Develop an autonomous product-based reconfigurable manufacturing system

With the ever-emerging market including mass customization and product variety, reconfigurable manufacturing systems (RMS) have been presented as the solution. A manufacturing system that combines the benefits of the two classic manufacturing systems to increase responsiveness and reduce production time and costs. To cope with the lack of physical systems, an RMS system have been built at UiT Narvik. Today, both reconfiguration and deciding layout must be executed manually by a human. A task that is both incredibly time consuming and far from optimal. A method of automating the layout generation and thus the manufacturing system is presented in this thesis. To the author’s knowledge such experiment has not been performed previously. Layouts is generated with a NSGA-II algorithm in Python by minimizing objectives from a developed mathematical model. The results have been tested with a MiR-100 mobile robot placing five modules in two different layouts. The results have been compared with a digital visualization for validation. In addition to the visualization, videos of the physical system's automated layout generation are presented. The results concludes that the method both generates feasible layouts as well as enhancing the automation of the system

Overview of Dynamic Facility Layout Planning as a Sustainability Strategy

[EN] The facility layout design problem is significantly relevant within the business operations strategies framework and has emerged as an alternate strategy towards supply chain sustainability. However, its wide coverage in the scientific literature has focused mainly on the static planning approach and disregarded the dynamic approach, which is very useful in real-world applications. In this context, the present article offers a literature review of the dynamic facility layout problem (DFLP). First, a taxonomy of the reviewed papers is proposed based on the problem formulation current trends (related to the problem type, planning phase, planning approach, number of facilities, number of floors, number of departments, space consideration, department shape, department dimensions, department area, and materials handling configuration); the mathematical modeling approach (regarding the type of model, type of objective function, type of constraints, nature of market demand, type of data, and distance metric), and the considered solution approach. Then, the extent to which recent research into DFLP has contributed to supply chain sustainability by addressing its three performance dimensions (economic, environmental, social) is described. Finally, some future research guidelines are provided.This research was funded by the Spanish Ministry of Science, Innovation and Universities Project CADS4.0, grant number RTI2018-101344-B-I00; and the Valencian Community ERDF Programme 2014-2020, grant number IDIFEDER/2018/025.Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2020). Overview of Dynamic Facility Layout Planning as a Sustainability Strategy. Sustainability. 12(19):1-16. https://doi.org/10.3390/su12198277S1161219Ghassemi Tari, F., & Neghabi, H. (2015). A new linear adjacency approach for facility layout problem with unequal area departments. Journal of Manufacturing Systems, 37, 93-103. doi:10.1016/j.jmsy.2015.09.003Kheirkhah, A., Navidi, H., & Messi Bidgoli, M. (2015). Dynamic Facility Layout Problem: A New Bilevel Formulation and Some Metaheuristic Solution Methods. IEEE Transactions on Engineering Management, 62(3), 396-410. doi:10.1109/tem.2015.2437195Altuntas, S., & Selim, H. (2012). Facility layout using weighted association rule-based data mining algorithms: Evaluation with simulation. Expert Systems with Applications, 39(1), 3-13. doi:10.1016/j.eswa.2011.06.045Ku, M.-Y., Hu, M. H., & Wang, M.-J. (2011). Simulated annealing based parallel genetic algorithm for facility layout problem. International Journal of Production Research, 49(6), 1801-1812. doi:10.1080/00207541003645789Navidi, H., Bashiri, M., & Messi Bidgoli, M. (2012). A heuristic approach on the facility layout problem based on game theory. International Journal of Production Research, 50(6), 1512-1527. doi:10.1080/00207543.2010.550638Hosseini-Nasab, H., Fereidouni, S., Fatemi Ghomi, S. M. T., & Fakhrzad, M. B. (2017). Classification of facility layout problems: a review study. The International Journal of Advanced Manufacturing Technology, 94(1-4), 957-977. doi:10.1007/s00170-017-0895-8Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360-387. doi:10.1108/09600030810882816Carter, C. R., & Washispack, S. (2018). Mapping the Path Forward for Sustainable Supply Chain Management: A Review of Reviews. Journal of Business Logistics, 39(4), 242-247. doi:10.1111/jbl.12196Roy, V., Schoenherr, T., & Charan, P. (2018). The thematic landscape of literature in sustainable supply chain management (SSCM). International Journal of Operations & Production Management, 38(4), 1091-1124. doi:10.1108/ijopm-05-2017-0260Barbosa-Póvoa, A. P., da Silva, C., & Carvalho, A. (2018). Opportunities and challenges in sustainable supply chain: An operations research perspective. European Journal of Operational Research, 268(2), 399-431. doi:10.1016/j.ejor.2017.10.036Tonelli, F., Evans, S., & Taticchi, P. (2013). Industrial sustainability: challenges, perspectives, actions. International Journal of Business Innovation and Research, 7(2), 143. doi:10.1504/ijbir.2013.052576Sánchez-Flores, R. B., Cruz-Sotelo, S. E., Ojeda-Benitez, S., & Ramírez-Barreto, M. E. (2020). Sustainable Supply Chain Management—A Literature Review on Emerging Economies. Sustainability, 12(17), 6972. doi:10.3390/su12176972Ford, S., & Despeisse, M. (2016). Additive manufacturing and sustainability: an exploratory study of the advantages and challenges. Journal of Cleaner Production, 137, 1573-1587. doi:10.1016/j.jclepro.2016.04.150Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425. doi:10.1016/j.psep.2018.05.009Khuntia, J., Saldanha, T. J. V., Mithas, S., & Sambamurthy, V. (2018). Information Technology and Sustainability: Evidence from an Emerging Economy. Production and Operations Management, 27(4), 756-773. doi:10.1111/poms.12822Roy, S., Das, M., Ali, S. M., Raihan, A. S., Paul, S. K., & Kabir, G. (2020). Evaluating strategies for environmental sustainability in a supply chain of an emerging economy. Journal of Cleaner Production, 262, 121389. doi:10.1016/j.jclepro.2020.121389Morais, D. O. C., & Silvestre, B. S. (2018). Advancing social sustainability in supply chain management: Lessons from multiple case studies in an emerging economy. Journal of Cleaner Production, 199, 222-235. doi:10.1016/j.jclepro.2018.07.097Stindt, D. (2017). A generic planning approach for sustainable supply chain management - How to integrate concepts and methods to address the issues of sustainability? Journal of Cleaner Production, 153, 146-163. doi:10.1016/j.jclepro.2017.03.126MOSLEMIPOUR, G., LEE, T. S., & LOONG, Y. T. (2017). Performance Analysis of Intelligent Robust Facility Layout Design. Chinese Journal of Mechanical Engineering, 30(2), 407-418. doi:10.1007/s10033-017-0073-9Emami, S., & S. Nookabadi, A. (2013). Managing a new multi-objective model for the dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 68(9-12), 2215-2228. doi:10.1007/s00170-013-4820-5Al Hawarneh, A., Bendak, S., & Ghanim, F. (2019). Dynamic facilities planning model for large scale construction projects. Automation in Construction, 98, 72-89. doi:10.1016/j.autcon.2018.11.021Pournaderi, N., Ghezavati, V. R., & Mozafari, M. (2019). Developing a mathematical model for the dynamic facility layout problem considering material handling system and optimizing it using cloud theory-based simulated annealing algorithm. SN Applied Sciences, 1(8). doi:10.1007/s42452-019-0865-xTuranoğlu, B., & Akkaya, G. (2018). A new hybrid heuristic algorithm based on bacterial foraging optimization for the dynamic facility layout problem. Expert Systems with Applications, 98, 93-104. doi:10.1016/j.eswa.2018.01.011Moslemipour, G., Lee, T. S., & Rilling, D. (2011). A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems. The International Journal of Advanced Manufacturing Technology, 60(1-4), 11-27. doi:10.1007/s00170-011-3614-xTebaldi, L., Bigliardi, B., & Bottani, E. (2018). Sustainable Supply Chain and Innovation: A Review of the Recent Literature. Sustainability, 10(11), 3946. doi:10.3390/su10113946Tseng, M.-L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resources, Conservation and Recycling, 141, 145-162. doi:10.1016/j.resconrec.2018.10.009Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. doi:10.1016/j.jclepro.2019.119869Boar, A., Bastida, R., & Marimon, F. (2020). A Systematic Literature Review. Relationships between the Sharing Economy, Sustainability and Sustainable Development Goals. Sustainability, 12(17), 6744. doi:10.3390/su12176744Novais, L., Maqueira, J. M., & Ortiz-Bas, Á. (2019). A systematic literature review of cloud computing use in supply chain integration. Computers & Industrial Engineering, 129, 296-314. doi:10.1016/j.cie.2019.01.056Masi, D., Day, S., & Godsell, J. (2017). Supply Chain Configurations in the Circular Economy: A Systematic Literature Review. Sustainability, 9(9), 1602. doi:10.3390/su9091602Zavala-Alcívar, A., Verdecho, M.-J., & Alfaro-Saiz, J.-J. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability, 12(16), 6300. doi:10.3390/su12166300Li, K., Rollins, J., & Yan, E. (2017). Web of Science use in published research and review papers 1997–2017: a selective, dynamic, cross-domain, content-based analysis. Scientometrics, 115(1), 1-20. doi:10.1007/s11192-017-2622-5Kulturel-Konak, S., & Konak, A. (2014). A large-scale hybrid simulated annealing algorithm for cyclic facility layout problems. Engineering Optimization, 47(7), 963-978. doi:10.1080/0305215x.2014.933825Madhusudanan Pillai, V., Hunagund, I. B., & Krishnan, K. K. (2011). Design of robust layout for Dynamic Plant Layout Problems. Computers & Industrial Engineering, 61(3), 813-823. doi:10.1016/j.cie.2011.05.014Peng, Y., Zeng, T., Fan, L., Han, Y., & Xia, B. (2018). An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem. Discrete Dynamics in Nature and Society, 2018, 1-8. doi:10.1155/2018/1529058McKendall, A. R., & Hakobyan, A. (2010). Heuristics for the dynamic facility layout problem with unequal-area departments. European Journal of Operational Research, 201(1), 171-182. doi:10.1016/j.ejor.2009.02.028Yang, C.-L., Chuang, S.-P., & Hsu, T.-S. (2010). A genetic algorithm for dynamic facility planning in job shop manufacturing. The International Journal of Advanced Manufacturing Technology, 52(1-4), 303-309. doi:10.1007/s00170-010-2733-0Abedzadeh, M., Mazinani, M., Moradinasab, N., & Roghanian, E. (2012). Parallel variable neighborhood search for solving fuzzy multi-objective dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 65(1-4), 197-211. doi:10.1007/s00170-012-4160-xGuan, X., Dai, X., Qiu, B., & Li, J. (2012). A revised electromagnetism-like mechanism for layout design of reconfigurable manufacturing system. Computers & Industrial Engineering, 63(1), 98-108. doi:10.1016/j.cie.2012.01.016Jolai, F., Tavakkoli-Moghaddam, R., & Taghipour, M. (2012). A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations. International Journal of Production Research, 50(15), 4279-4293. doi:10.1080/00207543.2011.613863Kia, R., Baboli, A., Javadian, N., Tavakkoli-Moghaddam, R., Kazemi, M., & Khorrami, J. (2012). Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing. Computers & Operations Research, 39(11), 2642-2658. doi:10.1016/j.cor.2012.01.012McKendall, A. R., & Liu, W.-H. (2012). New Tabu search heuristics for the dynamic facility layout problem. International Journal of Production Research, 50(3), 867-878. doi:10.1080/00207543.2010.545446Hosseini-Nasab, H., & Emami, L. (2013). A hybrid particle swarm optimisation for dynamic facility layout problem. International Journal of Production Research, 51(14), 4325-4335. doi:10.1080/00207543.2013.774486Kaveh, M., Dalfard, V. M., & Amiri, S. (2013). A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints. Neural Computing and Applications, 24(5), 1179-1190. doi:10.1007/s00521-013-1339-5KIA, R., JAVADIAN, N., PAYDAR, M. M., & SAIDI-MEHRABAD, M. (2013). A SIMULATED ANNEALING FOR INTRA-CELL LAYOUT DESIGN OF DYNAMIC CELLULAR MANUFACTURING SYSTEMS WITH ROUTE SELECTION, PURCHASING MACHINES AND CELL RECONFIGURATION. Asia-Pacific Journal of Operational Research, 30(04), 1350004. doi:10.1142/s0217595913500048Mazinani, M., Abedzadeh, M., & Mohebali, N. (2012). Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm. The International Journal of Advanced Manufacturing Technology, 65(5-8), 929-943. doi:10.1007/s00170-012-4229-6Samarghandi, H., Taabayan, P., & Behroozi, M. (2013). Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings. The International Journal of Advanced Manufacturing Technology, 67(9-12), 2701-2715. doi:10.1007/s00170-012-4685-zYu-Hsin Chen, G. (2013). A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems. International Journal of Production Economics, 142(2), 362-371. doi:10.1016/j.ijpe.2012.12.012Bozorgi, N., Abedzadeh, M., & Zeinali, M. (2014). Tabu search heuristic for efficiency of dynamic facility layout problem. The International Journal of Advanced Manufacturing Technology, 77(1-4), 689-703. doi:10.1007/s00170-014-6460-9CHEN, G. Y.-H., & LO, J.-C. (2014). DYNAMIC FACILITY LAYOUT WITH MULTI-OBJECTIVES. Asia-Pacific Journal of Operational Research, 31(04), 1450027. doi:10.1142/s0217595914500274Hosseini, S., Khaled, A. A., & Vadlamani, S. (2014). Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem. Neural Computing and Applications, 25(7-8), 1871-1885. doi:10.1007/s00521-014-1678-xKia, R., Khaksar-Haghani, F., Javadian, N., & Tavakkoli-Moghaddam, R. (2014). Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm. Journal of Manufacturing Systems, 33(1), 218-232. doi:10.1016/j.jmsy.2013.12.005Nematian, J. (2014). A robust single row facility layout problem with fuzzy random variables. The International Journal of Advanced Manufacturing Technology, 72(1-4), 255-267. doi:10.1007/s00170-013-5564-yPourvaziri, H., & Naderi, B. (2014). A hybrid multi-population genetic algorithm for the dynamic facility layout problem. Applied Soft Computing, 24, 457-469. doi:10.1016/j.asoc.2014.06.051Derakhshan Asl, A., & Wong, K. Y. (2015). Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization. Journal of Intelligent Manufacturing, 28(6), 1317-1336. doi:10.1007/s10845-015-1053-5Li, L., Li, C., Ma, H., & Tang, Y. (2015). An Optimization Method for the Remanufacturing Dynamic Facility Layout Problem with Uncertainties. Discrete Dynamics in Nature and Society, 2015, 1-11. doi:10.1155/2015/685408Ulutas, B., & Islier, A. A. (2015). Dynamic facility layout problem in footwear industry. Journal of Manufacturing Systems, 36, 55-61. doi:10.1016/j.jmsy.2015.03.004Zarea Fazlelahi, F., Pournader, M., Gharakhani, M., & Sadjadi, S. J. (2016). A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 230(12), 2264-2274. doi:10.1177/0954405415615728Hosseini, S. S., & Seifbarghy, M. (2016). A novel meta-heuristic algorithm for multi-objective dynamic facility layout problem. RAIRO - Operations Research, 50(4-5), 869-890. doi:10.1051/ro/2016057Pourvaziri, H., & Pierreval, H. (2017). Dynamic facility layout problem based on open queuing network theory. European Journal of Operational Research, 259(2), 538-553. doi:10.1016/j.ejor.2016.11.011Tayal, A., & Singh, S. P. (2016). Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach for facility layout problem. Annals of Operations Research, 270(1-2), 489-514. doi:10.1007/s10479-016-2237-xKumar, R., & Singh, S. P. (2017). A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems. Engineering Optimization, 49(11), 1848-1867. doi:10.1080/0305215x.2016.1274205Liu, J., Wang, D., He, K., & Xue, Y. (2017). Combining Wang–Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. European Journal of Operational Research, 262(3), 1052-1063. doi:10.1016/j.ejor.2017.04.002Vitayasak, S., Pongcharoen, P., & Hicks, C. (2017). A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm. International Journal of Production Economics, 190, 146-157. doi:10.1016/j.ijpe.2016.03.019Xiao, Y., Xie, Y., Kulturel-Konak, S., & Konak, A. (2017). A problem evolution algorithm with linear programming for the dynamic facility layout problem—A general layout formulation. Computers & Operations Research, 88, 187-207. doi:10.1016/j.cor.2017.06.025Li, J., Tan, X., & Li, J. (2018). Research on Dynamic Facility Layout Problem of Manufacturing Unit Considering Human Factors. Mathematical Problems in Engineering, 2018, 1-13. doi:10.1155/2018/6040561Vitayasak, S., & Pongcharoen, P. (2018). Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design. Expert Systems with Applications, 98, 129-152. doi:10.1016/j.eswa.2018.01.005Wei, X., Yuan, S., & Ye, Y. (2019). Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm. Production & Manufacturing Research, 7(1), 109-124. doi:10.1080/21693277.2019.1602486Kulturel-Konak, S. (2007). Approaches to uncertainties in facility layout problems: Perspectives at the beginning of the 21st Century. Journal of Intelligent Manufacturing, 18(2), 273-284. doi:10.1007/s10845-007-0020-1Sharma, P., & Singhal, S. (2016). Implementation of fuzzy TOPSIS methodology in selection of procedural approach for facility layout planning. The International Journal of Advanced Manufacturing Technology, 88(5-8), 1485-1493. doi:10.1007/s00170-016-8878-8Bukchin, Y., & Tzur, M. (2014). A new MILP approach for the facility process-layout design problem with rectangular and L/T shape departments. International Journal of Production Research, 52(24), 7339-7359. doi:10.1080/00207543.2014.930534Meller, R. D., Kirkizoglu, Z., & Chen, W. (2010). A new optimization model to support a bottom-up approach to facility design. Computers & Operations Research, 37(1), 42-49. doi:10.1016/j.cor.2009.03.018Feng, J., & Che, A. (2018). Novel integer linear programming models for the facility layout problem with fixed-size rectangular departments. Computers & Operations Research, 95, 163-171. doi:10.1016/j.cor.2018.03.013Allahyari, M. Z., & Azab, A. (2018). Mathematical modeling and multi-start search simulated annealing for unequal-area facility layout problem. Expert Systems with Applications, 91, 46-62. doi:10.1016/j.eswa.2017.07.049Ahmadi, A., Pishvaee, M. S., & Akbari Jokar, M. R. (2017). A survey on multi-floor facility layout problems. Computers & Industrial Engineering, 107, 158-170. doi:10.1016/j.cie.2017.03.015Drira, A., Pierreval, H., & Hajri-Gabouj, S. (2007). Facility layout problems: A survey. Annual Reviews in Control, 31(2), 255-267. doi:10.1016/j.arcontrol.2007.04.001Grobelny, J., & Michalski, R. (2017). A novel version of simulated annealing based on linguistic patterns for solving facility layout problems. Knowledge-Based Systems, 124, 55-69. doi:10.1016/j.knosys.2017.03.001Hathhorn, J., Sisikoglu, E., & Sir, M. Y. (2013). A multi-objective mixed-integer programming model for a multi-floor facility layout. International Journal of Production Research, 51(14), 4223-4239. doi:10.1080/00207543.2012.75348

Antennas using left handed transmission lines

The research described in this thesis is concerned with the analysis and design of conventional wire antenna types, dipoles and loops, based on the left-handed transmission line approach. The left handed antennas have a unique feature that the wavelength of the induced current becomes shorter with decreasing frequency. The left handed transmission line concept can be extended to construct reduced-size dipole or loop antennas in the VHF frequency band. The use of higher order modes allows orthogonal polarisation to be obtained, which is thought to be a feature unique to these antennas. Efficiency is a key parameter of left handed antennas as the heavy left handed loading increases the resistive loss. A study of the efficiency of small dipole antennas loaded with a left-handed transmission line is specially described, and the comparison with conventional inductive loading dipoles. In a low order mode, the efficiency of L-loading dipole is better with low number of unit cell. If the number of cell increases, CL-loading presents comparable and even better performance. In a high mode the meandered left handed dipole gives the best efficiency due to the phase distribution, presenting orthogonal polarization as well. The optimized dipole loaded with parallel plate capacitors and spiral inductors presents the best performance in impedance and efficiency, even better than the conventional inductive loading. A planar loop antenna using a ladder network of left handed loading is also presented. Various modes can be obtained in the left handed loop antenna. The zero order mode gives rise to omnidirectional patterns in the plane of the loop, with good efficiency. By loading the loop with active components, varactors, a tunable left handed loop antenna with a switchable radiation pattern is implemented. The loop gives an omnidirectional pattern with a null to z axis while working in an n = 0 mode and can switch to a pattern with a null at phi = 45° in the plane of the loop in an n = 2 mode

Energy Sustainability in Changeable Manufacturing Systems

University of Minnesota M.S.E.M. thesis. October 2017. Major: Engineering Management. Advisor: Tarek AlGeddawy. 1 computer file (PDF); vi, 76 pages.In a dynamic production environment, not only the product portfolio and demands are varying throughout a multi-period horizon, but also the economic aspects of the environment, such as energy pricing, change with time. The thesis of this work states that energy price fluctuation has a considerable optimizable effect on manufacturing system structural and operational decisions. This work progressively presents three novel linear mathematical models to optimize that effect. In the first step, a novel basic linear mixed integer mathematical model is proposed to maximize the sustainability of changeable manufacturing systems (MSCM) on the operational level. The model focuses on three factors, which are the change pattern in energy prices throughout the day, the transportation cost of jobs between machines, and the setup cost of each machine, which is dependent on the job sequence. The model output is a system configuration plan, indicating arrangement of machines in the system, and the sequence of jobs, which need to be produced on one day. It is solved by CPLEX solver in GAMS software for nine different problem sizes. The new LMI model finds the optimum configuration plan and job sequence in a reasonable time, which illustrates the efficiency and practicality of the proposed model. In the second step, a new linear mathematical model is presented to maximize the sustainability of changeable manufacturing systems on the structural level (MSSCM) by selecting the layout reconfiguration and material handling system in each period. It is solved by CPLEX solver in GAMS software to analyze influence of energy pricing and demand fluctuation on system convertibility and scalability, which can affect layout configuration selection. In the last step, a novel mixed integer linear mathematical model (MILTEC) is presented to maximize the sustainability of RMS on both the structural and operational levels. The system configuration planning in each period of time consists of machines layout and task scheduling which are the most interrelated decisions on the system level. The novel aspect of the presented model is the consideration of energy sustainability concurrently with system configuration and task scheduling decisions in a changing manufacturing environment. The model objective is to minimize total costs of energy consumption, system reconfiguration throughout the planning horizon, and part transportation between machines, which all depend on fluctuations in energy pricing and demand during different periods of time. Several case studies are solved by GAMS Software using the branch-and-bound technique to illustrate the performance of the presented model and analyze its sensitivity to the volatility of energy pricing and demand and their effect on system changeability. An efficient genetic algorithm (GA) has been developed to solve the proposed model in larger scale due to its NP-hardness (non-deterministic polynomial-time hardness). The results are compared to GAMS to validate the developed GA. It shows that the proposed GA finds near-optimal solutions in 70% shorter time than GAMS on average. Different examples are also solved resulting in negligible differences between solutions in several runs of each example to verify the efficiency of the proposed GA

INNOVATIVE SIMULATION AND OPTIMIZATION STUDIES ON GRID SYSTEM FOR TRANSSHIPMENT TERMINAL

Ph.DDOCTOR OF PHILOSOPH

A simulated annealing algorithm to determine a group layout and production plan in a dynamic cellular manufacturing system

In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented model different from the previous studies. These include: 1) the variable number of cells, 2) machine depot keeping idle machines, and 3) integration of cell formation (CF), GL and PP decisions in a dynamic environment. The objective is to minimize the total costs (i.e., costs of intra-cell and inter-cell material handling, machine relocation, machine purchase, machine overhead, machine processing, forming cells, outsourcing and inventory holding). Two numerical examples are solved by the GAMS software to illustrate the results obtained by the incorporated features. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in compare to the GAMS software. The obtained results show that the quality of the solutions obtained by SA is entirely satisfactory in compare to GAMS software based on the objective value and computational time, especially for large-sized problems

Operating Coupled VO-Based Oscillators for Solving Ising Models

Coupled nano-oscillators are attracting increasing interest because of their potential to perform computation efficiently, enabling new applications in computing and information processing. The potential of phase transition devices for such dynamical systems has recently been recognized. This paper investigates the implementation of coupled VO2-based oscillator networks to solve combinatorial optimization problems. The target problem is mapped to an Ising model, which is solved by the synchronization dynamics of the system. Different factors that impact the probability of the system reaching the ground state of the Ising Hamiltonian and, therefore, the optimum solution to the corresponding optimization problem, are analyzed. The simulation-based analysis has led to the proposal of a novel Second-Harmonic Injection Locking (SHIL) schedule. Its main feature is that SHIL signal amplitude is repeatedly smoothly increased and decreased. Reducing SHIL strength is the mechanism that enables escaping from local minimum energy states. Our experiments show better results in terms of success probability than previously reported approaches. An experimental Oscillatory Ising Machine (OIM) has been built to validate our proposal.</p

Analysis of Product Architectures of Pin Array Technologies for Tactile Displays

Refreshable tactile displays based on pin array technologies have a significant impact on the education of children with visual impairments, but they are prohibitively expensive. To better understand their design and the reason for the high cost, we created a database and analyzed the product architectures of 67 unique pin array technologies from literature and patents. We qualitatively coded their functional elements and analyzed the physical parts that execute the functions. Our findings highlight that pin array surfaces aim to achieve three key functions, i.e., raise and lower pins, lock pins, and create a large array. We also contribute a concise morphological chart that organises the various mechanisms for these three functions. Based on this, we discuss the reasons for the high cost and complexity of these surface haptic technologies and infer why larger displays and more affordable devices are not available. Our findings can be used to design new mechanisms for more affordable and scalable pin array display systems

Advances on Mechanics, Design Engineering and Manufacturing III

This open access book gathers contributions presented at the International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing (JCM 2020), held as a web conference on June 2–4, 2020. It reports on cutting-edge topics in product design and manufacturing, such as industrial methods for integrated product and process design; innovative design; and computer-aided design. Further topics covered include virtual simulation and reverse engineering; additive manufacturing; product manufacturing; engineering methods in medicine and education; representation techniques; and nautical, aeronautics and aerospace design and modeling. The book is organized into four main parts, reflecting the focus and primary themes of the conference. The contributions presented here not only provide researchers, engineers and experts in a range of industrial engineering subfields with extensive information to support their daily work; they are also intended to stimulate new research directions, advanced applications of the methods discussed and future interdisciplinary collaborations