24th International Conference on Flexible Automation and Intelligent Manufacturing

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12588/880

Program and abstracts of the 142 papers accepted for presentation at the FAIM 2014 International Conference, held in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio; Conference Chair: F. Frank Chen

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3-D biocompatible microneedle arrays with nanoporous surface
(DEStech Publications, Inc., 2014) Chen, Po Chun; Hsieh, Sheng Jen
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 microelectrodes.
3D printing with reusable voxels: A faster and greener future
(DEStech Publications, Inc., 2014) Stipe, Audrey; Wan, HungDa
Many of the applications in the 3D printing market have been for manufacturing prototypes in an inexpensive and relatively fast manner. Today, 3D printers make this possible by no longer having to use third party manufacturers. For all of the purposes that 3D printing is used, many of them, such as 3D geographic maps, visual art, model support structures, dioramas, prototypes, do not require a high precession. Furthermore, for such applications, there is no need for permanent prints. Due to the advancements in technology, and its residual pollution from waste, there is a need for a ‘greener’ method to 3-D printing. To meet this demand, we propose MIRV (Mechanically Interchangeable and Reusable Voxels), for voxel-based printing, a new method for 3-D printing. MIRV uses pre-built volumetric elements to build 3-D objects, by employing specially designed reusable and interchangeable building elements in voxel-based printing. When there is no longer need for the printed object, the object can be disassembled and the parts reused. This eliminates any wasted material. Meanwhile, all building elements of each layer are displaced in one simultaneous motion. Thus, the overall time to build a print can be significantly reduced compared to other 3D printing technologies.
A Bayesian network based decision support system
(DEStech Publications, Inc., 2014) Chen, Wen-Hsin; Wang, Wei-Hua Andrew
In this highly dynamic environment, data and information are rapidly changing in time. For a decision support system, to capture continuum data and then to extract knowledge from data is in high demand. Our research work focus on developing a systematic approach for discovering causal relations among data and dynamic updating upon to the varying goals. Bayesian network is a powerful tool for representing knowledge and tackling the above inquires. In this research, the entropy-based searching mechanism designed on Bayesian network is adopted to learn the structure of a goal-specific mission. Link strength and connection strength are the measures for selecting links to be added and subtracted. However, these two measures are the relative measures instead of absolute thresholds. Initially, we designed a link/connection strength selecting method for possible adjacency matrices in tabu searching. In the second phase, we used a homogeneity test to ensure the quality of the learned structure. The results of this study will be an important stepping stone to attain the learning requirements of designing, building, and operating effective decision support systems under dynamic environment.
A constructive cooperative coevolutionary algorithm applied to press line optimisation
(DEStech Publications, Inc., 2014) Glorieux, Emile; Svensson, Bo; Danielsson, Fredrik; Lennartson, Bengt
Simulation-based optimisation often considers computationally expensive problems. Successfully optimising such large scale and complex problems within a practical timeframe is a challenging task. Optimisation techniques to fulfil this need to be developed. A technique to address this involves decomposing the considered problem into smaller subproblems. These subproblems are then optimised separately. In this paper, an efficient algorithm for simulation-based optimisation is proposed. The proposed algorithm extends the cooperative coevolutionary algorithm, which optimises subproblems separately. To optimise the subproblems, the proposed algorithm enables using a deterministic algorithm, next to stochastic genetic algorithms, getting the flexibility of using either type. It also includes a constructive heuristic that creates good initial feasible solutions to reduce the number of fitness calculations. The extension enables solving complex, computationally expensive problems efficiently. The proposed algorithm has been applied on automated sheet metal press lines from the automotive industry. This is a highly complex optimisation problem due to its non-linearity and high dimensionality. The optimisation problem is to find control parameters that maximises the line's production rate. These control parameters determine velocities, time constants, and cam values for critical interactions between components. A simulation model is used for the fitness calculation during the optimisation. The results show that the proposed algorithm manages to solve the press line optimisation problem efficiently. This is a step forward in press line optimisation since this is to the authors' knowledge the first time a press line has been optimised efficiently in this way.
A fast and accurate recognition system for flexible grasping of electronic goods
(DEStech Publications, Inc., 2014) Woegerer, Christian; Rooker, M.; Angerer, Alfred; Kopf, Ch.; Pichler, A.
Automated packaging is becoming more and more interesting for various production sites even in Europe. However, in many companies the packaging process can only handle a limited amount of products. This leads to a very inflexible packaging and a bottle neck in the production. Most of the time for new products, the packaging system needs to be modified. One of the main components in an automated packaging process is the recognition and then the grasping of the objects that need to be packed. For different products mostly a different gripping system is required. In this paper, solutions from a research project are presented which enables the recognizing as a basis for flexible grasping of different products. These solutions includes a flexible pose recognition for different objects by a low cost system based on Kinect or or Asus Xtion cameras.
A foresight study on future trends influencing material consumption and waste generation in production
(DEStech Publications, Inc., 2014) Shahbazi, Sasha; Sjödin, Carina; Bjelkemyr, Marcus; Wiktorsson, Magnus
There are boundless upcoming factors that influence future of material waste in production. This broad range of factors needs to be scanned, categorized and analyzed in a structured way. This paper by a foresight study, aims to give an insight and increase awareness about external macro-level future trends concerning raw material consumption and waste generation in production. A limited pilot study indicated that technological forecasting and some reaction upon obvious trends are being taken, although in an ad hoc manner and without structured tools. However, political influences, economic visions and social-cultural shifts were seldom or never discussed. External macro trends and tendencies were examined through PEST analysis to identify potentials and opportunities influencing strategic decisions and innovation initiatives. It is vital to understand the whole picture of possible changes and not only considering the technological trends, but also other relevant development areas that might affect production in different ways.
A framework to support the lifecycle of virtual manufacturing enterprises
(DEStech Publications, Inc., 2014) Azevedo, Américo; Ferreira, Filipe; Faria, José
This paper proposes a framework to support the full virtual manufacturing enterprise lifecycle from the creation to the operation and dissolution. The paper will show how the framework supports the activities involved in the setup of virtual manufacturing enterprise, how to run it and which tools are needed. Three main perspectives are considered: knowledge and information, methodology and Technology. A business case analysis is then presented in order to understand the framework applicability to the development of collaborative business opportunities in an engineer-to-order and one-of-a-kind production environments, which is common to a large number of SMEs.
A model for integrating shipment consolidation and pricing decisions in perishable product supply chains
(DEStech Publications, Inc., 2014) Chen, Jing; Dong, Ming, Ph. D.; Chen, F. Frank
This paper focuses on a simple perishable product supply chain with a vendor and multiple retailers. These retailers, densely dispersed in a distribution zone, are sensitive to price, delivery time and product quality. With the aim of optimizing vendor's average expected profit during a shipment consolidation cycle, an analytical model is proposed for this problem. The upper unbound expressions of optimal time policy and fresh-keeping cost are given based on a certain range of time parameter. Then our theoretical findings are verified by using a numerical case. Some useful managerial insights are obtained based on analyzing the sensitivity of this model on major parameters.
A modular flexible scalable and reconfigurable system for manufacturing of microsystems based on additive manufacturing and e-printing
(DEStech Publications, Inc., 2014) Woegerer, Christian; Plasch, Matthias; Heidl, Wolfgang; Dickerhof, Markus; Kimmig, Daniel; Scholz, Steffen; Adamietz, Raphael; Iseringhausen, Tobias
Generative manufacturing technologies are gaining more and more of importance as key enabling technologies in future manufacturing, especially when a flexible scalable manufacturing of small medium series of customized parts is required. The paper describes a new approach for design manufacturing of complex three dimensional components building on a combination of laminated objects manufacturing and e-printing technologies. The micro component is made up of stacks of functionalized layers of polymer films. The concept is currently developed further in the project SMARTLAM, funded by the European Commission. The manufacturing system is based on a modular approach which enables the manufacturing of different small size batches with different modules. Different modules can be combined by defined Hardware and software interfaces. Avoiding time consumable and difficult programming caused by manufacturing a new product a Function-Block Runtime (FORTE) executes generated control application platform-independently and coordinates component module functionalities. The control system will integrate all processes as well as the base platform with features far beyond ordinary PLC systems. One aspect is the use of process data out of the data acquisition system to simulate and optimize the processes. These results are incorporated into the main machine control system. Another aspect is the vision system for flexible quality control and closed-loop positioning control with visual serving. The paper shows the first example of manufacturing technologies and demonstrates the control system approach by the example of the control system for alignment of different stacks.
A multi-objective model for solar industry closed-loop supply chain by using particle swarm optimization
(DEStech Publications, Inc., 2014) Chen, YiWen; Wang, Li-Chih; Chen, Tzu-Li; Wang, Allen; Cheng, Chen-Yeng
Solar energy industry is an exceptional industry which desperately relies on government support and subsidy. The demand is decreasing since the government support reduction, moreover, the dramatically increase China solar manufacturers have great impact on solar product price in recent years. Because the insufficient supply of silicon materials carries the issue of solar cell recycle, the solar manufacturer must design a sustainable closed-loop supply chain (CLSC) to recycle and reuse the retired solar cells to achieve 3E (Effective, Efficient, Environmental; 3E) objectives. This paper studies an integrated CLSC network design problem with sustainable concerns in the solar energy industry. We are interested in the logistics flows, capacity expansion and technology investments of existing and potential facilities in the multi-stage CLSC. Therefore, a deterministic multi-objective mixed integer programming model capturing the tradeoffs between the total cost and the carbon dioxide (CO2) emission is developed to tackle the multi-stage CLSC design problem from both economic and environmental perspectives. Due to the multi-objective nature and computational complexity, a multi-objective particle swarm optimization (MOPSO) with novel flow assignment algorithms is designed to search non-dominated /Pareto CLSC design solutions. Finally, a case study of crystalline solar energy industry is illustrated to verify the proposed multi-objective CLSC design model and demonstrate the efficiency of the developed MOPSO algorithm in terms of computational time and solution quality.
A new stochastic simulation optimization methodology for supply chain inventory optimization with imperfect quality items
(DEStech Publications, Inc., 2014) Duan, Qinglin; Liao, T. Warren
This paper proposes a new stochastic simulation optimization methodology that integrates meta-heuristic with sample average approximation for supply chain inventory optimization under supply uncertainty. The supply uncertainty specifically considered is quality imperfection/deviation modelled as a discrete or continuous distribution function. In order to approximate the expected total inventory-related cost, sufficient samples of quality deviations are generated and then the corresponding sample average function is optimized by a newly developed hybrid meta-heuristic algorithm. The proposed methodology and its individual components are presented. Numerical results of a single-distributor-multiple-retailer supply chain system with each adopting the (s, S) replenishment policy indicate that the proposed methodology is capable of obtaining high quality supply chain inventory policies with percentage optimality gap within 0.01%.
A novel engineering method for the power flow assessment in servo-actuated automated machinery
(DEStech Publications, Inc., 2014) Oliva, Enrico; Berselli, Giovanni; Pellicciari, Marcello
Multipurpose and programmable servo-actuated mechanisms may be envisaged as the key technology for increasing flexibility and re-configurability of modern automated machinery. Unfortunately, based on the current state-of-the-art, these mechatronic devices are extremely flexible but generally energy intensive, thus compromising the overall system sustainability. Nonetheless, the system power consumption can be partially reduced if energy optimality is introduced as a design goal along with the global productivity. Naturally, as a first step towards the practical implementation of any energy-optimality criterion, the end user should be capable of predicting the system power flow.
A performance estimation framework for complex manufacturing systems
(DEStech Publications, Inc., 2014) Almeida, António; Azevedo, Américo
To cope with today market challenges and guarantee adequate competitive performances, companies have been decreasing their products life cycles, as well as increasing the number of product varieties and respective services available on their portfolio. Consequently, it has been observed an increasing in complexity in all domains, from product and process development, factory and production planning to factory operation and management. This reality implies that organizations should be able to compile and analyze, in a more agile way, the immense quantity of data generated, as well as apply the suitable tools that, based on this knowledge, will supports stakeholders to take decision envisioning future performance scenarios. Aiming to pursuing this vision was developed a proactive performance management framework, composed by a performance thinking methodology and a performance estimation engine. While the methodology developed is an extension of the Systems Dynamics approach for complex systems' performance management, on the other hand, the performance estimation engine is an innovative IT solution responsible by capturing lagging indicators, as well as estimate future performance behaviors. As main outcome of this research work, it was demonstrated that following a systematic and formal approach, it is possible to identify the feedback loops and respective endogenous and exogenous variables responsible by hindering the systems behavior, in terms of a specific KPI. Moreover, based on this enhanced understanding about manufacturing systems behavior, it was proved to be possible to estimate with high levels of confidence not only the present but also future performance behavior. From the combination of both qualitative and quantitative approaches, it was explored an enhanced learning machine algorithm capable to specify the curve of behavior, characteristic from a specific manufacturing system, and thus estimate future behaviors based on a set of leading indicators. In order to achieve these objectives, both Neural Networks and Unscented Kalman Filter for nonlinear estimation were applied. Important results and conclusions were extracted from an application case performed within a real automotive plant, which demonstrated the feasibility of this research towards a more proactive management approach.
A techno-health study of the use of cutting fluids and future alternatives
(DEStech Publications, Inc., 2014) Shokrani, Alborz; Dhokia, Vimal; Newman, Stephen T.
The health issues associated with exposure to cutting fluids is an increasing concern among occupational health researchers. However, this issue has been overlooked in manufacturing enterprises from engineering prospective. The aim of this paper is to provide a multi-disciplinary review of the health issues related to the use of cutting fluids in machining companies and provides some alternative solutions through a series of case studies. The studies indicated that minimum quantity lubrication, biostable oils, cryogenic machining and dry machining are potential alternatives to traditional flood cooling with potential to improve machinability.
AC-pulse modulated electrohydrodynamic (EHD) direct printing of conductive micro silver tracks for micro-manufacturing
(DEStech Publications, Inc., 2014) Qin, Hantang; Wei, Chuang; Dong, Jingyan; Lee, Yuan-Shin
This paper presents a direct fabrication of highly conductive silver tracks with sub-20 µm microstructures on glass substrates using electrohydrodynamic jet printing (EHD) based on alternative current (AC) voltage. A new AC-modulated EHD technique is presented and used in directly printing by generating a fine jet through a large electrical potential between the nozzle and substrate. In the presented technique of AC-modulated EHD, when charge accumulates on the ink meniscus at the nozzle, a fine jet down to nano scale can be generated. The variables of fabrication process, like plotting speeds, curing temperature and number of layers, were investigated to achieve reliable jet printing of conductive silver tracks. Topography and electrical property of printed tracks were characterized and verified. By using modulated AC-pulsed voltage, we are capable of printing high resolution continuous patterns on insulating substrates. In the study, we successfully applied EHD for fabrication of highly conductive silver tracks on glass substrate. It was the first time that sub-20 µm silver tracks were demonstrated with resistivity about 3.16 times than bulk silver. The presented technique can be used for direct printing of micro scale electronic circuits and devices.
Adaptive robotic control in cloud environments
(DEStech Publications, Inc., 2014) Adamson, Goran; Wang, Lihui, 1959-; Holm, Magnus; Moore, Philip
Many of the applications in the 3D printing market have been for manufacturing prototypes in an inexpensive and relatively fast manner. Today, 3D printers make this possible by no longer having to use third party manufacturers. For all of the purposes that 3D printing is used, many of them, such as 3D geographic maps, visual art, model support structures, dioramas, prototypes, do not require a high precession. Furthermore, for such applications, there is no need for permanent prints. Due to the advancements in technology, and its residual pollution from waste, there is a need for a ‘greener’ method to 3-D printing. To meet this demand, we propose MIRV (Mechanically Interchangeable and Reusable Voxels), for voxel-based printing, a new method for 3-D printing. MIRV uses pre-built volumetric elements to build 3-D objects, by employing specially designed reusable and interchangeable building elements in voxel-based printing. When there is no longer need for the printed object, the object can be disassembled and the parts reused. This eliminates any wasted material. Meanwhile, all building elements of each layer are displaced in one simultaneous motion. Thus, the overall time to build a print can be significantly reduced compared to other 3D printing technologies.
Advanced 3D robot simulation for flexible interactive manual robot guidance—an eRobotics approach
(DEStech Publications, Inc., 2014) Kaigom, Eric Guiffo; Rossmann, Jürgen
Manual robot guidance is an intuitive approach to teach robots with human’s skills in the loop. It is particularly useful to manufacturers because of the high flexibility and low programming efforts. However, manual robot guidance requires compliance control that is generally not available in industrial robots. We address this issue with a simulation-based approach. The dynamics of the robot are replicated and its motion is controlled on the simulator, which is enriched with a joint admittance controller driven in real time with external joint torques sensed during interaction with the physical robot. We then virtually transfer the admittance capability by sending back the simulated compliant joint position to the real robot to enable manual guidance. Experimental case studies are provided to illustrate the practical performance and usefulness of the proposed smooth bidirectional transition between 3D simulation and reality, as pursued by eRobotics to address complex issues in industrial automation.
Advantages of using hybrid manufacturing platforms to realize decentralized manufacture
(DEStech Publications, Inc., 2014) Kendrick, Blake A.; Dhokia, Vimal; Newman, Stephen T.
Manufacturing has traditionally been the domain of centralised factories, set-up and optimised to make a sole product or product-range. Whilst the in-house efficacy of such systems has been greatly improved due to lean six-sigma methodologies, the wider scale distribution and supply system has undergone little to no transformation over the past century. Previous research pertaining to distributed manufacture, cloud-manufacture and reconfigurable systems has provided several decentralised models using traditional manufacturing capabilities. Though to date they have not been fully realised due to practical limitations. This paper outlines the scope for hybrid manufacturing platforms â€“ using a plurality of processes on a single motion platform, to manufacture products in a decentralised network. Social, economic and environmental ramifications of adopting such a system under particular use cases, such as in shops, community areas or in individual households, are highlighted. The combination of several key processes, including measurement, will allow users to manufacture parts with minimal intervention. A move to personal fabrication would allow greater personalisation and convenience for the end user
An approach of one-item-multiple-code for logistics management in international power generation EPC projects
(DEStech Publications, Inc., 2014) Wu, Shan-shan; Wang, De-yuan
Engineering-Procurement-Construction project type is widely used in the industry of power generation development, and logistics management has been playing an important role in the execution of especially international power generation projects. Logistics in the area of power generation industry can be a very complicated system, typically involving many subcontractors related to logistical activities, requiring countless operations to be completed as well as deals with numerous interfaces between neighboring operations. With the objective of efficient and effective management and control of the whole logistics process, the paper proposes a "one-item-multiple-code" approach to realize the transparency and traceability of logistics management.
An artificial neural network based on adaptive resonance theory for fault classification on an automated assembly machine
(DEStech Publications, Inc., 2014) Fernando, Heshan; Surgenor, Brian
An unsupervised artificial neural network (ANN) based on the ART2-A algorithm is compared to a rule-based method for fault classification on an automated assembly machine. Machine data is collected using three greyscale sensors and two redundant limit switches for 11 different operating conditions. Descriptive features are extracted from the raw data and two data sets, each containing 180 feature vectors, are created for testing both methods. The first data set contains 'real' feature vectors obtained from the original sensor signals, and the second data set contains 'simulated' feature vectors obtained by scaling the 'real' feature vectors. The second data set is used to test the performance of each system when variations are present in the input space. During testing, the rule-based system correctly classified 98.3% of all feature vectors, but its classification thresholds needed to be manually adjusted to accommodate the 'simulated' data set. The ART2-A network perfectly classified the 'real' data set into 13 clusters, and then correctly classified the 'simulated' data into the same 13 clusters without any modification to the algorithm's tuning parameter, vigilance.

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