International Science Index

International Journal of Industrial and Manufacturing Engineering

A Review on the Role of Partial Velocity in Cold Spray
Among the various coating methods, cold spraying is a new emerging coating technique. Cold gas dynamic spray (CGDS), simply called cold spraying, is a rapidly developing technology for the preparation of coatings or bulk materials in the solid state. Cold spray coatings have very low porosity, high hardness, erosion resistant and with a strong ability to resist high-temperature corrosion. This paper briefly reviews the role of partial velocity in cold spray process to understand the phenomenon and to summarize the rapidly expanding common knowledge on the cold spray technology under the light of presently available literature.
Competency and Strategy Formulation in Automobile Industry
In present days, companies face the rapid competition in terms of customer requirements to be satisfied, new technologies to be integrated into future products, new safety regulations to be followed, new computer-based tools introduced into design activities that become more scientific, etc. In today’s highly competitive market, survival focuses on various factors such as quality, innovation, adherence to standards and rapid response as the basis for competitive advantage. In order to maintain a competitive advantage, companies have to produce various competencies, for enhancing the capability of suppliers, the process of technology integration needs to be strengthened. For more competitiveness, organizations should operate in a strategy driven way and have a strategic architecture for developing core competencies Traditional ways to take such experience and develop competencies tend to take a lot of time and are expensive. A new learning environment, which is built around a gaming engine supports the development of competencies in specific subject areas. Technology competencies have a significant role in firm innovation and competitiveness, they interact with competitive environment. Technological competencies, varies according to the type of competitive environment, thus enhancing firm innovativeness. Technological competency is gained through extensive experimentation and learning in its research, development, and employment in production.
A System to Detect Cyber-Physical Attacks in CyberManufacturing Systems
CyberManufacturing System (CMS), Industrie 4.0, Cloud Manufacturing are visions for future manufacturing systems where the physical components are fully integrated with computational resources. The openness of the Internet enhances manufacturing activities with new capabilities in communication, information resources, storage, and computation. However, this very openness also creates vulnerability, especially because it enlarges the attack surface where attackers can intrude into or extract data from the manufacturing system. Currently, computer and information security methods—such as firewalls and intrusion detection system—cannot detect the malicious attacks in CMS with adequate respond time and accuracy. Realization of CMS depends on effectively addressing cyber-physical security issues. These attacks can cause physical damages to physical components—machines, equipment, parts, assemblies, products—through over-wearing, breakage, scrap parts or other changes that designers did not intend. This research proposes a system to detect cyber-physical intrusions in CMS. To accomplish this objective, physical data from manufacturing process level, production system level, are integrated with cyber data from network-based and host-based intrusion detection systems. The correlation between the cyber and physical data are investigated. Two methods—machine learning and quality control—are mainly adopted to detect the intrusion. 3D printing and CNC milling processes are used as examples of manufacturing processes for detecting cyber-physical attacks. Five attack scenarios: repackaging attack on “STL” file, race condition attack on job priority, SQL injection attack on “G-code,” Shellshock attack on 3D printer settings, cross-site request forgery attack on CNC machine settings have been developed to study process flow, influence, and detection of cyber-physical attacks.
Distance-To-Target Method to Evaluate Sustainability Patterns of CyberManufacturing Systems
Recognizing the importance of sustainability, manufacturers are pursuing holistic well-being of the society by addressing all three dimensions of sustainability: environmental, economical, and societal aspects. Sustainability metrics—or indicators—can measure the progress towards sustainability. However, existing metrics on assessing sustainability patterns of manufacturing systems are not comprehensive; and lacking objectivity, data measurability, and information communication efficiency. This research developed an improved sustainability assessment framework. A comprehensive set of sustainability indicators covering various patterns of manufacturing system is collected. Distance-to-Target methodology is adopted to compute and aggregate all sustainability indicators. The quantitative formula for each indicator is elaborated and all involved variables are measurable performance record of manufacturing system or publicly available data. Among them, the workload and production context or specificity information are integrated into target values of distance-to-target weighing factors. One example, cooling/lubricant fluid usage in machining, is selected for testing the validation of the proposed assessment framework. The evaluation report shows consistent results with the referred work and also demonstrates a high efficiency in result interpretation, chart presentation, and suggestions for improvement. Another example—plastic parts assembly and inspection process in a traditional production line and a CyberManufacturing system production line—are adapted for analyzing sustainability benefits. The evaluation result indicates the degree of improvement in economic profitability. Therefore, the Distance-to-Target methodology has proven to be unbiased and reproducible, along with transparent computation processes and efficient results interpretation.
Energy Efficiency Analysis of Crossover Technologies in Industrial Applications
Industry accounts for one-third of global final energy demand. Before the background of climate change and restricted resources, it is necessary to improve the energy efficiency of industrial processes. A key challenge for improving the energy efficiency is that industry is highly heterogeneous. The structure of the energy consumption in industrial enterprises depends on the character of the production process (e.g., primary energy resources, energy intensity of the products, production plan, and machinery). Energy efficiency targets include activities for single processes, as well as strategies for the complete enterprise. The energy analysis represents the first step of the optimization process. In many plants, the energy streams are only measured by a single meter at the source. The energy use of single processes is mostly unknown. The installation of additional measurement devices (e.g., flowmeters or wireless electric power meters) is one option to get more information about the energy distribution. Otherwise retrofitting of energy meters into running processes is difficult and in many cases impossible. Alternatively, we can use specific information coming from the automation system, which controls the production process. These data are collected by an energy information system (EMIS). The paper will describe a comprehensive methodology to realize an energy analysis. In industrial enterprises, crossover technologies play an important role for energy efficiency. They are characterized by a large number of applications independent of the production branch. They include motors and drives, pump systems, compressed air, lighting, process heat, and air conditioning systems. The crossover technologies are responsible for a large share of the industrial energy consumption. Especially electrical power is used by drives, pumps, compressors, and lightning. In many applications, there are common problems dealing with: low energy efficiency, oversized dimension of the system, lack of control, and maintenance deficits. In many cases, oversized and inefficient drives are still used in historically grown industrial enterprises with changing production programs. The exchange of long term running motors by new ones with high efficiency class saves much energy and costs. We will demonstrate the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control systems (PCS) can support EMS. They observe the performance of the production systems and organize the maintenance procedure. PCS contains the sensors and actuators that are required for the control of the processing plant. The sensors measure the process variables, i.e., temperature, pressure, mass flow, etc. The actuators receive signals from the controller level and perform a function, e.g., they start a pump or close a valve. PCS schedules and records the outcomes of maintenance testing, inspection, and repair. These may be supplemented by equipment monitoring tools, typically running in association with the plant process historian, which measure and evaluate the current equipment performance. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.
Capacity Oversizing for Infrastructure Sharing Synergies: A Game Theoretic Analysis
Industrial symbiosis (I.S) rely on two basic modes of cooperation between organizations that are infrastructure/service sharing and resource substitution (the use of waste materials, fatal energy and recirculated utilities for production). The former consists in the intensification of use of an asset and thus requires to compare the incremental investment cost to be incurred and the stand-alone cost faced by each potential participant to satisfy its own requirements. In order to investigate the way such a cooperation mode can be implemented we formulate a game theoretic model integrating the grassroot investment decision and the ex-post access pricing problem. In the first period two actors set cooperatively (resp. non-cooperatively) a level of common (resp. individual) infrastructure capacity oversizing to attract ex-post a potential entrant with a plug-and-play offer (available capacity, tariff). The entrant’s requirement is randomly distributed and known only after investments took place. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period under some conditions that we derive. The entrant willingness-to-pay for the access to the infrastructure is driven by both her standalone cost and the complement cost to be incurred in case she chooses to access an infrastructure whose the available capacity is lower than her requirement level. The expected complement cost function is thus derived, and we show that it is decreasing, convex and shaped by the entrant’s requirements distribution function. For both uniform and triangular distributions optimal capacity level is obtained in the cooperative setting and equilibrium levels are determined in the non-cooperative case. Regarding the latter, we show that competition is deterred by the first period investor with the highest requirement level. Using the non-cooperative game outcomes which gives lower bounds for the profit sharing problem in the cooperative one we solve the whole game and describe situations supporting sharing agreements.
Intelligent Tooling Embedded Sensors for Monitoring the Wear of Cutting Tools in Turning Applications
In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.
An Overbooking Model for Car Rental Service with Different Types of Cars
Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level.
Infrastructure Sharing Synergies: Optimal Capacity Oversizing and Pricing
Industrial symbiosis (I.S) deals with both substitution synergies (exchange of waste materials, fatal energy and utilities as resources for production) and infrastructure/service sharing synergies. The latter is based on the intensification of use of an asset and thus requires to balance capital costs increments with snowball effects (network externalities) for its implementation. Initial investors must specify ex-ante arrangements (cost sharing and pricing schedule) to commit toward investments in capacities and transactions. Our model investigate the decision of 2 actors trying to choose cooperatively a level of infrastructure capacity oversizing to set a plug-and-play offer to a potential entrant whose capacity requirement is randomly distributed while satisficing their own requirements. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period. The entrant’s willingness-to-pay for the access to the infrastructure is dependent upon its standalone cost and the capacity gap that it must complete in case the available capacity is insufficient ex-post (the complement cost). Since initial capacity choices are driven by ex-ante (expected) yield extractible from the entrant we derive the expected complement cost function which helps us defining the investors’ objective function. We first show that this curve is decreasing and convex in the capacity increments and that it is shaped by the distribution function of the potential entrant’s requirements. We then derive the general form of solutions and solve the model for uniform and triangular distributions. Depending on requirements volumes and cost assumptions different equilibria occurs. We finally analyze the effect of a per-unit subsidy a public actor would apply to foster such sharing synergies.
A Literature Review on The Role of Local Potential for Creative Industries
Local creativity utilization has been a strategic investment to be expanded as a creative industry due to its significant contribution to the national gross domestic product. Many developed and developing countries look toward creative industries as an agenda for the economic growth. This study aims to identify the role of local potential for creative industries from various empirical studies. The method performed in this study will involve a peer-reviewed journal articles and conference papers review addressing local potential and creative industries. The literature review analysis will include several steps: material collection, descriptive analysis, category selection, and material evaluation. Finally, the outcome expected provides a creative industries clustering based on the local potential of various nations. In addition, the finding of this study will be used as future research reference to explore a particular area with well-known aspects of local potential for creative industry products.
Potential of High Performance Ring Spinning Based on Superconducting Magnetic Bearing
Due to the best quality of yarn and the flexibility of the machine, the ring spinning process is the most widely used spinning method for short staple yarn production. However, the productivity of these machines is still much lower in comparison to other spinning systems such as rotor or air-jet spinning process. The main reason for this limitation lies in the twisting mechanism of the ring spinning process. In the ring/traveler twisting system, each rotation of the traveler along with the ring inserts twist in the yarn. The rotation of the traveler at higher speed includes strong frictional forces, which in turn generates heat. Different ring/traveler systems concerning with its geometries, material combinations and coatings have already been implemented to solve the frictional problem. However, such developments can neither completely solve the frictional problem nor increase the productivity. The friction free superconducting magnetic bearing (SMB) system can be a right alternative replacing the existing ring/traveler system. The unique concept of SMB bearings is that they possess a self-stabilizing behavior i.e. they remain fully passive without any necessity for expensive position sensing and control. Within the framework of a research project funded by German research foundation (DFG), suitable concepts of the SMB-system have been designed, developed, and integrated as a twisting device of ring spinning replacing the existing ring/traveler system. With the help of the developed mathematical model and experimental investigation, the physical limitations of this innovative twisting device in the spinning process have been determined. The interaction among the parameters of the spinning process and the superconducting twisting element has been further evaluated, which derives the concrete information regarding the new spinning process. Moreover, the influence of the implemented SMB twisting system on the yarn quality has been analyzed with respect to different process parameters. The presented work reveals the enormous potential of the innovative twisting mechanism so that the productivity of the ring spinning process especially in case of thermoplastic materials can be at least doubled for the first time in a hundred years. The SMB ring spinning tester has also been presented in the international fair 'International Textile Machinery Association (ITMA) 2015'.
Effectiveness with Respect to Time-to-Market and the Impacts of Late-Stage Design Changes in Rapid Development Life Cycles
The author examines the recent trend where business organizations are significantly reducing their developmental cycle times to stay competitive in today’s global marketspace. The author proposes a rapid systems engineering framework to address late design changes and allow for flexibility (i.e. to react to unexpected or late changes and its impacts) during the product development cycle using a Systems Engineering approach. A System Engineering approach is crucial in today’s product development to deliver complex products into the marketplace. Design changes can occur due to shortened timelines and also based on initial consumer feedback once a product or service is in the marketplace. The ability to react to change and address customer expectations in a responsive and cost-efficient manner is crucial for any organization to succeed. Past literature, research, and methods such as concurrent development, simultaneous engineering, knowledge management, component sharing, rapid product integration, tailored systems engineering processes, and studies on reducing product development cycles all suggest a research gap exist in specifically addressing late design changes due to the shortening of life cycle environments in increasingly competitive markets. The author’s research suggests that 1) product development cycles time scales are now measured in months instead of years, 2) more and more products have interdepended systems and environments that are fast-paced and resource critical, 3) product obsolesce is higher and more organizations are releasing products and services frequently, and 4) increasingly competitive markets are leading to customization based on consumer feedback. The author will quantify effectiveness with respect to success factors such as time-to-market, return-of-investment, life cycle time and flexibility in late design changes by complexity of product or service, number of late changes and ability to react and reduce late design changes.
Design of a Low Cost Programmable LED Lighting System
Smart LED-based lighting systems have significant advantages over traditional lighting systems due to their capability of producing tunable light spectrums on demand. The main challenge in the design of smart lighting systems is to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area. This paper outlines the programmable LED lighting system design principles of design to achieve the two aims. In this paper, a seven-channel design using low-cost discrete LEDs is presented. Optimization algorithms are used to calculate the number of required LEDs, LEDs arrangements and optimum LED separation distance. The results show the illumination uniformity for each channel. The results also show that the maximum color error is below 0.0808 on the CIE1976 chromaticity scale. In conclusion, this paper considered the simulation and design of a seven-channel programmable lighting system using low-cost discrete LEDs to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area.
Assessment of Incorporating Drones into Emergency Services against Alternative Means of Transportation for Quick Response Time and Delivering Aiding Equippments
Traffic accidents are the leading cause of deaths among fatalities occurring due to non-natural disasters around the world. Emergency services of different countries responds to traffic accidents and these services execute the precious and very significant job of rescuing and securing human lives. Seriously injured persons during an event of a traffic accident need medical attention within first few minutes. For instance, victims of traumatic cardiac arrest in traffic accident and non-traumatic cardiac arrest must receive CPR within first 5-6 minutes otherwise their chances of survival are minimum around only 8 %. The average response time to emergencies in Europe is 10 minutes. The response time needs to be further reduced in order to maximize safety, therefore an improvement in current standard emergency procedures needs to be considered. For this purpose, this article investigates whether emergency services can respond faster by induction of drones whether manned or unmanned aerial vehicles (UAV) comparing with conventional means of transport such as helicopters or driving vehicles into emergency services. This articles uses the methodology of Multi Criteria Decision Analysis (MCDA) to choose the best possible alternative. The research of MCDA reveals that UAV could be the best alternative. A case study of a presumed traffic crash at Korskro roundabout in outskirts of Esbjerg, Denmark is hypothetically considered for the findings of the article. Moreover, the research finds that the socio economic benefits to the society of Unmanned Aerial Vehicles (UAV) can outweigh the costs of its induction by a huge margin if it could even save a single life. Resultantly the articles reckon the inevitable role that drones can play by incorporation of it into emergency services that can take safety to a higher level comparing conventional means of transportation.
A Priority Based Imbalanced Time Minimization Assignment Problem: An Iterative Approach
This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.
Toward Better Quality in Healthcare and Operations Management: A Developmental Literature Review
This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough (English and French) review drawn from their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, meeting or exceeding customer expectations, attributes, satisfaction), whereas in HCS, two approaches are prominent (Donabedian`s structure, process and outcomes model and Lohr and Schroeder`s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. It then proposes an encompassing definition of quality as a tool and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.
The Evaluation of Surface Integrity during Machining of Inconel 718 with Various Laser Assistance Strategies
The paper is focused on the evaluation of surface integrity formed during turning of Inconel 718 with the application of various laser assistance strategies. The primary objective of the work was to determine the relations between the applied machining strategy and the obtained surface integrity, in order to select the effective cutting conditions allowing the obtainment of high surface quality. The carried out experiment included the machining of Inconel 718 in the conventional turning conditions, as well as during the continuous laser assisted machining and sequential laser assistance. The surface integrity was evaluated by the measurements of machined surface topographies, microstructures and the microhardness. Results revealed that surface integrity of Inconel 718 is strongly affected by the selected machining strategy. The significant improvement of the surface roughness formed during machining of Inconel 718, can be reached by the application of simultaneous laser heating and cutting (LAM).
The Analysis of Surface Topography during Turning of Waspaloy with the Application of Response Surface Method
This paper presents the analysis of surface topography during longitudinal turning of Waspaloy. The primary objective of the work was to determine the optimal machining conditions enabling the minimization of surface roughness parameters. Experimental studies were performed with the application of fractional plan (with 1 block and 9 systems). The carried out experiment included the measurements of surface topographies formed after turning with variable cutting conditions (cutting speed vc, cutting depth ap and feed f). Subsequently, the measured quantities have been applied to the optimization procedure based on the application of response surface method (RSM). In order to obtain the optimal cutting parameters, the maximization of total utility function was carried out. Results revealed that the minimal surface roughness parameters values during turning of Waspaloy with the cubic boron nitride (CBN) inserts can be obtained for the: f=0.05 mm/rev, ap =0.23 mm and vc =452 m/min.
The Study on Physical Surface Layer after Laser Heating of Inconel 718
This paper focuses on the analysis of physical surface layer after laser heating of Inconel 718 alloy in variable conditions. The primary objective of the work was to determine the relations between the applied absorptive layer deposited on the workpiece, the type of applied laser and the obtained dimensions of re-melted surface, its microstructure, and micro-hardness distribution. Experiments were performed with the application of CO₂ and diode lasers. The Acheson and Gouache substances were selected as the absorptive layers. The carried out tests included the measurements of re-melted areas width and height, the identification of their microstructure, as well as the inspection of micro-hardness distribution inside the surface layer. Results revealed that the application of different lasers and distinct absorptive layers affect the values of re-melted areas’ micro-hardness.
Surface Roughness Formed during Hybrid Turning of Inconel Alloy
Inconel 718 is a material characterized by the unique mechanical properties, high temperature strength, high thermal conductivity and the corrosion resistance. However, these features affect the low machinability of this material, which is usually manifested by the intense tool wear and low surface finish. Therefore, this paper is focused on the evaluation of surface roughness during hybrid machining of Inconel 718. The primary aim of the study was to determine the relations between the vibrations generated during hybrid turning and the formed surface roughness. Moreover, the comparison of tested machining techniques in terms of vibrations, tool wear and surface roughness has been made. The conducted tests included the face turning of Inconel 718 with laser assistance in the range of variable cutting speeds. The surface roughness was inspected with the application of stylus profile meter and accelerations of vibrations were measured with the use of three-component piezoelectric accelerometer. The carried out research shows that application of laser assisted machining can contribute to the reduction of surface roughness and cutting vibrations, in comparison to conventional turning. Moreover, the obtained results enable the selection of effective cutting speed allowing the improvement of surface finish and cutting dynamics.
Maintenance Scheduling of Flood Control Plant under Uncertainty Based on Multi-Objective Optimization
The drainage pumping plants are the main facilities in flood control infrastructure. Many of them have deteriorated and their maintenance, especially replacement, has become a large issue in Japan. The plant consists of many kinds of devices. Each of them has its own lifespan. The lifespan has uncertainty. A method is proposed to schedule the replacement of devices under uncertainty, considering the two properties of rationality and robustness. The schedule has rationality when it is formulated logically and can be easily executed. The rationality is evaluated by the replacement cost in the scheduling period. The schedule has the robustness when it is hard to be affected even if uncertainty exists in the lifespan of device. The robustness is evaluated by the time difference between the actual and scheduled replacement. The problem results in multi-objective optimization on rationality and robustness. Pareto-optimal solutions are obtained. Finally, the case studies based on the practical conditions are illustrated to show the effectiveness of the proposed method. The contribution of this paper is to propose a method to design the replacement schedule which is hard to be affected by the uncertainty of the device lifespan.
Impact of Contemporary Performance Measurement System and Organization Justice on Academic Staff Work Performance
As part of the Malaysia Higher Institutions' Strategic Plan in promoting high-quality research and education, the Ministry of Higher Education has introduced various instrument to assess the universities performance. The aims are that university will produce more commercially-oriented research and continue to contribute in producing professional workforce for domestic and foreign needs. Yet the spirit of the success lies in the commitment of university particularly the academic staff to translate the vision into reality. For that reason, the element of fairness and justice in assessing individual academic staff performance is crucial to promote directly linked between university and individual work goals. Focusing on public research universities (RUs) in Malaysia, this study observes at the issue through the practice of university contemporary performance measurement system. Accordingly management control theory has conceptualized that contemporary performance measurement consisting of three dimension namely strategic, comprehensive and dynamic building upon equity theory, the relationships between contemporary performance measurement system and organizational justice and in turn the effect on academic staff work performance are tested based on online survey data administered on 365 academic staff from public RUs, which were analyzed using statistics analysis SPSS and Equation Structure Modeling. The findings validated the presence of strategic, comprehensive and dynamic in the contemporary performance measurement system. The empirical evidence also indicated that contemporary performance measure and procedural justice are significantly associated with work performance but not for distributive justice. Furthermore, procedural justice does mediate the relationship between contemporary performance measurement and academic staff work performance. Evidently, this study provides evidence on the importance of perceptions of justice towards influencing academic staff work performance. This finding may be a fruitful input in the setting up academic staff performance assessment policy.
Contracting Strategies to Foster Industrial Symbiosis Implementation
Industrial symbiosis (I.S) deals with the exchange of waste materials, fatal energy and utilities as resources for production. While it brings environmental benefits from resource conservation its economic profitability is one of the main barriers to its implementation. I.S involves several actors with their own objectives and resources so that each actor must be satisfied by ex-ante arrangements to commit toward investments and transactions. Regarding I.S Transaction cost economics helps to identify hybrid forms of governance for transactions governance due to I.S projects specificities induced by the need for customization (asset specificity, non-homogeneity). Thus we propose a framework to analyze the best contractual practices tailored to address I.S specific risks that we identified as threefold (load profiles and quality mismatch, value fluctuations). Schemes from cooperative game theory and contracting management are integrated to analyze value flows between actors. Contractual guidelines are then proposed to address the identified risks and to split the value for a set of I.S archetypes drawn from actual experiences.
A Hybrid Distributed Algorithm for Multi-Objective Dynamic Flexible Job Shop Scheduling Problem
In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.
A Hybrid Distributed Algorithm for Solving Job Shop Scheduling Problem
In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.
A High-Level Co-Evolutionary Hybrid Algorithm for the Multi-Objective Job Shop Scheduling Problem
In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.
Integrating Cost-Benefit Assessment and Contract Design to Support Industrial Symbiosis Deployment
Industrial symbiosis (I.S) is the realization of Industrial Ecology (I.E) principles in production systems in function. I.S consists in the use of waste materials, fatal energy, recirculated utilities and infrastructure/service sharing as resources for production. Environmental benefits can be achieved from resource conservation but economic profitability is required by the participating actors. I.S indeed involves several actors with their own objectives and resources so that each one must be satisfied by ex-ante arrangements to commit toward I.S execution (investments and transactions). Following the Resource-Based View of transactions we build a modular framework to assess global I.S profitability and to specify each actor’s contributions to costs and benefits in line with their resource endowments and performance requirements formulations. I.S projects specificities implied by the need for customization (asset specificity, non-homogeneity) induce the use of long-term contracts for transactions following Transaction costs economics arguments. Thus we propose first a taxonomy of costs and value drivers for I.S and an assignment to each actor of I.S specific risks that we identified as load profiles mismatch, quality problems and value fluctuations. Then appropriate contractual guidelines (pricing, cost sharing and warranties) that support mutual profitability are derived from the detailed identification of contributions by the cost-benefits model. This analytical framework helps identifying what points to focus on when bargaining over contracting for transactions and investments. Our methodology is applied to I.S archetypes raised from a literature survey on eco-industrial parks initiatives and practitioners interviews.
Classifying Thin Film Transistor-Liquid Crystal Display Panels Based on Defective Pixels Using Rough Set Model
The number of defective pixels found on a thin film transistor-liquid crystal display (TFT-LCD) panel is a major criterion to grade the panel. Instead of inspecting the TFT-LCD panels manually, recent trend in practice is to use automatic optical inspection (AOI) which applying algorithms to analyze the images taken by optical instruments. Very few studies related to using AOI on TFT-LCD panel inspection focused on detecting the defective pixels on the panels. This study proposed a classification model based on Rough Set Theory (RST) to differentiate good TFT-LCD panels from bad ones based on the existence of defective pixels found on the images of the panels. Special image pre-processing algorithms were developed to emphasize the types of defective pixels shown on the images. Real images of TFT-LCD panels provided by a computer manufacturer in Taiwan were used to test the effectiveness and efficiency of the proposed model. The results of numerical experiment showed that the proposed approach has an average of 99.5% classification accuracy.
A Framework for Event-Based Monitoring of Business Processes in the Supply Chain Management of Industry 4.0
In modern supply chains, large numbers of SKU (Stock-Keeping-Unit) need to be timely managed, and any delays in noticing disruptions of items often limit the ability to defer the impact on customer order fulfillment. However, in supply chains of IoT-connected enterprises, the ERP (Enterprise-Resource-Planning), the MES (Manufacturing-Execution-System) and the SCADA (Supervisory-Control-and-Data-Acquisition) systems generate large amounts of data, which generally glean much earlier notice of deviations in the business process steps. That is, analyzing these streams of data with process mining techniques allows the monitoring of the supply chain business processes and thus identification of items that deviate from the standard order fulfillment process. In this paper, a framework to enable event-based SCM (Supply-Chain-Management) processes including an overview of core enabling technologies are presented, which is based on the RAMI (Reference-Architecture-Model for Industrie 4.0) architecture. The application of this framework in the industry is presented, and implications for SCM in industry 4.0 and further research are outlined.
Ultrasonic Micro Injection Molding: Manufacturing of Micro Plates of Biomaterials
Introduction: Ultrasonic moulding process (USM) is a recent injection technology used to manufacture micro components. It is able to melt small amounts of material so the waste of material is certainly reduced comparing to microinjection molding. This is an important advantage when the materials are expensive like medical biopolymers. Micro-scaled components are involved in a variety of uses, such as biomedical applications. It is required replication fidelity so it is important to stabilize the process and minimize the variability of the responses. The aim of this research is to investigate the influence of the main process parameters on the filling behaviour, the dimensional accuracy and the cavity pressure when a micro-plate is manufactured by biomaterials such as PLA and PCL. Methodology or Experimental Procedure: The specimens are manufactured using a Sonorus 1G Ultrasound Micro Molding Machine. The used geometry is a rectangular micro-plate of 15x5mm and 1mm of thickness. The materials used for the investigation are PLA and PCL due to biocompatible and degradation properties. The experimentation is divided into two phases. Firstly, the influence of process parameters (vibration amplitude, sonotrodo velocity, ultrasound time and compaction force) on filling behavior is analysed, in Phase 1. Next, when filling cavity is assured, the influence of both cooling time and force compaction on the cavity pressure, part temperature and dimensional accuracy is instigated, which is done in Phase. Results and Discussion: Filling behavior depends on sonotrodo velocity and vibration amplitude. When the ultrasonic time is higher, more ultrasonic energy is applied and the polymer temperature increases. Depending on the cooling time, it is possible that when mold is opened, the micro-plate temperature is too warm. Consequently, the polymer relieve its stored internal energy (ultrasonic and thermal) expanding through the easier direction. This fact is reflected on dimensional accuracy, causing micro-plates thicker than the mold. It has also been observed the most important fact that affects cavity pressure is the compaction configuration during the manufacturing cycle. Conclusions: This research demonstrated the influence of process parameters on the final micro-plated manufactured. Future works will be focused in manufacturing other geometries and analysing the mechanical properties of the specimens.