Siti Zawiah Md Dawal

A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes

Global economic competition has spurred the manufacturing sector to improve and invest in modern equipment to satisfy the needs of the market. In particular, machine tool selection is the most important problem; it plays a primary role in the improvement of productivity and flexibility in the manufacturing environment and involves the imprecise, vague and uncertain information. This paper presents the hybrid approach of the fuzzy ANP (Analytic Network Process) and COPRAS-G (COmplex PRoportional ASsessment of alternatives with Grey relations) for fuzzy multi-attribute decision-making in evaluating machine tools with consideration of the interactions of the attributes. The fuzzy ANP is used to handle the imprecise, vague and uncertain information from expert judgments and model the interaction, feedback relationships and interdependence among the attributes to determine the weights of the attributes. COPRAS-G is employed to present the preference ratio of the alternatives in interval values with respect to each attribute and calculate the weighted priorities of the machine alternatives. Alternatives are ranked in ascending order by priority. As a demonstration of the proposed model, a numerical example is implemented based on the collected data and the literature. The result is then compared with the rankings provided by other methods such as TOPSIS-G, SAW-G and GRA. Moreover, a sensitivity analysis is conducted to verify the robustness of the ranking. The result highlights that the hybrid approach of the fuzzy ANP and COPRAS-G is a highly flexible tool and reaches an effective decision in machine tool selection.

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

The Effect of Job and Environmental Factors on Job Satisfaction in Automotive Industries

A methodology was developed for diagnosing industrial work, which includes questionnaire, observation, measurements, data collection and statistical analysis. A survey was conducted to investigate the relationship between job satisfaction and factors that affect work design in 2 automotives manufacturing companies in Malaysia. A basic work design model was proposed. The aim of this model was to determine the factors that influence employees’ perception towards their work. A set of multiple-choice questionnaires was developed and data was collected by interviewing employees at a production plant. The survey focused on job and environmental factors. The results supported the proposed model and showed that job and environmental factors were significantly related to job satisfaction. They highlighted the significant influence of age, work experience and marital status on job satisfaction. Further, environmental factors, especially the surroundings, context dependence and the building’s function, also had a significant impact on job satisfaction.

Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling

We build a novel model of the developed distributing scheduling by supplementing the reentrant characteristic into the model of distributed reentrant permutation flow shop scheduling (DRPFS).We determine the number of factory needs to use, factory assignment and sequence of job assigned to the factory.A novel multi-objective adaptive large neighborhood search (MOALNS) algorithm is developed.The various destroy and repair operators are presented. Factory management plays an important role in improving the productivity and quality of service in the production process. In particular, the distributed permutation flow shop scheduling problem with multiple factories is considered a priority factor in the factory automation. This study proposes a novel model of the developed distributed scheduling by supplementing the reentrant characteristic into the model of distributed reentrant permutation flow shop (DRPFS) scheduling. This problem is described as a given set of jobs with a number of reentrant layers is processed in the factories, which compromises a set of machines, with the same properties. The aim of the study is to determine the number of factory needs to be used, jobs assignment to certain factory and sequence of job assigned to the factory in order to simultaneously satisfy three objectives of minimizing makespan, total cost and average tardiness. To do this, a novel multi-objective adaptive large neighborhood search (MOALNS) algorithm is developed for finding the near optimal solutions based on the Pareto front. Various destroy and repair operators are presented to balance between intensification and diversification of searching process. The numerical examples of computational experiments are carried out to validate the proposed model. The analytical results on the performance of proposed algorithm are checked and compared with the existing methods to validate the effectiveness and robustness of the proposed potential algorithm in handling the DRPFS problem.

Virtual reality based support system for layout planning and programming of an industrial robotic work cell.

Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.

Analysis and experiment of centrifugal force for microfluidic ELISA CD platform

This paper presents an analysis and experiment of centrifugal force for microfluidic Enzyme-Linked Immunosorbent Assay (ELISA) on a compact-disc (CD) platform. The ELISA CD was designed based on the centrifugal force as a driving force while capillary force acts as preventing barrier. The CD composed of 2 layers: the substrate layer is made of PMMA and the top layer is laminated with an Adhesive Sealing Films (ASF) or thermal seal. The PMMA substrate was fabricated by CNC micromachining. The ELISA CD consists of 7 reservoirs: waste, detection, serum, conjugate, washing solution, substrate and stopping solution. In the experiment, the reservoirs were filled with colour liquid and the fluid flow behaviour of the liquid in the CD was studied and monitored by a customized CD spin stand system equipped with visualization system. The experimental test results show an average of 9% error when compared with the theoretical calculation of burst frequency for all the reservoirs.

Capacitive interfacing for MEMS humidity and accelerometer sensors

This paper presents a study on the design issues of the electronic interfacing circuit for MEMS humidity and accelerometer sensors. The study focuses on capacitive sensing method as its one of the most important and widely used techniques in interfacing the micro sensors. Some of capacitive sensing techniques are reviewed and appropriate read out interfacing circuit for humidity and accelerometer sensors were chosen depends on their sensing capacitance magnitude. The Hartley oscillator circuit is proposed to interface the MEMS humidity sensor which is its capacitance is in the range of 180–500pF (G.Nagy, 2007) depending on the relative humidity values. The feedback circuit of Hartley Oscillator is designed at 998.473 kHz of resonant frequency with 167.09 degree of phase shift. At this particular frequency, the maximum gain achieved at about 11dB. To ensure the oscillation begins, the amplifier with 13dB of gain is connected to the feedback circuit. The result of the oscillator circuit, which is based on capacitance to frequency converter are generally 5- 15% of calculated results. Chopper stabilization sensing circuit is chosen for interfacing MEMS accelerometer sensor. This sensor was based on an acceleration sensing capacitor which is the displacement of the moving electrode results in a change in the capacitance. The chopper stabilization results the proportional output voltage to capacitance changes for a very small sensing capacitance magnitude which is less than 1pF. (G.Nagy, 2007).These two interfacing read out electronics circuit was simulated by using National Instrument Multisim 10.1 software. The results from both simulation shows that the capacitive interfacing circuits are suitable for each sensor application.

An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness

The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts’ uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

The effects of energy expenditure rate on work productivity performance at different levels of production standard time.

[Purpose] The purpose of this study was to investigate the effects of energy expenditure rate on work productivity performance at different levels of production standard time. [Subjects and Methods] Twenty industrial workers performed repetitive tasks at three different levels of production standard time, normal, hard, and very hard. Work productivity and energy expenditure rate were recorded during the experimental tasks. [Results] The work productivity target was not attainable for the hard and very hard production standard times. This was attributed to the energy expenditure rate, which increased as the level of production standard time became harder. The percentage change in energy expenditure rate for the very hard level (32.5%) relative to the normal level was twice that of the hard level (15.5%), indicating a higher risk of work-related musculoskeletal disorders for the harder production standard time. The energy expenditure rate for the very hard production standard time (1.36 kcal/min) was found to exceed the maximum energy expenditure rate recommended for light repetitive tasks involving both arms (1.2 kcal/min). [Conclusion] The present study shows that working with an energy expenditure rate that is either equal to or above the maximum energy expenditure rate of the tasks results in decreased work productivity performance due to the onset of physical fatigue and a higher risks of work-related musculoskeletal disorders.

Anthropometric Database for the Learning Environment of High School and University Students

Abstract This paper presents an anthropometric database of high school and university students from Kuala Lumpur, Malaysia. Forty-one high school participants (21 males and 20 females), 13–17 years old, and 143 university students (74 males and 69 females) took part in the study. Twenty-one static body dimensions were measured. The greatest mean differences in the anthropometric data between male and female high school students were found in the sitting elbow height. In addition, a comparison of anthropometric data of male and female university students showed that data for males and females were significantly different, except for buttock–popliteal length, sitting elbow height and thigh clearance. The primary aim of this study was to develop an anthropo-metric database that could be used as a primary reference in designing products, devices and equipment for ergonomic learning environments.