Jafni Azhan Ibrahim

Waste biomass toward hydrogen fuel supply chain management for electricity: Malaysia perspective

Green energy is becoming an important aspect of every country in the world toward energy security by reducing dependence on fossil fuel import and enhancing better life quality by living in the healthy environment. This conceptual paper is an approach toward determining physical flow’s characteristic of waste wood biomass in high scale plantation toward producing gas fuel for electricity using gasification technique. The scope of this study is supply chain management of syngas fuel from wood waste biomass using direct gasification conversion technology. Literature review on energy security, Malaysia’s energy mix, Biomass SCM and technology. This paper uses the theoretical framework of a model of transportation (Lumsden, 2006) and the function of the terminal (Hulten, 1997) for research purpose. To incorporate biomass unique properties, Biomass Element Life Cycle Analysis (BELCA) which is a novel technique develop to understand the behaviour of biomass supply. Theoretical framework used to answer the resea...

Spare parts inventory risk for decision making in plant maintenance

Equipment breakdown due to unavailability of spare parts is really disastrous in plant maintenance. The failure increase the cost of repair and production downtime. Therefore, it is important to understand the maintenance and inventory function in order to ensure the plant operate accordingly. Moreover, it is necessary for the plant maintenance to balance the issue of shortage and excess of inventory in plant maintenance. In view of this situation, the spare parts become a critical matters and it is good starting point to tackle the issues from looking at the perspective of spare parts inventory risk. This paper describes the development of risk technique for plant maintenance decision making purposes using the Shortage and Excess Impact Table. It also used the Breakdown Probability Table to quantify the risk for the spare part failure.

A new formulation for optimizing coal procurement in power generation

M in health care refers to the physician and their assistant dealing with more than one task simultaneously over the same period during surgery or in other operations of the health care system. The multitasking in healthcare system is also a big challenge and has esteem importance. Physicians, Nurses, Dispenser (Medicine collector) and patients are the key stakeholders for this system. The aim of this study is to determine the impact of multitasking by hospital physicians, nurse and operator performance. The method to evaluate the performance of the each stakeholder is done using a time and motion study in King Khalid university hospital. The performance measures multitasking activities during medicine distributions, nursing and surgery/operations. The effect of these input factors is assessed through the satisfaction of patients. Ten stakeholders (surgeon, nurses, medicine distribution unit at pharmacy and patients) were observed. The patients are observed after the activity is performed through an interview. Then the response of each patient is calculated on a likert scale (from 1 to 5) and is evaluated and analyzed. The research highlights for each category of multitasking is proposed at the end. Physician surgery supposed to be the most caring area and need more attention during multitasking. Nurse’s patient caring and medicine distribution are least area with respect to danger. Each area has its own importance; especially in cardiac surgery when number of patients waiting are too large and surgeons are limited. In these types of cases, they have to do multitask to serve more patients corresponding to decrease the death rate.T traditional desk-based design of work in many organizations, even those that outwardly claim to embrace the principles of ergonomics reflects a design paradigm in which workers are constrained by organizational factors rather than human factors, stifling workers’ potential for innovation and productivity. The traditional approach to workplace design reflects an organizational fear of uncertainty. This workplace is a product of the desire of its owners to control and direct human activity to achieve a predefined goal; it is essentially a command-and-control work system, in which uncertainty is a form of future threat to be negated by the application of tighter controls, more rigorous planning, micro-management, and by increasing centralization of decision-making and power. Such an approach is inefficient and unrewarding, both for the employee and for the employer. Uncertainty is, however, a significant component of profit, and it has long been argued that there are economic advantages for organizations that embrace, rather than resist uncertainty. In the uncertainty-embracing workplace, people may express their potential for working in a more co-operative manner with more fluid social engagement, resulting in greater problem solving, peer-to-peer encouragement, teaching, learning, ingenuity, and innovation. Based on recent collaboration between professionals in workplace design, management consulting and human factors, this presentation advocates a design approach that facilitates the embracing of uncertainty, thereby releasing the innovation and profit potential of all employees.The aim of this paper is to reassess the way management technology was carried out in the manufacturing industry and establish “New JIT, New Management Technology Principle”. New JIT consists of the Total Development System (TDS), the Total Production System (TPS) and the Total Marketing System (TMS), which are the three core elements required for establishing new management technology principles for sales, R&D, design, engineering, and production, among others. To realize manufacturing that places top priority on customers with a good QCD in a rapidly changing technical environment, the author proposes a high linkage model, employing a structured “integrated triple management technologies system Advanced TDS, TPS & TMS” for expanding “uniform quality worldwide and production at optimum locations”.S chain (SC) is a system with multi-layer entities, multi-layer processes, to convert raw material into products. There are three levels of planning issues in a supply chain, i.e., strategic, tactical, and operational levels. They differ from each other based on their considerations and time effects. The strategic level planning deals with issues in the design stage of a supply chain, tactical level considers utilizing the SC resources, and the operational level deals with daily or weekly scheduling issues. SC optimization and its responsiveness are greatly influenced by inventory and as such inventory and amount of safety stock are important issues in a supply chain to manage demand uncertainties and maintain customer service level at lowest possible cost and shortest responsive time. In this paper, the multi-echelon safety stock optimization (MESSO) for tactical supply chain planning (SCP) in manufacturing systems is addressed. The problem is formulated as a multi-objective mixed integer non-linear programming (MINLP) model. Unlike other works that consider serial, assembly, or distribution system only, our model considers general supply chain topology. In a competitive global market, different objectives should be optimized simultaneously to avoid conflicting decisions. In the SC planning context, two methods are often used to optimize multi-objective models. The first one is to convert the multi-objective problem into a single-objective using a weighted sum or weighted goal programming method. The main drawback of this method is the subjectivity and bias in weight setting. The other method is known as e-constraint method in which one objective is optimized while the others are used as un-equality constraints. The same approach is applied to every objective leading to a set of solutions called Pareto optimal solutions or nondominated points which form the Pareto-Optimal (Pareto-Efficient) Frontier. However, this method again involves subjectivity in determining which frontier point is selected eventually. For this reason, the modified Chebyshev programming (MFC) method is adopted to solve the multi-objective model. Unlike the conventional weighted sum method that subjectively assigns weight to each objective, the weights in the MCP method are automatically selected based on the importance order of the objectives, the model and input data. Application of the proposed model and solution method are illustrated by solving an example problem and compared with the traditional weighted-goal programming method.T concern to develop wind turbines as a low carbon source of renewable energy is paramount to the fast expansion of renewable energy for power production. Proper analytical condition monitoring technique to observe the state of system could minimize damage to the whole turbine. Faults are inevitable in automated system of which failures could be severe depending on the kind of machine and the circumstances of the fault interruption. The main aim is to increase reliability, cost effective for modern dynamic systems could improve industrial automatic system availability as well as achieving a better system performance. The main challenge in model-based fault detection and diagnosis FDD is to diagnose incipient and abrupt faults in complex dynamic systems considering a practical system input and output measurements. Several techniques have been proposed to improve the performance of fault diagnosis is a captivating research challenge to advance of the robustness to fault detection. Model-based FDI has been studied for over 20 years; this can be used to either boost safety or accomplish a more reasonable current level of safety. A genetic algorithm (GA) is an artificial intelligence to increase the FDD performance to optimize an observer. A better analysis have been identified to demonstrate the propose approach.M and reliability are playing vital roles in all engineering disciplines. As the demand for systems with better performance at minimum cost increases, there is a requirement to minimize the failure probability and the need to the system recovery mechanisms and fault tolerance. However, history witnesses that maintainability design is lagging behind structure design. To solve this problem, VR based maintainability design method is proposed that validates maintainability design of a structure. This presentation aims at providing an overview on maintainability design and VR technology. Also, the required platform for integrating maintainability information into structured information, and limitations & complications will be discussed. Finally, the processes and feature/benefit matrix and maintenance metrics will be presented.A sequence planning is a typical of representative combinatorial optimization problems in manufacturing. The general methods are used to generate a large number of feasible assembly sequences and find the best sequence through evaluation. A lot of computation time and memory space are needed and many methods usually find a local optimum. To reduce the hardness of assembly sequence planning, the assembly model is converted into a directed weighted graph considering the assembly constraints which are classified into the qualitative and quantitative constraints. The qualitative constraints including the topological and geometrical assembly constraints between parts are adopted to configure out the feasible assembly sequences and they are represented as the directed edges in the weighted graph. A portion of process constraints is also used as the qualitative constraints. The other process constraints, such as the assembly tolerance, assembly stability, assembly directions and tools, are quantified with the fuzzy analytical hierarchy process method and attached to the edges. The weights are taken as the heuristic information to find the optimal fragments of the optimal or near-optimal assembly sequences. With the assembly weighted graph, the optimal or near-optimal assembly sequences will be searched in the generation of the feasible sequences and the search space of the best solution will be decreased. A branch and bound algorithm is designed to find the optimal sequence with the weighted graph. The results illustrate that the optimal assembly sequences are found quickly. The method is expected to apply to the complex products.