraints. Until recently, standards for CAD data exchange among different CAD systems were restricted to the exchange of pure shape information. These standards ignored the construction history, parameters, constraints, features and other elements of ‘design intent’ present in the model to be transferred. This paper suggests an implementational foundation for CAD data exchange with the preservation of design intent, based on the use of newly published parts of the International Standard ISO 10303 (STEP). Case studies are presented which employ a hypothetical STEP application protocol (AP) using Parts 55, 108 and 111 of ISO 10303. A prototype translator based on this AP has been implemented and tested. The paper reports on the experience gained in ‘intelligent’ data exchange.     

Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems

A new efficient optimization method, called ‘Teaching–Learning-Based Optimization (TLBO)’, is proposed in this paper for the optimization of mechanical design problems. This method works on the effect of influence of a teacher on learners. Like other nature-inspired algorithms, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. The population is considered as a group of learners or a class of learners. The process of TLBO is divided into two parts: the first part consists of the ‘Teacher Phase’ and the second part consists of the ‘Learner Phase’. ‘Teacher Phase’ means learning from the teacher and ‘Learner Phase’ means learning by the interaction between learners. The basic philosophy of the TLBO method is explained in detail. To check the effectiveness of the method it is tested on five different constrained benchmark test functions with different characteristics, four different benchmark mechanical design problems and six mechanical design optimization problems which have real world applications. The effectiveness of the TLBO method is compared with the other population-based optimization algorithms based on the best solution, average solution, convergence rate and computational effort. Results show that TLBO is more effective and efficient than the other optimization methods for the mechanical design optimization problems considered. This novel optimization method can be easily extended to other engineering design optimization problems.     

A computational model of time for stiff hybrid systems applied to control synthesis

Computation has quickly become of paramount importance in the design of engineered systems, both to support their features as well as their design. Tool support for high-level modeling formalisms has endowed design specifications with executable semantics. Such specifications typically include not only discrete-time and discrete-event behavior, but also continuous-time behavior that is stiff from a numerical integration perspective. The resulting stiff hybrid dynamic systems necessitate variable-step solvers to simulate the continuous-time behavior as well as solver algorithms for the simulation of discrete-time and discrete-event behavior. The combined solvers rely on complex computer code which makes it difficult to directly solve design tasks with the executable specifications. To further leverage the executable specifications in design, this work aims to formalize the semantics of stiff hybrid dynamic systems at a declarative level by removing implementation detail and only retaining ‘what’ the computer code does and not ‘how’ it does it. A stream-based approach is adopted to formalize variable-step solver semantics and to establish a computational model of time that supports discrete-time and discrete-event behavior. The corresponding declarative formalization is amenable to computational methods and it is shown how model checking can automatically generate, or synthesize, a feedforward control strategy for a stiff hybrid dynamic system. Specifically, a stamper in a surface mount device is controlled to maintain a low acceleration of the stamped component for a prescribed minimum duration of time.     

A general model for machinable features and its application to machinability evaluation of mechanical parts

This paper is intended to reveal the rationale in the machinability evaluation and to present an effective, systematic approach to the assessment of the machined parts in the early stage of design. By examining the inherent shaping mechanism of machining processes, a geometric feature model, termed ‘machining volume’, resulting from the cutter's movement that mimics the cutter's real motion trajectory in machining, is proposed with which a set of feature derivatives can be affiliated. The geometric and topological patterns of machining volume permit to capture and convey machinability constraints on a part shape, leading to a new, simple machinability evaluation method centered on machining volume. This method is dedicated to two kinds of inspection on the geometry of a part in design: one is to search for unmachinable surfaces that are beyond the capability of machining processes, and the other to detect machining interference between a cutter and a part. It shows a more useful means to characterize machinable features that result in the machinability evaluation with ease and efficiency.     

Generic programming in 3D

Support for generic programming consists of three essential ingredients: support for overloaded functions, a run-time type representation, and a generic view on data. Different approaches to datatype-generic programming occupy different points in this design space. In this article, we revisit the “Scrap your boilerplate” approach and identify its location within the three-dimensional design space. The characteristic features of “Scrap your boilerplate” are its two generic views, the ‘spine’ view for consuming and transforming data, and the ‘type-spine’ view for producing data. We show how to combine these views with different overloading mechanisms and type representations.     

An effectiveness-based adaptive cache replacement policy

Belady’s optimal cache replacement policy is an algorithm to work out the theoretical minimum number of cache misses, but the rationale behind it was too simple. In this work, we revisit the essential function of caches to develop an underlying analytical model. We argue that frequency and recency are the only two affordable attributes of cache history that can be leveraged to predict a good replacement. Based on those two properties, we propose a novel replacement policy, the Effectiveness-Based Replacement policy (EBR) and a refinement, Dynamic EBR (D-EBR), which combines measures of recency and frequency to form a rank sequence inside each set and evict blocks with lowest rank. To evaluate our design, we simulated all 30 applications from SPEC CPU2006 for uni-core system and a set of combinations for 4-core systems, for different cache sizes. The results show that EBR achieves an average miss rate reduction of 12.4%. With the help of D-EBR, we can tune the weight ratio between ‘frequency’ and ‘recency’ dynamically. D-EBR can nearly double the miss reduction achieved by EBR alone. In terms of hardware overhead, EBR requires half the hardware overhead of real LRU and even compared with Pseudo LRU the overhead is modest.     

Applying social bookmarking to collective information searching (CIS): An analysis of behavioral pattern and peer interaction for co-exploring quality online resources

With the advancement of Web 2.0 applications, this study aims to advocate that social bookmarking (SB) applications could support mutual exchange of finding information in a manner of collective information searching (CIS). A social bookmarking system, namely ‘WeShare,’ was developed, and conducted with 127 junior high school students for performing the given assignment in this study. The participants’ activities of collecting and reviewing relevant information were traced by log data for later analysis. To initially unveil the participants’ behaviors in the use of social bookmarking for co-exploring the Internet resources, this study proposed some quantitative indicators to represent students’ personal contributions (‘Bookmarks from the Internet,’ ‘Bookmarks from WeShare,’ ‘Annotations on personal bookmarks,’ ‘Comments on others’ bookmarks’) and peer feedback (‘The number of bookmarks collected by peers,’ ‘The number of bookmarks commented on by peers,’ ‘The number of comments from peers’). By the method of cluster analysis, some behavioral patterns regarding how participants collectively search the Internet by use of WeShare were identified. Furthermore, the findings suggest that personal contributions to citing and commenting on peers’ bookmarks are important to the advancement of collective information searching activities for finding quality information on the Internet.     

Model analysis and performance analysis of two industrial MPCs

This paper presents two case studies on the performance evaluation and model validation of two industrial multivariate model predictive control (MPC) based controllers: (1) a 7-output, 3-input MPC with three measured disturbance variables for controlling a part of kerosene hydrotreating unit (KHU) and (2) a 8-output, 4-input MPC with five measured disturbances for controlling a part of naphtha hydrotreating unit (NHU). The first case study focuses on potential limits to control performance due to constraints and limits set at the time of controller commissioning. The root causes of sub-optimal performance of KHU are successfully isolated. Data from the NHU unit with MPC ‘on’ and with MPC ‘off’ are analyzed to obtain and compare several different measures of multivariate controller performance. Model quality assessment for the two MPCs are performed. A new model index is proposed to have a measure of simulation ability and prediction ability of a model. Closed-loop identification of KHU and closed-loop identification of NHU are conducted using the asymptotic method (ASYM) proposed by Zhu (1998).     

Developing Web-based assessment strategies for facilitating junior high school students to perform self-regulated learning in an e-Learning environment

This research refers to the self-regulated learning strategies proposed by Pintrich (1999) in developing a multiple-choice Web-based assessment system, the Peer-Driven Assessment Module of the Web-based Assessment and Test Analysis system (PDA-WATA). The major purpose of PDA-WATA is to facilitate learner use of self-regulatory learning behaviors to perform self-regulated learning and in turn improve e-Learning effectiveness. PDA-WATA includes five main strategies: ‘Adding Answer Notes,’ ‘Stating Confidence,’ ‘Reading Peer Answer Notes,’ ‘Recommending Peer Answer Notes’ and ‘Querying Peers’ Recommendation on Personal Answer Notes’. Using these strategies, examinees are allowed to add answer notes to explain why they chose a certain option as the correct answer and state their confidence in their own answer and answer notes, for peers’ reference. In addition to reading peer answer notes, examinees can also recommend peer answer notes as valuable references. The recommendation information can also be queried by all examinees. Quasi-experimental design was adopted to understand the effectiveness of PDA-WATA in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving learner e-Learning effectiveness. Participants were 123 seventh-grade junior high school students from four classes. These four classes were randomly divided into the PDA-WATA group (n = 63) and the N-WBT group (n = 60). Before e-Learning instruction, all students took the pre-test of the Learning Process Inventory (LPI), used to understand how often learners use self-regulatory learning behaviors in the learning process, and the pre-test of the summative assessment. After a two-week e-Learning instruction, the students all took the post-test of the LPI and the summative assessment. Results indicate that students in the PDA-WATA group appear to be more willing to take the Web-based formative assessment than students in the N-WBT group. In addition, PDA-WATA appears to be significantly more effective than N-WBT in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving their e-Learning effectiveness. Moreover, this research also finds that in the PDA-WATA group, there is no significant difference between the learning effectiveness of students with a low level of self-regulated learning and students with a high level of self-regulated learning, but similar result cannot be found in the N-WBT group.     

A customer-oriented organisational diagnostic model based on data mining of customer-complaint databases

The purpose of this paper is to develop a customer-oriented organisational diagnostic model, ‘PARA’ model, based on data mining of customer-complaint databases. The proposed ‘PARA’ model, which is designed to diagnose and correct service failures, takes its name from the initial letters of the four analytical stages of the model: (i) ‘primary diagnosis’; (ii) ‘advanced diagnosis’; (iii) ‘review’; and (iv) ‘action’. In the primary-diagnosis stage, the customer-complaint database is comprehensively analysed to identify themes and categories of complaints. In the advanced-diagnosis stage, a data-mining technique is employed to investigate the relationship between the categories of customer complaints and the deficiencies of the service system. In the review stage, the identified weaknesses of the service system are reviewed and awareness of these weaknesses is enhanced among the organisation’s employees. In the action stage, a strategy of action plans for improvement is developed. An empirical case study is conducted to demonstrate the practical efficacy of the ‘PARA’ model. The paper concludes by summarising the advantages of the proposed model and the implications for future research.     

Gaming addiction,definition and measurement: A large-scale empirical study

Although the general public appears to have embraced the term ‘videogame addiction’, the scientific debate as to whether ‘gaming addiction’ can actually be considered an addiction similar to substance addictions of DSM-IV is still unsettled. To date, research on gaming addiction has focused on problematic behavior from the gaming activity itself and there has been little empirical research related to pathological personality patterns that usually are associated with substance addictions. Therefore, the current study examined how game exposure and ‘problematic gaming behavior’ are related to personality patterns associated with addiction by means of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). A large-scale survey study was performed among 1004 adolescent boys (age-range 11–18, M = 14.18, SD = 1.36) measuring problematic gaming behavior, physical game-related symptoms, gaming behavior and three MMPI-2 subscales measuring personality patterns usually associated with substance addiction (MAC-R, APS, AAS). Results showed that problematic gaming and physical symptoms were positively related to all MMPI-2 subscales, while game exposure was not related to the indirect measures of addictive personality patterns (i.e., MAC-R, APS). Thus, problematic gaming should be clearly distinguished from high game exposure. High game exposure merely indicates enthusiasm for some although it may be psychopathological for others.     

Qualitative reachability in stochastic BPA games

We consider a class of infinite-state stochastic games generated by stateless pushdown automata (or, equivalently, 1-exit recursive state machines), where the winning objective is specified by a regular set of target configurations and a qualitative probability constraint ‘>0’ or ‘=1’. The goal of one player is to maximize the probability of reaching the target set so that the constraint is satisfied, while the other player aims at the opposite. We show that the winner in such games can be determined in P for the ‘>0’ constraint, and in NP∩co-NP for the ‘=1’ constraint. Further, we prove that the winning regions for both players are regular, and we design algorithms which compute the associated finite-state automata. Finally, we show that winning strategies can be synthesized effectively.     

RelaxMCD: Smooth optimisation for the Minimum Covariance Determinant estimator

The Minimum Covariance Determinant (MCD) estimator is a highly robust procedure for estimating the centre and shape of a high dimensional data set. It consists of determining a subsample of h points out of n which minimises the generalised variance. By definition, the computation of this estimator gives rise to a combinatorial optimisation problem, for which several approximate algorithms have been developed. Some of these approximations are quite powerful, but they do not take advantage of any smoothness in the objective function. Recently, in a general framework, an approach transforming any discrete and high dimensional combinatorial problem of this type into a continuous and low-dimensional one has been developed and a general algorithm to solve the transformed problem has been designed. The idea is to build on that general algorithm in order to take into account particular features of the MCD methodology. More specifically, two main goals are considered: (a) adaptation of the algorithm to the specific MCD target function and (b) comparison of this ‘tuned’ algorithm with the usual competitors for computing MCD. The adaptation focuses on the design of ‘clever’ starting points in order to systematically investigate the search domain. Accordingly, a new and surprisingly efficient procedure based on a suitably equivariant modification of the well-known k-means algorithm is constructed. The adapted algorithm, called RelaxMCD, is then compared by means of simulations with FASTMCD and the Feasible Subset Algorithm, both benchmark algorithms for computing MCD. As a by-product, it is shown that RelaxMCD is a general technique encompassing the two others, yielding insight into their overall good performance.     

CAD tools for aesthetic engineering

The role of computers and of computer-aided design tools for the creation of geometrical shapes that will be judged primarily by aesthetic considerations is reviewed. Examples are the procedural generation of abstract geometrical sculpture or the shape optimization of constrained curves and surfaces with some global ‘cost’ functional. Different possibilities for such ‘beauty functionals’ are discussed. Moreover, rapid prototyping tools based on layered manufacturing now add a new dimension to the visualization of emerging designs. Finally, true interactivity of the CAD tools allows a more effective exploration of larger parts of the design space and can thereby result in an actual amplification of the creative process.     

An approach to competitive product line design using conjoint data

In today’s highly competitive environment, where market oriented firms aim to maximize profits through customer satisfaction, there is an increasing need to design a product line, rather than a single product. The main goal of designing a profit maximizing product line is to target the ‘right product’ to the ‘right customer’. Although conjoint analysis has turned out to be one of the most widely used techniques for product line design, it falls to explicitly consider retaliatory reactions from competitors. In this paper, we propose a new conjoint-based approach to competitive new product line design, employing the Nash equilibrium concept. The optimal product line design problem for each firm is formulated as a nonlinear integer programming problem. In the absence of a closed-form solution, to compute the Nash equilibrium and to determine the optimal product line, we propose a two-phase procedure: a sequential iterative procedure in the first phase, and backward induction in the second. To solve the optimization problem in each of the iterations of the sequential procedure, we used the branch-and-bound method. The proposed approach is illustrated under several scenarios of competition using previously published conjoint data.