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Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; The depletion of natural resources has necessitated a better management of resources. One of the methods in this regard has been the reuse of materials and parts from products at the end of their life cycles, which requires a suitable configuration of disassembly systems for an effective operation. In this paper, we compare performances of two types of system configurations: standalone tear-down-stations and disassembly lines. These system configurations are tested for the disassembly of class 8 trucks to recover parts, which are then remanufactured or refurbished for reuse. A key feature of this product, and that of a used product in general that is disassembled, is the uncertainty of the processing time of a disassembly step. This uncertainty can lead to difficulties in proper line balancing, bottlenecks, inefficient use of resources, and generally, reduced throughput. In order to overcome these limitations, in this paper, we investigate the above disassembly facility configurations, and determine how their performances are affected by variability in operation time
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; When investigating different location and/or system designs the possible variables to take into consideration can differs between the alternatives. Different production system will have different optimal working conditions and hence should be compared with parameters suitable for the actual production system. When planning production and calculating production costs the batch size is of high interest. Based on a manufacturing part cost model, this paper will present a new model, close connected to the production system, integrating production performance, set-up times, material costs, material handling costs and tied capital, giving the production economic optimal batch size. The aim is to give companies a model for determining the economic optimal batch size in order to use this knowledge to make strategic decisions regarding production planning. Mathematical simulations are performed to analyse the differences in result from the developed model and Wilson's existing standard method for calculating the economic order quantity, hence to verify the importance of making an in-depth analysis, taking the production system into consideration. The advantage of the developed model is the usage of production costs based on variable batch sizes, giving a more accurate outcom
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; Automated manufacturing systems are traditionally hierarchically controlled by a centralized control system. This makes the system deterministic and therefore easier to be optimized for efficient manufacturing of a large number of one single product. However, in modern manufacturing the demand for customization and high-mix, low-volume production is growing. This move is strengthened by the acceptation of 3D printers for industrial products and new technologies that make it easier to reconfigure manufacturing systems. Hence, new paradigms like agile manufacturing, which focuses on a shorter time to market, and flexibility are becoming more important to industry. One of these paradigms is grid manufacturing, which uses a group (grid) of autonomous manufacturing systems that can be controlled as a heterarchy (where every system is autonomous and equal to each other). In this paper the goal is to determine, by simulation, if it is useful to develop a hierarchical entity to reserve some of these systems to partly break the heterarchy. This way it would be easier to optimize performance of manufacturing batch products. To fully utilize a grid it would be of interest to be able to use both hierarchical control, where a hierarchical entity reserves specific manufacturing systems, and heterarchical control, where a product can negotiate with any manufacturing system to complete the next step. Since both hierarchical and heterarchical control have advantages this paper investigates the possibility to dynamically choose one of both strategies, depending on the current deman
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; European economies have been deeply affected by different crises. The impact of the economic crisis on enterprises is now recognized by everybody. Enterprises are fighting to pull through the present situation and are seeking to be prepared for the post-crisis phase. Enterprises need to reorganize in order to be better adapted to this situation and to integrate new dimensions in their development. GRAI Methodology is one of the three main methodologies (with PERA and CIMOSA) for enterprise modelling. In this paper, the concepts of GRAIMOD a tool for supporting GRAI Methodology is presented. Then a zoom is made on an example related to multi-product companies for defining a reference model according to enterprises of this activity domain. For improving this enterprise performance, a multi-criteria analysis was used by combining quality, cost, lead time but also carbon management, social societal and environmental dimensions
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; Recent concerns over the use of and reliance on fossil fuels have stimulated research efforts in identifying, developing, and selecting alternative energy sources. Biofuels represent a promising replacement for conventional fuels for heating and mobility applications, however, variability in the quality and availability of biomass feedstocks greatly affect the utility of biofuels due to the impact on cost and life cycle environmental performance. Thus, methods for mitigating these potential impacts are needed when selecting biomass feedstock suppliers. In the research herein, the selection of the best supplier is investigated for a biomass supply chain (BSC) network by including both qualitative and quantitative factors. Most existing supplier-selection methods consider four steps: (1) Problem formulation, where Decision-Tree Analysis is applied as a qualitative method for defining the type of biomass feedstock materials for biofuel production, (2) Criteria definition, (3) Preevaluation of qualified suppliers, which employs the Support Vector Machine (SVM) method, and (4) Final selection. Integration of machine learning (ML) techniques and a mathematical programming model is undertaken with this method to select the most appropriate feedstock suppliers. It is shown that integrating ML and mathematical programming methods offers a promising approach to supplementing existing supplier selection methods for biomass-to-biofuel supply chain
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; To build the first LNG ship in china, production efficiency and cost pose an urgent problem when designs its layout. Considering the real logistics types in insulation box line for LNG ship, a multi-line facility layout problem is first proposed. Then, a genetic algorithm with combinational coding schema and crossover operators is put forward to solve the problem. In this way, both sequence and coordinate of machine can be coded. Accordingly, partial and arithmetic crossovers are used to minimize the logistics cost of box line. In addition, 27 machines with rectangle contours in box pre- processing area are optimized using this algorithm. Through a case study using logistics and size data, the result shows that this genetic algorithm is effectiv
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; By running life tests at higher stress levels than normal operating conditions, accelerated life testing quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. To conduct an accelerated life test efficiently with constrained resources in practice, several decision variables such as the allocation proportions and stress durations should be determined carefully at the design stage. These decision variables affect not only the experimental cost but also the estimate precision of the lifetime parameters of interest. In this work, under the constraint that the total experimental cost does not exceed a pre-specified budget, the optimal decision variables are determined based on C/D/A-optimality criteria. In particular, the constant-stress and step-stress accelerated life tests are considered with the exponential failure data under time constraint as well. We illustrate the proposed methods using a case study, and under a given budget constraint, the efficiencies of these two stress loading schemes are compared in terms of the ratio of optimal objective functions based on the information matri
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; During the past few years, developing painless needles or patches to replace traditional hypodermic needles has been investigated. Since micromachining can be used to construct a high density metallic micropillar array, we propose to use a biocompatible metal oxide, such as Al2O3 and TiO2, as an alternative material for fabricating arrays of microneedles. In this study, we fabricated an anodic aluminum oxide (AAO) covered Al micro-indent array using electrochemical and mechanical micromachining. We demonstrate use of a nanoindenter to make pyramidal indentions on Al surface in order to produce a female microneedle array mold. We also performed melting injection to fill AAO template with ultra-high molecular weight polyethylene (UHMWPE) to produce UHMWPE nanotubes. The microneedle array provides a 3-D structure that possesses several hundred times more surface area than a traditional nanotube template. This suggests that a medical-grade polymer microneedle array can potentially be formed for more applications. This 3-D microneedle array device can be used not only for painless injection or extraction, but also for storage, highly sensitive detection, drug delivery, and microelectrode
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; Healthcare Services across the globe are going through a very challenging phase under the current economic uncertainty. Among many other public services which are under the financial scrutiny healthcare services is the most affected one. This is primarily attributed to severe funding cuts and reduced headcounts that have resulted in long waiting queues for a variety of medical treatments. The delay in treatments due to the lack of resources have caused huge outcry among the general public. Therefore, healthcare services are under immense pressure to reduce their inefficiencies and improve their operational performance. Inspired by the on-going challenges faced by the healthcare service organisations, this research aims to study the role of discrete-event simulation modelling tool in reducing the waiting time issues. This research investigates waiting time issue faced by the physiotherapy department of an Irish hospital. The data for the simulation study was collected through personal visits to the physiotherapy department. As a first step towards the simulation modelling, a process map of the department was constructed. Thereafter, simulation model was developed and tested for alternative scenarios to tackle the waiting time problem. The result shows that simulation modelling can be a very effective tool in resolving the waiting time issue by providing managerial decision makers vital information on how to use their resources efficientl
Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014
No full textPaper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Includes bibliographical references; Electrical energy is directly linked to society prosperity across the globe; much of this due to the diverse machining and manufacturing processes. Keeping pace with the high energy demand growth will require constant efforts on investment and research to explore new alternatives. This paper outlines the application of multiple response optimization in order to find a balance in the tradeoff between production time and energy consumption in 5- axis impeller rough machining. It is well known that higher speed reduces the machining time but increases the energy consumption, and vice versa. By utilizing response surface methodology (RSM) together with desirability function it is possible to find a quantitative form of the relationship between outputs and the independent factors involved in the process. Four independent factors were selected, namely, spindle speed, feed rate, depth and width of cut. The responses are consumed energy and machining time. The results showed that selecting an appropriate feed rate is crucial to balance the tradeoffs between energy and time. Spindle speed is the major factor that consumes more energy, while width of cut is the most influential factor on machining tim