Progress in Material Handling Research: 2012

Table of Content

Bench v2 Optimization

The client is a furniture production company located in Woodstock, GA. One of their products is a bench used for café style settings in a major United States bank chain. The client defined their requirements with a prioritized list of wants, needs, and problems that they encouraged us to accomplish. The number one item on their list is that the benches are heavy and awkward to turn, flip over, and otherwise manufacture and maneuver, a potential safety hazard for workers. After reviewing several options for improving the company’s manufacturing process, Finite Element Analysis [FEA] was determined as the team’s highest impact method for assisting the company. FEA tests a product without costly machinery or numerous sample products, “[allowing] the removal of the indefiniteness before the manufacturing and making the decisions related to manufacturing in a more healthy and economical manner” (Koç, et al., 2011). The AutoCAD model of the bench was acquired from the client. Slight alterations were then made to the model to make it capable of undergoing stress testing, including drilling holes and adding bolts and screws. Then, eight alternate models were made, ranging from using plywood instead of Birch wood to less supports and larger holes in the interior. Stress was applied in three evolving ways as the team strived for a realistic method: one point force in the center, two point forces on top of the interior support, and two pressures applied to a 144 square inch square. One important note is that “the intention of performing FEA is not to eliminate the real tests but rather to reduce the time for a product to pass through the process” (Rundgren and Wörmke, 2011). Using Safety Factor as the primary metric for determining if a model is viable, the team came to the conclusion that either the baseline model or the baseline interior replaced with Plywood were the most viable options

Hybrid approach of discrete event simulation integrated with location search algorithm in a cells assignment problem: a case study

[EN] This paper presents a case study describing a cell assignment problem in an assembly facility. These cells receive parts from external suppliers, and sort and sequence these parts to feed the final assembly line. Therefore, to each cell are associated important inbound and outbound flows generating hundreds of material handling equipment movements along the facility, impacting the traffic density and causing eventually safety issues in the plant. Following an important plant redesign, cells have been relocated, and the plant managers need to decide how to manage the new logistic flows. To that aim, a hybrid approach encompassing mathematical optimization and discrete event simulation (DES) is proposed. This approach allows us to reduce complexity by decomposing the design into two phases. The first phase deals with the problem of generating cell¿s assignment alternatives by using a heuristic method to find good quality solutions. Then, a DES software is used to dynamically evaluate the performance of the solutions with respect to operational features such as traffic congestion and intensity. This second phase provides interesting managerial insights on the manufacturing system from both quantitative and qualitative aspects related to in-plant safety and traffic.Saez-Mas, A.; García Sabater, JJ.; García Sabater, JP.; Maheut, J. (2020). Hybrid approach of discrete event simulation integrated with location search algorithm in a cells assignment problem: a case study. Central European Journal of Operations Research. 28(1):125-142. https://doi.org/10.1007/s10100-018-0548-5S125142281Anjos MF, Vieira MVC (2017) Mathematical optimization approaches for facility layout problems: the state-of-the-art and future research directions. Eur J Oper Res 261(1):1–16. https://doi.org/10.1016/j.ejor.2017.01.049Battini D, Boysen N, Emde S (2013) Just-in-time supermarkets for part supply in the automobile industry. J Manag Control 24(2):209–217. https://doi.org/10.1007/s00187-012-0154-yBenjaafar S (2002) Modeling and analysis of congestion in the design of facility layouts. Manag Sci 48(5):679–704. https://doi.org/10.1287/mnsc.48.5.679.7800Board TR (2010) Highway capacity manual. Environmental ProtectionBoysen N, Emde S, Hoeck M, Kauderer M (2015) Part logistics in the automotive industry: decision problems, literature review and research agenda. Eur J Oper Res 242(1):107–120. https://doi.org/10.1016/j.ejor.2014.09.065Caputo AC, Pelagagge PM, Salini P (2015) Modeling errors in kitting processes for assembly lines feeding. IFAC Proc Vol (IFAC PapersOnline) 48(3):338–344. https://doi.org/10.1016/j.ifacol.2015.06.104Centobelli P, Cerchione R, Murino T (2016) Layout and material flow optimization in digital factory. Int J Simul Model 15(2):223–235. https://doi.org/10.2507/IJSIMM15(2)3.327Dehghanimohammadabadi M, Keyser TK (2017) Intelligent simulation: integration of SIMIO and MATLAB to deploy decision support systems to simulation environment. Simul Model Pract Theory 71:45–60. https://doi.org/10.1016/j.simpat.2016.08.007Ficko M, Palcic I (2013) Designing a layout using the modified triangle method, and genetic algorithms. Int J Simul Model 12(4):237–251. https://doi.org/10.2507/IJSIMM12(4)3.244Gamberi M, Manzini R, Regattieri A (2009) An new approach for the automatic analysis and control of material handling systems: integrated layout flow analysis (ILFA). Int J Adv Manuf Technol 41(1–2):156–167. https://doi.org/10.1007/s00170-008-1466-9Gould O, Colwill J (2015) A framework for material flow assessment in manufacturing systems. J Ind Prod Eng 32(1):55–66. https://doi.org/10.1080/21681015.2014.1000403Hasda RK, Bhattacharjya RK, Bennis F (2016) Modified genetic algorithms for solving facility layout problems. Int J Interact Des Manuf (IJIDeM) 11(3):1–13. https://doi.org/10.1007/s12008-016-0362-zImran M, Kang C, Hae Lee Y, Zaib J, Aziz H (2017) Cell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm. Comput Ind Eng 105:123–135. https://doi.org/10.1016/j.cie.2016.12.028Iqbal M, Hashmi MSJ (2001) Design and analysis of a virtual factory layout. J Mater Process Technol 118(1–3):403–410. https://doi.org/10.1016/S0924-0136(01)00908-6Jainury SM, Ramli R, Ab Rahman MN, Omar A (2014) Integrated Set Parts Supply system in a mixed-model assembly line. Comput Ind Eng 75(1):266–273. https://doi.org/10.1016/j.cie.2014.07.008Kanduc T, Rodic B (2016) Optimisation of machine layout using a force generated graph algorithm and simulated annealing. Int J Simul Model 15(2):275–287. https://doi.org/10.2507/IJSIMM15(2)7.335Kang J (2001) A new trend of parts supply system in Korean automobile industry; the case of the modular production system at Hyundai Motor Company. In: Proceedings of the fifth Russian-Korean international symposium on science and technology, 2001. KORUS '01. IEEE, Tomsk, Russia, Russia. https://doi.org/10.1109/KORUS.2001.975268Kim J, Yu G, Jang YJ (2016) Semiconductor FAB layout design analysis with 300-mm FAB data: “is minimum distance-based layout design best for semiconductor FAB design?”. Comput Ind Eng 99:330–346. https://doi.org/10.1016/j.cie.2016.02.012Krishnan KK, Jithavech I, Liao H (2009) Mitigation of risk in facility layout design for single and multi-period problems. Int J Prod Res 47(21):5911–5940. https://doi.org/10.1080/00207540802175337Ku M-Y, Hu MH, Wang M-J (2011) Simulated annealing based parallel genetic algorithm for facility layout problem. Int J Prod Res 49(6):1801–1812. https://doi.org/10.1080/00207541003645789Kulturel-Konak S (2017) A matheuristic approach for solving the dynamic facility layout a matheuristic approach for problem solving the dynamic facility layout problem. Proc Comput Sci 108(June):1374–1383. https://doi.org/10.1016/j.procs.2017.05.234Leveson N (2004) A new accident model for engineering safer systems. Saf Sci 42(4):237–270. https://doi.org/10.1016/S0925-7535(03)00047-XNegahban A, Smith JS (2014) Simulation for manufacturing system design and operation: literature review and analysis. J Manuf Syst 33(2):241–261. https://doi.org/10.1016/j.jmsy.2013.12.007Prajapat N, Tiwari A (2017) A review of assembly optimisation applications using discrete event simulation. Int J Comput Integr Manuf 30(2–3):215–228. https://doi.org/10.1080/0951192X.2016.1145812Saez-Mas A, Garcia-Sabater JP, Morant-Llorca J (2018) Using 4-layer architecture to simulate product and information flows in manufacturing. Int J Simul Model 17(1):30–41. https://doi.org/10.2507/IJSIMM17(1)408Seebacher G, Winkler H, Oberegger B (2015) In-plant logistics efficiency valuation using discrete event simulation. Int J Simul Model 14:60–70. https://doi.org/10.2507/IJSIMM14(1)6.289Singh RR, Sharma SPK (2006) A review of different approaches to the facility layout problems. Int J Adv Manuf Technol 30(5–6):425–433. https://doi.org/10.1007/s00170-005-0087-9Tompkins J, White J, Bozer Y, Tanchoco J (2003) Facilities planning. Wiley, New YorkTugnoli A, Khan F, Amyotte P, Cozzani V (2008) Safety assessment in plant layout design using indexing approach: implementing inherent safety perspective. Part 1—guideword applicability and method description. J Hazard Mater 160(1):100–109. https://doi.org/10.1016/j.jhazmat.2008.02.089Zhang M, Batta R, Nagi R (2009) Modeling of workflow congestion and optimization of flow routing in a manufacturing/warehouse facility. Manag Sci 55(2):267–280. https://doi.org/10.1287/mnsc.1080.0916Zhou F, AbouRizk SM, AL-Battaineh H (2009) Optimisation of construction site layout using a hybrid simulation-based system. Simul Model Pract Theory 17(2):348–363. https://doi.org/10.1016/j.simpat.2008.09.011Zhuo L, Chua Kim Huat D, Wee KH (2012) Scheduling dynamic block assembly in shipbuilding through hybrid simulation and spatial optimisation. Int J Prod Res 50(20):5986–6004. https://doi.org/10.1080/00207543.2011.639816Zupan H, Herakovic N, Starbek M (2016) hybrid algorithm based on priority rules for simulation of workshop production. Int J Simul Model 15(1):29–41. https://doi.org/10.2507/IJSIMM15(1)3.31

A structured method for the optimization of the existing last mile logistic flows

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceIn a fast-moving world some business exists due to the interconnectivity between countries. This happens because transports are able to reach the other side of the globe within few days and without being too expensive compensating the lower costs of production and competitive advantages. This is true for well-organized and big supply chains but even them can benefit from integration with disconnected and more complex supply chain as it is the case of e-commerce chains. The transaction of small packages from online shopping required in a totally distinct country of the place of production have very specific characteristics as they are spot flows, hard to predict and to combine with other goods owing to the fact that the destination of flows are different every time and it is not always worth it to dedicate a transport for such a small goods value and in addition most times, logistics have to answer to some challenging marketing requirements meaning they have time windows to fulfil. Last mile is a big part of logistics transports and is one important part of it that can really help companies having better prices and revenues for their transports. Last mile solutions need to be easy to implement and really have to translate in quick gains to logistic companies that are largely reducing their margins to increase competitiveness. In this context, the study aims to investigate and define a method following design Research Methodology hopping to draw some innovative solutions for the problem of last mile. In this respect, the work developed intends to study the solutions already implemented and extract insights on how distribution is made and how to maximize last mile profit through the mature of an algorithm able to reduce inefficiencies in a simple way without having to wiggle too much the structure of businesses as resources of last mile service providers are understood to be scarce as many last mile companies are small sized and running under big logistic players. The solution aims to attain the different marketing requirements exactly as it was defined without having to compromise anything but still being able to make good profit margins and perhaps make room for new opportunities to arise that previously were not profitable

Augmenting the distribution of goods from warehouses in dynamic demand environments using intelligent agents

Warehouses are being impacted by increasing e-commerce and omni-channel commerce. Future innovation may predominantly involve automation but many warehouses remain manually operated. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment. Standard operational process is paramount to warehouse operational control but inflexible processes don’t allow for a dynamic response to real-time operational constraints. The growth of IoT sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents an intelligent agent framework for basic warehouse management systems that is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework

Throughput Analysis of Manual Order Picking Systems with Congestion Consideration

Throughput in manual order picking systems with narrow aisles suffers from congestion as pickers cannot pass each other. Only few models incorporate congestion but they have very strict assumptions. In this work, queueing theory is used to analyze systems with traversal routing as well as different storage policies. The models are able to estimate throughput for many alternative designs in a relatively short amount of time. New guidelines for narrow-­aisle order picking systems are introduced

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

A new approximate evaluation method for two-echelon inventory systems with emergency shipments

We consider the control of repairable spare parts in a network consisting of a central warehouse, a central repair facility, and multiple local warehouses. Demands for spare parts occur at the local warehouses. If a local warehouse is out of stock, then an arriving demand is satisfied by an emergency delivery from the central warehouse or the central repair facility. Such emergency shipments are common practice for networks that support technical systems with high downtime costs, and it is important to take them into account when the inventory is optimized. Our main contribution consists of the development of a new approximate evaluation method. This method gives accurate approximations for the key performance measures, as we show via numerical analysis. The method is also fast and thus can easily be incorporated in existing (greedy) heuristic optimization methods. Our method outperforms the approximate evaluation method of Muckstadt and Thomas (1980), as we also show via the numerical analysis. Finally, we show that the performance of the system is rather insensitive to the leadtime distribution of the repairs at the central repair facility, which implies that our method works well for generally distributed repair leadtimes

RFID in the warehouse:a literature analysis (1995-2010) of its applications, benefits, challenges and future trends

Radio Frequency Identification (RFID) has been identified as a crucial technology for the modern 21st century knowledge-based economy. Some businesses have realised benefits of RFID adoption through improvements in operational efficiency, additional cost savings, and opportunities for higher revenues. RFID research in warehousing operations has been less prominent than in other application domains. To investigate how RFID technology has had an impact in warehousing, a comprehensive analysis of research findings available from articles through leading scientific article databases has been conducted. Articles from years 1995 to 2010 have been reviewed and analysed with respect to warehouse operations, RFID application domains, benefits achieved and obstacles encountered. Four discussion topics are presented covering RFID in warehousing focusing on its applications, perceived benefits, obstacles to its adoption and future trends. This is aimed at elucidating the current state of RFID in the warehouse and providing insights for researchers to establish new research agendas and for practitioners to consider and assess the adoption of RFID in warehousing functions