Tang Sai Hong

Development of a new minimum avoidance system for a behavior-based mobile robot

A new fuzzy logic algorithm is developed for mobile robot navigation in local environments. A Pioneer robot perceives its environment through an array of eight sonar sensors and self positioning-localization sensors. While the fuzzy logic body of the algorithm performs the main tasks of obstacle avoidance and target seeking, an actual-virtual target switching strategy resolves the problem of limit cycles in any type of dead-ends encountered on the way to the target. This is an advantage beyond pure fuzzy logic approach and common virtual target techniques. In this work, multiple traps may have any shape or arrangement from barriers forming simple corners and U-shape dead-ends to loops, maze, snail shape, and other complicated shapes. Robot trajectories are demonstrated by simulation work and compared with results from other related methods to prove the robustness of this method.

Development of genetic fuzzy logic controllers for complex production systems

Complex production systems can produce more than one part type. For these systems, production rate and priority of production for each part type is determined by production controllers. In this paper, genetic fuzzy logic control (GFLC) methodology is used to develop two production control architectures namely genetic distributed fuzzy (GDF), and genetic supervisory fuzzy (GSF) controllers. Previously these controllers have been applied to single-part-type production systems. In the new approach the GDF and GSF controllers are developed to control complex production systems. The methodology is illustrated and evaluated using two test cases; two-part-type production line and re-entrant production systems. Genetic algorithm is used to tune the membership functions of input variables of GSF or GDF controllers. The objective function of the GSF controller minimizes the production cost based on work-in-process (WIP) and backlog costs, while surplus minimization is considered by GDF controller. The results show that GDF and GSF controllers can improve the performance of production systems. GSF controllers decrease the WIP level and its variations. GDF controllers show their abilities in reducing the backlog level but generally, production cost for GDF controller is greater than GSF controller.

IT investments and business performance improvement: the mediating role of lean manufacturing implementation

The main purpose of this study is to examine whether the application of current information technology (IT) and different principles of lean manufacturing (LM) are interdependent and complimentary or they are mutually exclusive. This study draws on the so-called IT-enabled organisational capabilities perspective to study the relationships between IT, LM and business performance improvement. Using a questionnaire-based survey, the data come from 231 leading Iranian and Malaysian auto-part manufacturers. The findings suggest that LM and IT are mutually interdependent and value of IT investments can be effectively transformed into business performance improvement for auto-part manufacturers through the higher levels of lean manufacturing system (LMS) implementation. Advanced manufacturing technology (AMT) competency is a valuable intermediate capability which links IT investments into LMS implementation. It was found that IT investment is one of the minimum requirements of LMS implementation for surveyed business, and the value of IT investment is truly transformed to LMS implementation when IT investments offer competent administrative AMTs to effectively manage all production processes. Findings also recommend that managers should avoid isolating the performance metrics only on areas such as net financial measures, while assessing the business value of IT and LM.

A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem

Technology progress is a cause of industrial hazardous wastes increasing in the whole world . Management of hazardous waste is a significant issue due to the imposed risk on environment and human life. This risk can be a result of location of undesirable facilities and also routing hazardous waste. In this paper a biobjective mixed integer programing model for location-routing industrial hazardous waste with two objectives is developed. First objective is total cost minimization including transportation cost, operation cost, initial investment cost, and cost saving from selling recycled waste. Second objective is minimization of transportation risk. Risk of population exposure within bandwidth along route is used to measure transportation risk. This model can help decision makers to locate treatment, recycling, and disposal centers simultaneously and also to route waste between these facilities considering risk and cost criteria. The results of the solved problem prove conflict between two objectives. Hence, it is possible to decrease the cost value by marginally increasing the transportation risk value and vice versa. A weighted sum method is utilized to combine two objectives function into one objective function. To solve the problem GAMS software with CPLEX solver is used. The problem is applied in Markazi province in Iran.

IT investments and product development effectiveness: Iranian SBs

– The purpose of this paper is to examine if, and how, investments in IT at different levels can create new product development (NPD) capabilities in terms of IT leveraging competence in NPD and NPD effectiveness. The paper also investigates how Iranian small businesses (SBs) can achieve desired marketing performance through developing these capabilities., – The paper is consistent with the perspective on IT‐enabled organizational capabilities. A questionnaire‐based survey was conducted to collect data from 218 businesses or NPD managers of SBs in Iran., – IT leveraging competence in NPD and NPD effectiveness are valuable key capabilities that transform the value of IT resources to a firms performance for Iranian SBs. Investments in both technical and human IT resources have positive effects on the development of NPD capabilities, and thus performance in the surveyed SBs., – Among other limitations, relying on a small sample size and cross‐sectional data of this research, and lack of generalizability of findings tend to have certain limitations., – The results suggest that the investments in both technical and human IT resources increase firms ability to develop effectiveness in NPD. However, IT investments strategy should be aligned with effective use of IT functionalities, as the effect of IT leveraging competence in development of NPD effectiveness is more pronounced. Second, IT leveraging competence in NPD and NPD effectiveness are important intermediate organizational capabilities through which the benefits of both technical and human IT resources are converted into performance effects at the firm level for Iranian SBs., – This case study explores how Iranian SBs can develop NPD capabilities, and subsequently, marketing performance, a topic that has received little attention to date.

Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process

Tool path optimization in today’s manufacturing systems is one of the crucial issues in holes-making machining. This paper presents an evolutionary optimization algorithm based on geographic distribution of biological organism to deal with hole-making process problem. The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. The aim of this study is to minimise the non-productive time, including tool travelling time and tool switching time, by employing biogeography based optimization algorithm, since the problem is considered as NP-hard. The performance of proposed algorithm is evaluated based on various test problems adopted from the literature. The obtained results demonstrate that the proposed algorithm can efficiently improve the solution quality in terms of minimising non-productive time.

A STATISTICAL MODEL FOR EXPECTED CYCLE TIME OF SP-AS/RS: AN APPLICATION OF MONTE CARLO SIMULATION

The elimination of international trade barriers, lower tariffs, and shifting centers of global manufacturing and consumption leads to new dynamics in intermodal shipping. Advanced technologies, and in particular, automated storage/retrieval systems (AS/RSs) for designing high-capacity automated container terminals, have been recently proposed as possible candidates for improving the terminals efficiency and meeting the challenges of the future in marine transportation. In this article, the authors present an analytical statistical model for computing expected cycle time of split-platform AS/RS (SP-AS/RS), in order to reduce average handling time of this system. The accuracy of the proposed statistical model is validated by Monte Carlo simulation. The results show that the analytical model is reliable for the design and analysis of the SP-AS/RS.

Measuring process capability index Cpmk with fuzzy data and compare it with other fuzzy process capability indices

The index Cpmk is a well-known loss-based process capability index. It can reveal more information about the location of the process mean compared with other classic process capability indices. This index is also more sensitive than other capability indices to any deviations from process mean. When there are some uncertainties in observations, fuzzy logic can be employed to manage these uncertainties. There is some research on different fuzzy process capability indices and this paper is an extension of Tsai and Chen (2006), Chen, Lin, and Chen (2003) for the process capability index Cpmk of fuzzy numbers. In order to find the membership function of process capability index Cpmk, the α-cuts of the fuzzy observation were employed. An example of fuzzy process capability Cpmk calculator was illustrated and compared with other classic fuzzy process capability indices C ~ p , C ~ pl , C ~ pu , C ~ pk and C ~ pm . Results showed that fuzzy C ~ pmk has the advantages of both C ~ pk and C ~ pm . Since the index Cpmk is a more sensitive index compared with other classic indices, the fuzzy process capability index C ~ pmk can be a more sensitive fuzzy index compared with C ~ p , C ~ pl , C ~ pu , C ~ pk and C ~ pm .

Analysis of household electricity consumption behaviours

Adoption of renewable electricity generation technologies such as photovoltaic (PV) systems is at the early majority stage in most developed countries. Depending on solar capacity, applied feed-in tariff, and other factors, households exhibit different electricity consumption behaviours which can potentially assist in Demand Side Management (DSM) of electricity usage. This article presents three univariate analysis methods to infer deliberative behavioural patterns at households with solar electricity generation capacity. Analysis methods include qualitative Principal Component Analysis (PCA), unsupervised Hebbian-based clustering, and clustering using a semi-supervised Self-Organising Map (SOM). The techniques are individually applied to 300 sample households with rooftop PV panels operating under a Gross Metering (GM) scheme. According to the PCA, the dominant behaviours are often general among most households, and therefore reveal themselves on first and second principal components. However, on the third and fourth components some specific household behaviours related to load-shifting and self-consumption, are observed. The Hebbian model differentiates between at least eight behaviour types, some of which indicate deliberative behaviours by the households. Most effectively, SOM clustering clearly detects a self-consumption behaviour attributed to domestic electricity generation. A control group of 400 households is analysed to ensure uniqueness of the self-consumption behaviour to customers with solar PV installed. The techniques developed herein may be able to be used by electricity utilities to assess the influence that future tariff and technology offerings will have on behavioural aspects of customer electricity consumption.

Business-to-Business Electronic Commerce Success: A Supply Network Perspective

DeLone and McLean (2004) have advanced an electronic commerce (EC) success model and suggest that it can be extended to investigating EC success in different contexts. However, the EC success model has not been empirically validated in the context of business-to-business (B2B) EC. The purpose of this study is to gain a better understanding of EC value and success within the B2B environment. Accordingly, we introduce an extended version of DeLone and McLean’s (2004) EC success model, and test hypotheses regarding the associations between various success dimensions using the data collected from 122 supply chain units. In addition to providing support for most of the hypotheses suggested by DeLone and McLean’s (2004) EC success model, our results indicate that other success dimensions, such as EC readiness, must be considered for successful EC in B2B environments. The research findings provide practitioners with clarity on the levers of B2B e-commerce success within the supply chain unit level of analysis. Overall, the study’s results contribute to theoretical development in the area of business value creation and EC success, and present a basis for further research in these fields.