Raja Ariffin Raja Ghazilla

The impact of sustainable manufacturing practices on sustainability performance: Empirical evidence from Malaysia

Sustainable manufacturing practices are one of the significant environmental initiatives taken by manufacturing industries to preserve the environment and improve the quality of human life while performing manufacturing activities. The emergence of the value creation concept, economic value no longer counts as a single factor for measuring manufacturing performance. Within the sustainability context, the impact of manufacturing activities on the environmental and social aspects should be taken into account as the basis for assessing manufacturing performance, which is called sustainability performance. The purpose of this paper is to examine the relationship of sustainable manufacturing practices with sustainability performance, which considers the environmental, economic and social aspects.,A questionnaire survey is carried out among 443 ISO 14001 certified manufacturing companies in Malaysia. Structural equation modelling is used to evaluate the relationship of sustainable manufacturing practices with sustainability performance.,The findings of this study indicate that manufacturing process is the manufacturing stage that gives the most impact on the improvement of sustainability performance. Hence, it is concluded that manufacturing companies in Malaysia are highly focussed on the production bound when implementing sustainable manufacturing practices.,Although this study indicates a good estimation of the proposed model, additional variables might be added to improve the prediction strength of the proposed model such as considering type of industries, economic scale or ownership. Adding the comparison of sustainable manufacturing practices between different countries also a valuable research to investigated.,The framework proposed here can also assist manufacturing industries to conduct sustainability assessments by providing elements of sustainability performance and can serve as a guideline to select appropriate sustainable manufacturing practices and to what level the practices need to be improved to leverage companies’ sustainability performance.,The framework proposed here can also assist manufacturing industries to conduct sustainability assessments by providing elements of sustainability performance and can serve as a guideline to select appropriate sustainable manufacturing practices and to what level the practices need to be improved to leverage companies’ sustainability performance.

Development of a fuzzy economic order quantity model for imperfect quality items using the learning effect on fuzzy parameters

This paper develops an inventory model for items with imperfect quality in a fuzzy environment by assuming that learning occurs in setting the fuzzy parameters. This implies that inventory planners collect information about the inventory system and build up knowledge from previous shipments, and thus learning process occurs in estimating the fuzzy parameters. So, it is hypothesized that the fuzziness associated with all fuzzy inventory parameters is reduced with the help of the knowledge acquired by the inventory planners. In doing so, the study developed a total profit function with fuzzy parameter, where triangular fuzzy number is used to quantify the fuzziness of the parameters. Next, the learning curve is incorporated into the fuzzy model to account for the learning in fuzziness. Subsequently, the optimal policy, including the batch size and the total profit are derived using the classical approach. Finally, numerical examples and a comparison among the fuzzy learning, fuzzy and crisp cases are provided to highlight the importance of using learning in fuzzy model.

A fuzzy EOQ model with backorders and forgetting effect on fuzzy parameters

This paper considers a fuzzy lot-sizing problem with forgetting effect.A new fuzzy EOQ model with backorders and forgetting is developed.The result suggests decreasing the maximum inventory and the total inventory cost. The study of learning effect on inventory models with imprecise parameters is a research topic that has recently emerged. The research papers have published so far studied this aspect from a theoretical point of view and thus the literature lacks the investigation of this topic from a practical standpoint. To close this research gap, we conducted a semi-structured interview with a number of industry experts to gain insights into the prevalence of learning and forgetting in real applications. Based on the insights gained from the interviews, we have developed a recently published model by countering the assumption of full transfer of learning. The model developed herein proposes a situation where the knowledge gained by the operator in setting imprecise parameters deteriorates over the planning cycles due to intermittent planning process. A numerical study suggests that accounting for the effect of knowledge depreciation/forgetting on imprecise parameters leads to reduction in maximum inventory, which consequently reduces the total cost of the system.

A fuzzy controller for lower limb exoskeletons during sit-to-stand and stand-to-sit movement using wearable sensors

Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research, a fuzzy based control algorithm is proposed for lower limb exoskeletons during sit-to-stand and stand-to-sit movements. Surface electromyograms (EMGs) are acquired from the vastus lateralis muscle using a wearable EMG sensor. The resultant acceleration angle along the z-axis is determined from a kinematics sensor. Twenty volunteers were chosen to perform the experiments. The whole experiment was accomplished in two phases. In the first phase, acceleration angles and EMG data were acquired from the volunteers during both sit-to-stand and stand-to-sit motions. During sit-to-stand movements, the average acceleration angle at activation was 11° – 48° and the EMG varied from −0.19 mV to +0.19 mV. On the other hand, during stand-to-sit movements, the average acceleration angle was found to be 57.5°–108° at the activation point and the EMG varied from −0.32 mV to +0.32 mV. In the second phase, a fuzzy controller was designed from the experimental data. The controller was tested and validated with both offline and real time data using LabVIEW.

Application of the NSGA-II algorithm to a multi-period inventory-redundancy allocation problem in a series-parallel system

In this paper, we formulate a mixed-integer binary non-linear programming model to study a series-parallel multi-component multi-periodic inventory-redundancy allocation problem (IRAP). This IRAP is a novel redundancy allocation problem (RAP) because components (products) are purchased under an all unit discount (AUD) policy and then installed on a series-parallel system. The total budget available for purchasing the components, the storage space, the vehicle capacities, and the total weight of the system are limited. Moreover, a penalty function is used to penalize infeasible solutions, generated randomly. The overall goal is to find the optimal number of the components purchased for each subsystem so that the total costs including ordering cost, holding costs, and purchasing cost are minimized while the system reliability is maximized, simultaneously. A non-dominated sorting genetic algorithm-II (NSGA-II), a multi-objective particle swarm optimization (MOPSO), and a multi-objective harmony search (MOHS) algorithm are applied to obtain the optimal Pareto solutions. While no benchmark is available in the literature, some numerical examples are generated randomly to evaluate the results of NSGA-II on the proposed IRAP. The results are in favor of NSGA-II.

Sustainable supply chain design-a configurational approach

Designing the right supply chain that meets the requirements of sustainable development is a significant challenge. Although there are a considerable number of studies on issues relating to sustainable supply chain design (SSCD) in terms of designing the practices, processes, and structures, they have rarely demonstrated how these components can be aligned to form an effective sustainable supply chain (SSC). Considering this gap in the literature, this study adopts the configurational approach to develop a conceptual framework that could configure the components of a SSC. In this respect, a process-oriented approach is utilized to classify and harmonize the design components. A natural-resource-based view (NRBV) is adopted to determine the central theme to align the design components around. The proposed framework presents three types of SSC, namely, efficient SSC, innovative SSC, and reputed SSC. The study culminates with recommendations concerning the direction for future research.

Economic order quantity models for items with imperfect quality and emission considerations

ABSTRACTIncorporation of quality and environmental concerns in production and inventory models has received considerable attention in the inventory management literature; however, researchers studied these topics mostly independently. Thus, it is required to jointly incorporate those two relevant aspects in a single research to support decisions, compare the results and obtain new insights for complexities in practice. This paper takes a step in this line of thought and revisits some economic order quantity (EOQ) models with imperfect quality from a sustainable point of view. The objective is to investigate the impact of emission costs on the replenishment order sizes and the total profit of a buyer (retailer) in an imperfect supply process, where the buyer receives the batches containing a percentage of imperfect quality items. First, an EOQ model with imperfect quality items and emission costs, which are the result of warehousing and waste disposal activities, is formulated. Next, the model is extended ...

A bi-objective multi-period series-parallel inventory-redundancy allocation problem with time value of money and inflation considerations

We formulate a multi-component multi-period series-parallel inventory redundancy allocation problem.We consider time value of money and inflation rate in optimizing the problem.We find the optimal order quantity for each subsystem by optimizing inventory costs and reliability, concurrently.CE-NRGA, NSGA-II, and MOPSO are used to solve the SPIRAP.Numerical examples demonstrate the applicability of the algorithms. A large number of existing research studies on reliability redundancy allocation problems do not take into consideration the time value of the money and the inflations costs associated with the component inventories. In this study, we formulate a multi-component multi-period series-parallel inventory redundancy allocation problem (SPIRAP) as a mixed-integer nonlinear mathematical model where: (a) the costs are calculated by considering the time value of money and inflation rates; and (b) the total warehouse capacity to store the components, the total budget to purchase the components and the truck capacity are subject to constraints. The primary goal in this study is to find the optimal order quantity of the components for each subsystem in each period such that the total inventory costs are minimized and the system reliability is maximized, concurrently. A controlled elitism non-dominated ranked genetic algorithm (CE-NRGA), a NSGA-II, and a multi-objective particle swarm optimization (MOPSO) are presented to solve the proposed SPIRAP. A series of numerical examples are used to demonstrate the applicability and exhibit the efficacy of the procedures and algorithms. The results reveal that the CE-NRGA outperforms both NSGA-II and MOPSO.

Application of Data Acquisition and Telemetry System into a Solar Vehicle

The Center for Product Design and Manufacturing (CPDM) of University Malaya going to take part in the World Solar Challenge (WSC) 2009. It is a biannual solar powered car race over 3021 km from Darwin to Adelaide. The aim of this project is to build a system for monitoring performance of the solar vehicle during testing and race, a data acquisition and telemetry (DaqT) system is needed. In this project, a DaqT system will be developed using National Instruments’ (NI) LabVIEW, compactRIO (cRIO) and MaxStream Xstream Radio Frequency modules. The DaqT is able to measure signals from sensors which are thermocouples, current transducers, battery storage and tachometer. Experiment is conducted to investigate the capability of the DaqT system to process signals from essential sensors, transmit data with wireless communication and data logging. The results of this project from the experiment, the DaqT manage to transmit data in open space up to 700 meters and the percentages of the error is below 5%.

A Review on lower-Limb Exoskeleton System for Sit to Stand, Ascending and Descending Staircase Motion.

Robotic exoskeleton system has been found to be an active area of study which being used in human power augmentation, human power assistance, robotic rehabilitation, and haptic interaction in virtual reality developed in recent robotic research. In recent years, the application of robotic exoskeleton has become more prominent as to provide alternative solutions for physically less incapable people (PLIP) support in their daily movements. Most common difficulties faced by PLIP are in sit-to-stand, ascending and descending staircases. Unlike industrial robots, the robotic exoskeleton systems need to consider a special design because they directly interact with human user. In the mechanical design of these systems, human and robotic suitable kinematics, wearer safety, human user comfort wearing, low inertia, and adaptability should be especially considered. Controllability, responsiveness, flexible and smooth motion generation, and safety should especially be considered in the controllers of exoskeleton systems. Furthermore, the controller should generate the motions in accordance with the human motion intention. This paper briefly reviews the lower-limb robotic exoskeleton systems. In the short review, it is focused to identify the brief history, basic concept, challenges, and future development of the robotic exoskeleton systems to assist the physically less incapable people (PLIP) in rising up, sitting, ascending and descending staircases. Furthermore, key technologies of lower-limb exoskeleton systems are reviewed by taking state-of-the-art robot as examples. Keywords: List the Robotic exoskeleton systems, rehabilitation robotics, man-machine intelligent system