World Academy of Science, Engineering and Technology

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

Procedia PDF Downloads 240

Authors: Ilaria Barletta, Mahesh Mani, Björn Johansson

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The concept of sustainability encompasses economic, environmental, social and institutional considerations. Sustainable manufacturing (SM) is, therefore, a multi-faceted concept. It broadly implies the development and implementation of technologies, projects and initiatives that are concerned with the life cycle of products and services, and are able to bring positive impacts to the environment, company stakeholders and profitability. Because of this, achieving SM-related goals requires a holistic, life-cycle-thinking approach from manufacturing companies. Further, such an approach must rely on a logic of continuous improvement and ease of implementation in order to be effective. Currently, there exists in the academic literature no comprehensively structured frameworks that support manufacturing companies in the identification of the issues and the capabilities that can either hinder or foster sustainability. This scarcity of support extends to difficulties in obtaining quantifiable measurements in order to objectively evaluate solutions and programs and identify improvement areas within SM for standards conformance. To bridge this gap, this paper proposes the concept of a framework for assessing and continuously improving the sustainability of manufacturing companies. The framework addresses strategies and projects for SM and operates in three sequential phases: analysis of the issues, design of solutions and continuous improvement. A set of interviews, observations and questionnaires are the research methods to be used for the implementation of the framework. Different decision-support methods - either already-existing or novel ones - can be 'plugged into' each of the phases. These methods can assess anything from business capabilities to process maturity. In particular, the authors are working on the development of a sustainable manufacturing maturity model (SMMM) as decision support within the phase of 'continuous improvement'. The SMMM, inspired by previous maturity models, is made up of four maturity levels stemming from 'non-existing' to 'thriving'. Aggregate findings from the use of the framework should ultimately reveal to managers and CEOs the roadmap for achieving SM goals and identify the maturity of their companies’ processes and capabilities. Two cases from two manufacturing companies in Australia are currently being employed to develop and test the framework. The use of this framework will bring two main benefits: enable visual, intuitive internal sustainability benchmarking and raise awareness of improvement areas that lead companies towards an increasingly developed SM.

Keywords: life cycle management, continuous improvement, maturity model, sustainable manufacturing

Procedia PDF Downloads 253

Authors: M. Zadshakoyan, H. Marassem Bonab, P. M. Keshtiban

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The SPD process widely used to optimize microstructure, strength and mechanical properties of the metals. Processes such as ARB and APB could have a considerable impact on improving the properties of metals. The aluminum material after steel, known as the most used metal, Because of its low strength, there are restrictions on the use of this metal, it is required to spread further studies to increase strength and improve the mechanical properties of this light weight metal. In this study, Annealed aluminum material, with yield strength of 85 MPa and tensile strength of 124 MPa, sliced into 2 sheets with dimensions of 30 and 25 mm and the thickness of 1.5 mm. then the sheets press bonded under 6 cycles, which increased the ultimate strength to 281 MPa. In addition, by adding 0.1%Wt of SiC particles to interface of the sheets, the sheets press bonded by 6 cycles to achieve a homogeneous composite. The same operation using Al2O3 particles and a mixture of SiC+Al2O3 particles was repeated and the amount of strength and elongation of produced composites compared with each other and with pure 6 cycle press bonded Aluminum. The results indicated that the ultimate strength of Al/SiC composite was 2.6 times greater than Annealed aluminum. And Al/Al2O3 and Al/Al2O3+SiC samples were low strength than Al/SiC sample. The pure 6 time press bonded Aluminum had lowest strength by 2.2 times greater than annealed aluminum. Strength of aluminum was increased by making the metal matrix composite. Also, it was found that the hardness of pure Aluminum increased 1.7 times after 6 cycles of APB process, hardness of the composite samples improved further, so that, the hardness of Al/SiC increased up to 2.51 times greater than annealed aluminum.

Keywords: APB, nano composite, nano particles, severe plastic deformation

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Authors: Sevde D. Karayel, Ediz Atmaca

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Supplier selection subject is vital because of development competitiveness and performance of firms which have right, rapid and with low cost procurement. Considering the fact that competition between firms is no longer on their supply chains, hence it is very clear that performance of the firms’ not only depend on their own success but also success of all departments in supply chain. For this purpose, firms want to work with suppliers which are cost effective, flexible in terms of demand and high quality level for customer satisfaction. However, diversification and redundancy of their expectations from suppliers, supplier selection problems need to be solved as a hard problem. In this study, supplier selection problem is discussed for critical piece, which is using almost all production of products in and has troubles with lead time from supplier, in a firm that produces medical devices. Analyzing policy in the current situation of the firm in the supplier selection indicates that supplier selection is made based on the purchasing department experience and other authorized persons’ general judgments. Because selection do not make based on the analytical methods, it is caused disruptions in production, lateness and extra cost. To solve the problem, AHP and TOPSIS which are multi-criteria decision making techniques, which are effective, easy to implement and can analyze many criteria simultaneously, are used to make a selection among alternative suppliers.

Keywords: AHP-TOPSIS methods, multi-criteria decision making, supplier selection problem, supply chain management

Procedia PDF Downloads 257

Authors: Samuel Atongaba Danji, Veseke Moleke

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The increase of globalization is a very important part of today’s changing environment and due to this, manufacturing industries have to always come up with methods of continuous improvement of their manufacturing methods in order to be competitive, without which may lead them to be left out of the market due to constant changing customers requirement. Due to this, the need is an advance supply chain system which prevents a number of issues that can prevent a company from being competitive. In this work, we developed a feedback control supply chain system which streamline the entire process in order to improve competitiveness and the result shows that when applied in a different geographical area, the output varies.

Keywords: globalization, supply chain, improvement, manufacturing

Procedia PDF Downloads 327

Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: queueing network, discrete-event simulation, health applications, SPT

Procedia PDF Downloads 183

Authors: Mehdi Moayyedian, Kazem Abhary, Romeo Marian

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This paper presents an evaluation of a plastic defect in injection molding before it occurs in the process; it is known as the short shot defect. The evaluation of different parameters which affect the possibility of short shot defect is the aim of this paper. The analysis of short shot possibility is conducted via SolidWorks Plastics and Taguchi method to determine the most significant parameters. Finite Element Method (FEM) is employed to analyze two circular flat polypropylene plates of 1 mm thickness. Filling time, part cooling time, pressure holding time, melt temperature and gate type are chosen as process and geometric parameters, respectively. A methodology is presented herein to predict the possibility of the short-shot occurrence. The analysis determined melt temperature is the most influential parameter affecting the possibility of short shot defect with a contribution of 74.25%, and filling time with a contribution of 22%, followed by gate type with a contribution of 3.69%. It was also determined the optimum level of each parameter leading to a reduction in the possibility of short shot are gate type at level 1, filling time at level 3 and melt temperature at level 3. Finally, the most significant parameters affecting the possibility of short shot were determined to be melt temperature, filling time, and gate type.

Keywords: injection molding, plastic defects, short shot, Taguchi method

Procedia PDF Downloads 212

Authors: Van Dong Phung, Igor Hawryszkiewycz, Kyeong Kang, Muhammad Hatim Binsawad

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Knowledge sharing (KS) is the key to creativity and innovation in any organizations. Overcoming the KS barriers has created new challenges for designing in dynamic and complex environment. There may be interrelations and interdependences among the barriers. The purpose of this paper is to present a review of literature of KS barriers and impute the relative importance of them through the fuzzy analytic network process that is a generalization of the analytical hierarchy process (AHP). It helps to prioritize the barriers to find ways to remove them to facilitate KS. The study begins with a brief description of KS barriers and the most critical ones. The FANP and its role in identifying the relative importance of KS barriers are explained. The paper, then, proposes the model for research and expected outcomes. The study suggests that the use of the FANP is appropriate to impute the relative importance of KS barriers which are intertwined and interdependent. Implications and future research are also proposed.

Keywords: FANP, ANP, knowledge sharing barriers, knowledge sharing, removing barriers, knowledge management

Procedia PDF Downloads 326

Authors: Muhammad Saleem Ullah Khan Sumbal, Eric Tsui, Ricky Cheong, Eric See To

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Organizations are posed to a threat of valuable knowledge loss when employees leave either due to retirement, resignation, job change or because of disabilities e.g. death, etc. Due to changing economic conditions, globalization, and aging workforce, organizations are facing challenges regarding retention of valuable knowledge. On the one hand, large number of employees are going to retire in the organizations whereas on the other hand, younger generation does not want to work in a company for a long time and there is an increasing trend of frequent job change among the new generation. Because of these factors, organizations need to make sure that they capture the knowledge of employee before (s)he walks out of the door. The first step in this process is to know what type of knowledge employee possesses and whether this knowledge is important for the organization. Researchers reveal in the literature that despite the serious consequences of knowledge loss in terms of organizational productivity and competitive advantage, there has not been much work done in the area of knowledge loss assessment of departing employees. An important step in the knowledge retention process is to determine the critical ‘at risk’ knowledge. Thus, knowledge loss risk assessment is a process by which organizations can gauge the importance of knowledge of the departing employee. The purpose of this study is to explore this topic of knowledge loss risk assessment by conducting a qualitative study in oil and gas sector. By engaging in dialogues with managers and executives of the organizations through in-depth interviews and adopting a grounded methodology approach, the research will explore; i) Are there any measures adopted by organizations to assess the risk of knowledge loss from departing employees? ii) Which factors are crucial for knowledge loss assessment in the organizations? iii) How can we prioritize the employees for knowledge retention according to their criticality? Grounded theory approach is used when there is not much knowledge available in the area under research and thus new knowledge is generated about the topic through an in-depth exploration of the topic by using methods such as interviews and using a systematic approach to analyze the data. The outcome of the study will generate a model for the risk of knowledge loss through factors such as the likelihood of knowledge loss, the consequence/impact of knowledge loss and quality of the knowledge loss of departing employees. Initial results show that knowledge loss assessment is quite crucial for the organizations and it helps in determining what types of knowledge employees possess e.g. organizations knowledge, subject matter expertise or relationships knowledge. Based on that, it can be assessed which employee is more important for the organizations and how to prioritize the knowledge retention process for departing employees.

Keywords: knowledge loss, risk assessment, departing employees, Hong Kong organizations

Procedia PDF Downloads 401

Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

Procedia PDF Downloads 392

Authors: Tobias Wissing, Peter Burggräf, Johannes Wagner

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Cost pressure, competitiveness and the increasing turbulence of globalized saturated markets has been the driver for a variety of research activities in the field of production planning and control (PPC) during the past decades. For some time past an increasing awareness for innovative technologies in terms of Industry 4.0 can be noticed. Although there are many promising approaches a solely installation of those smart solutions will not maximize the PPC performance. To accelerate the successful digital transformation the cooperation between employee and technology also has to be adapted. The existing processes and organizational structures might be not sufficient to maximize the utilization of technological innovations. This paper presents the key results of an extensive study which was conducted by the Laboratory for Machine Tools and Production Engineering (WZL) of the RWTH Aachen University to evaluate the current situation and examine the organizational readiness for this digital transformation.

Keywords: cyber-physical production system, digital transformation, industry 4.0, production planning and control

Procedia PDF Downloads 347

Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Nemanja Sarovic

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A key component of the drive train of electric vehicles is the lithium-ion battery system. Among various other components, such as the battery management system or the thermal management system, the battery system mostly consists of several cells which are integrated mechanically as well as electrically. Due to different vehicle concepts with regards to space, energy and power specifications, there is a variety of different battery systems. The corresponding assembly lines are specially designed for each battery concept. Minor changes to certain characteristics of the battery have a disproportionally high effect on the set-up effort in the form of high change-related costs. This paper will focus on battery systems which are made out of battery cells with a prismatic format. The product architecture and the assembly process will be analyzed in detail based on battery concepts of existing electric cars and key variety-causing drivers will be identified. On this basis, several measures will be presented and discussed on how to change the product architecture and the assembly process in order to reduce change-related costs.

Keywords: assembly, automotive industry, battery system, battery concept

Procedia PDF Downloads 296

Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Jan-Philip Ganser

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In the past years, the automotive industry has changed significantly. Innovative mobility concepts have become more important, and electric vehicles see a chance of replacing vehicles with combustion engines in the long term. However, the coming years will be characterized by coexistence. In this context, there are two possible production scenarios: One the one hand, electric vehicles could be manufactured in bespoke assembly lines. Concerning the uncertainty regarding sales figures development, this alternative boasts a high investment risk. Therefore, an integrated assembly building upon existing structures also seems a feasible solution. This empirical study aims at validating hypotheses concerning theoretical and practical challenges of the integrated production in the final assembly. In order to take a test of approaches of the research by analyzing censored feedback of professionals, these hypotheses are validated in the framework of an expert study. For this purpose, hypotheses have been generated on the basis of a requirements analysis and a concept specification. Thereupon, a list of question has been implemented and deduced from the hypotheses to execute an online- and written-survey and interviews with professionals. The interpretation and evaluation of the findings includes an inter-component comparison for the electric drivetrain. Furthermore, key drivers for a sufficient integrated product and process design are presented.

Keywords: automotive industry, final assembly, integrated manufacturing, product and process development

Procedia PDF Downloads 334

Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

Procedia PDF Downloads 314

Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

Procedia PDF Downloads 224

Authors: Asma Perveen, M. P. Jahan

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Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: micro holes, micro EDM, Ni Alloy, discharge energy

Procedia PDF Downloads 271

Authors: Mohammad Jamil Abd AlGhani

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The natural native antioxidants N,N-P-methyl phenyl acetone and N,N-phenyl acetone were isolated from the Iraqi crude oil region of Kirkuk by ion exchange and their structure was characterized by spectral and chemical analysis methods. Tetraline was used as a liquid hydrocarbon to detect the efficiency of isolated molecules at elevated temperature (393 K) that it has physicochemical specifications and structure closed to hydrocarbons fractionated from crude oil. The synthesized universal antioxidant 2,6-ditertiaryisobutyl-p-methyl phenol (Unol) with known stochiometric coefficient of inhibition equal to (2) was used as a model for comparative evaluation at the same conditions. Modified chemiluminescence method was used to find the amount of absorbed oxygen and the induction periods in and without the existence of isolated antioxidants molecules. The results of induction periods and quantity of absorbed oxygen during the oxidation process were measured by manometric installation. It was seen that at specific equal concentrations of N,N-phenyl acetone and N, N-P-methyl phenyl acetone in comparison with Unol at 393 K were with (2) and (2.5) times efficient than do Unol. It means that they had the ability to inhibit the formation of new free radicals and prevent the chain reaction to pass from the propagation to the termination step rather than decomposition of formed hydroperoxides.

Keywords: antioxidants, chemiluminescence, inhibition, Unol

Procedia PDF Downloads 197

Authors: Hung Nguyen, Norma Harrison

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This paper examines the role supply chain dependence as contingency factors which affect the effectiveness of different critical factors (in terms trust, information exchange and shared culture) in delivering supply chain satisfaction and financial performance. Using the data of 468 manufacturing firms in the Global Manufacturing Research Group, this study shows that supply chain dependence strengthens the positive relationship between shared culture & vision and supply chain satisfaction while dampens the relationship between trust and satisfaction. The study also demonstrates the direct positive effect of satisfaction on financial performance. Supply chain managers were advised to emphasize on the alignments of common understanding, codes, languages, common shared vision and similar cultures.

Keywords: information exchange, shared culture, satisfaction, supply chain dependence

Procedia PDF Downloads 379

Authors: Manish Gupta

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Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).

Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use

Procedia PDF Downloads 310

Authors: Irena Alperyte

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Since the regaining of the Independence, the Lithuanian state has been confronting an increasingly dramatic challenge because of the lack of funding sources dedicated to the film industries. During the Soviet times, Lithuanian film was under a total supervision of the Soviet functioners. This means that the responsibility of the state to make movies was of a monopolist character. The filmmakers’ community of the newly independent state needed to learn how to develop their fundraising skills, co-production and marketing techniques. Currently, Lithuanian film is experiencing a new phase concerning its funding: it is exploring the possibilities of motivating the public to invest in entertainment via crowd funding and crowd sourcing techniques and making these activities an alternative way of funding films. The paper aims at the exploration of the existing film financing practices in Lithuania and abroad and provides recommendations on how to improve the alternative Lithuanian film financing strategy via employing new possibilities, such as crowd funding and other alternative marketing tools. Objectives: 1) To examine the theories on creative industries and possibilities for their application. 2) To analyze the current situation in the film industry Lithuania. 3) To analyze the statistical data on movie theater visitors in Lithuania. 4) To discuss alternative options for film financing system. 5) To look through the alternative funding strategies tailored for Lithuanian film industry. 6) To propose recommendations for alternative funding strategies in Lithuanian film fundraising.

Keywords: creative industries, film, funding, fun theory

Procedia PDF Downloads 341

Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

Procedia PDF Downloads 231

Authors: Mohamed Elshal, Hazim El-Mounayri, Omar El-Mounayri

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Emergency department (ED) is considered as a complex system of interacting entities: patients, human resources, software and hardware systems, interfaces, and other systems. This paper represents a research for implementing a detailed Systems Engineering (SE) approach in a mid-size hospital in central Indiana. This methodology will be applied by “The Initiative for Product Lifecycle Innovation (IPLI)” institution at Indiana University to study and solve the crowding problem with the aim of increasing throughput of patients and enhance their treatment experience; therefore, the nature of crowding problem needs to be investigated with all other problems that leads to it. The presented SE methods are workflow analysis and systems modeling where SE tools such as Microsoft Visio are used to construct a group of system-level diagrams that demonstrate: patient’s workflow, documentation and communication flow, data systems, human resources workflow and requirements, leadership involved, and integration between ER different systems. Finally, the ultimate goal will be managing the process through implementation of an executable model using commercialized software tools, which will identify bottlenecks, improve documentation flow, and help make the process faster.

Keywords: systems modeling, ED operation, workflow modeling, systems analysis

Procedia PDF Downloads 175

Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

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The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

Procedia PDF Downloads 332

Authors: Moh’d A. AL-Shboul

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Recently, and due to Arab spring and terrorism around the globe, pushing and driving most governments potentially to harmonize their border measures particularly the regional and an international transit trade within and among Customs Unions. The main purpose of this study is to investigate and provide an insight for monitoring and controlling the trade supply chain within and among different countries by using technological advancement (i.e. an electronic tracking system, etc.); furthermore, facilitate the local and intra-regional trade among countries through reviewing the recent trends and practical implementation of an electronic transit traffic and cargo that related to customs measures by introducing and supporting some case studies of several international and landlocked transit trade countries. The research methodology employed in this study was described as qualitative by conducting few interviews with managers, transit truck drivers, and traders and reviewing the related literature to collect qualitative data from secondary sources such as statistical reports, previous studies, etc. The results in this study show that Jordan and other countries around the globe that used an electronic tracking system for monitoring transit trade has led to a significant reduction in cost, effort and time in physical movement of goods internally and crossing through other countries. Therefore, there is no need to escort transit trucks by customs staff; hence, the rate of escort transit trucks is reduced by more than ninety percent, except the bulky and high duty goods. Electronic transit traffic has been increased; the average transit time journey has been reduced by more than seventy percent and has led to decrease in rates of smuggling up to fifty percent. The researcher recommends considering Jordan as regional and international office for tracking electronically and monitoring the transit trade for many considerations.

Keywords: electronic tracking system, facilitation system, regional and international corridor, supply chain security, transit trade

Procedia PDF Downloads 495

Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan

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Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.

Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation

Procedia PDF Downloads 451

Authors: Zeynep Ayfer Bozat

Abstract:

As traditional innovation has already taken its place in managers’ to do lists; managers and companies have started to look for new ways to go beyond the traditional innovation. Because of its cost, traditional innovation became a burden for companies since they only use inner sources. Companies have intended to use outer innovation sources to decrease the innovation costs and Open Innovation has become a new solution for companies at this point. Crowdsourcing is a tool of Open Innovation and it consists of two words: Outsourcing and crowd. Crowdsourcing aims to benefit from the efforts and ideas of a virtual crowd via Internet technologies. In addition to that, crowdsourcing can help entrepreneurs to innovate and grow their businesses. They can crowd source anything they can use to grow their businesses: Ideas, investment, new business, new partners, new solutions, new policies, data, insight, marketing or talent. Therefore, the aim of the study is to be able to show some possible ways for entrepreneurs to benefit from crowdsourcing to expand or foster their businesses. In the study, the term crowdsourcing has been given in details and these possible ways have been searched and given.

Keywords: crowdsourcing, entrepreneurship, innovation, open innovation

Procedia PDF Downloads 289

Authors: Maya Arlini Puspasari, Shafira Karamina Alifah, Hardianto Iridiastadi

Abstract:

High mental workload can lead to fatigue and further result in decreased concentration and work performance. This study is conducted to see the effects of mental workload towards mental fatigue. Mental fatigue measurement was conducted at the first and the last 10 minutes of the working time using electroencephalogram, while mental workload measurement was conducted after the work is completed using the NASA-TLX questionnaire. The result shows that there is an increase in alpha band which indicates an increase in mental fatigue. This study also shows absolute alpha is more sensitive compared to the relative alpha. This study proves that there is a relationship between mental workload and mental fatigue although not relatively strong.

Keywords: mental workload, electroencephalogram, customer care agents, NASA-TLX

Procedia PDF Downloads 218

Authors: Bo Zhang, Ellen S. Wilschut, Dehlia M. C. Willemsen, Marieke H. Martens

Abstract:

With the rapid development of intelligent transportation systems, automated platooning of trucks is drawing increasing interest for its beneficial effects on safety, energy consumption and traffic flow efficiency. Nevertheless, one major challenge lies in the safe transition of control from the automated system back to the human drivers, especially when they have been inattentive after a long period of highly automated driving. In this study, we investigated driver take-over time after a system initiated request to leave the platooning system Virtual Tow Bar in a non-critical scenario. 22 professional truck drivers participated in the truck driving simulator experiment, and each was instructed to drive under three experimental conditions before the presentation of the take-over request (TOR): driver ready (drivers were instructed to monitor the road constantly), driver not-ready (drivers were provided with a tablet) and eye-shut. The results showed significantly longer take-over time in both driver not-ready and eye-shut conditions compared with the driver ready condition. Further analysis revealed hand movement time as the main factor causing long response time in the driver not-ready condition, while in the eye-shut condition, gaze reaction time also influenced the total take-over time largely. In addition to comparing the means, large individual differences can be found especially in two driver, not attentive conditions. The importance of a personalized driver readiness predictor for a safe transition is concluded.

Keywords: driving simulation, highly automated driving, take-over time, transition of control, truck platooning

Procedia PDF Downloads 247

Authors: Muhammad Liaqat, Hafiz Abdul Samad, Syed Talha Ali Hamdani, Yasir Nawab

Abstract:

In the current research, the four layers, orthogonal through the thickness, 2D woven, 3D fabric structure was modified to improve the impact resistance of 3D fabric reinforced composites. This was achieved by imparting the auxeticity into four layers through the thickness woven structure. A comparison was made between the standard and modified four layers through the thickness woven structure in terms of auxeticity, penetration and impact resistance. It was found that the modified structure showed auxeticity in both warp and weft direction. It was also found that the penetration resistance of modified sample was less as compared to the standard structure, but impact resistance was improved up to 6.7% of modified four layers through the thickness woven structure.

Keywords: 2D woven, 3D fabrics, auxetic, impact resistance, orthogonal through the thickness

Procedia PDF Downloads 334

Authors: Suwarsono, Ario S. Baskoro, Gandjar Kiswanto, Budiono

Abstract:

Friction Stir Welding (FSW) is a relatively new technique for joining metal. In some cases on aluminum joining, FSW gives better results compared with the arc welding processes, including the quality of welds and produces less distortion.FSW welding process for a light structure and thin materials requires small forces as possible, to avoid structure deflection. The joining process on FSW occurs because of melting temperature and compressive forces, the temperature generation of caused by material deformation and friction between the cutting tool and material. In this research, High speed rotation of spindle was expected to reduce the force required for deformation. The welding material was Aluminum A1100, with thickness of 0.4 mm. The tool was made of HSS material which was shaped by micro grinding process. Tool shoulder diameter is 4 mm, and the length of pin was 0.6 mm (with pin diameter= 1.5 mm). The parameters that varied were the plunge speed (2 mm/min, 3 mm/min, 4 mm/min). The tool speed is fixed at 33,000 rpm. Responses of FSSW parameters to analyze were Axial Force (Z-Force), Temperature and the Shear Strength of welds. Research found the optimum µFSSW parameters, it can be concluded that the most important parameters in the μFSSW process was plunge speed. lowest plunge speed (2 mm / min) causing the lowest axial force (110.40 Newton). The increases of plunge speed will increase the axial force (maximum Z-Farce= 236.03 Newton), and decrease the shear strength of welds.

Keywords: friction stir spot welding, aluminum A1100, plunge speed, axial force, shear strength

Procedia PDF Downloads 307