515,622 research outputs found

    The limitations of market driven sustainability: The case of environmental management systems for food production in Australia.

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    Environmental Management Systems (EMSs) address environmental risks in supply chains and certification of environmental claims. Governments supporting EMSs have encouraged producers to respond to anticipated consumer environmental concerns. Attempts at implementing EMSs have rarely been in direct response to market demand but are usually farmer organisation driven - to forestall increased regulation. In Australia, consumer demand for foods produced to environmentally sustainable standards is minimal because consumers don't believe these products offer special benefits. EMS implementation is expensive and onerous; and the products require a market premium. Food consumers have difficulty differentiating the terms organic, environmentally-friendly, and sustainably-produced in food labelling.EMS, environmental marketing, sustainable food production, eco-labelling, Environmental Economics and Policy,

    Implementing Management Systems and Demand Driven MRP concepts: A Project Based Learning experience in Industrial Organization Engineering

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    [EN] This research work presents an experience of the Faculty of Engineering of Mondragon Unibertsitatea using Project Based Learning (PBL) with the students of 4th semester of Bachelor's Degree in Industrial Organization Engineering (IOE). The PBL delved into the concepts developed in the subjects of Management Systems and Production Logistics. The project was contextualized in a company that produced parts for the automotive sector. Teams of students implemented a management system that enabled the efficient management of materials and the production process using tools such as Demand Driven MRP (DDRMP). As a result, they had to solve the proposed problem, develop a simulation and choose the proposal that best met the needs of the company. In order to assess PBL performance a survey was carried out. The results confirmed that the experience was positive since the achieved knowledge provided a meaningful learning experience for the students, while facilitating the development of both technical and transversal competences. http://ocs.editorial.upv.es/index.php/HEAD/HEAD18Kortabarria, A.; Elizburu, A. (2018). Implementing Management Systems and Demand Driven MRP concepts: A Project Based Learning experience in Industrial Organization Engineering. Editorial Universitat Politècnica de València. 543-550. https://doi.org/10.4995/HEAD18.2018.8033OCS54355

    Assessment of Farmer Preferences for Cattle Traits in Cattle Production Systems of Kenya

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    The urgent need to improve livestock productivity in sub-Saharan Africa in order to keep pace with expected increases in demand for meat and milk is very topical. Breed improvement provides key entry points for increasing productivity in cattle populations. However, there are tendencies for breed improvement programs to focus on single, market driven traits such as milk or meat production in isolation of environmental constraints and broader livestock system functions which cattle assume in developing countries. This potentially leads to genotypes that are not well adapted to the environment and not capable of performing the multiple roles that cattle assume in cattle production systems of developing countries. In developing countries, many important functions of livestock are embedded in non-tradable traits that are neither captured in economic analysis nor considered in livestock improvement programs. This study evaluates preferences of cattle keepers in pastoral and crop- livestock systems of selected sites in Kenya for various cattle traits, focusing attention on trypanotolerance and employing choice modelling techniques. These systems are characterized by low input management, harsh environmental conditions and prevalence of various cattle diseases. Trypanosomosis is a serious disease constraint in these systems. The results indicate that farmer preferences for cattle traits are influenced by various factors including cultural practices, production system characteristics and environmental conditions, especially in relation to disease prevalence and availability of cattle feeds.cattle production system, trait preferences, choice experiment, Kenya, Livestock Production/Industries, D11, C35, Q26,

    Data-driven reconfigurable supply chain design and inventory control

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    In this dissertation, we examine resource mobility in a supply chain that attempts to satisfy geographically distributed demand through resource sharing, where the resources can be inventory and manufacturing capacity. Our objective is to examine how resource mobility, coupled with data-driven analytics, can result in supply chains that without customer service level reduction blend the advantages of distributed production-inventory systems (e.g., fast fulfillment) and centralized systems (e.g., economies of scale, less total buffer inventory, and reduced capital expenditures). We present efficient and effective solution methods for logistics management of multi-location production-inventory systems with transportable production capacity. We present a novel, generalized representation of demand uncertainty and propose data-driven responses to the manage a single location inventory system under such demands.Ph.D

    Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems

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    Industrial Cyber-Physical Systems have benefitted substantially from the introduction of a range of technology enablers. These include web-based and semantic computing, ubiquitous sensing, internet of things (IoT) with multi-connectivity, advanced computing architectures and digital platforms, coupled with edge or cloud side data management and analytics, and have contributed to shaping up enhanced or new data value chains in manufacturing. While parts of such data flows are increasingly automated, there is now a greater demand for more effectively integrating, rather than eliminating, human cognitive capabilities in the loop of production related processes. Human integration in Cyber-Physical environments can already be digitally supported in various ways. However, incorporating human skills and tangible knowledge requires approaches and technological solutions that facilitate the engagement of personnel within technical systems in ways that take advantage or amplify their cognitive capabilities to achieve more effective sociotechnical systems. After analysing related research, this paper introduces a novel viewpoint for enabling human in the loop engagement linked to cognitive capabilities and highlighting the role of context information management in industrial systems. Furthermore, it presents examples of technology enablers for placing the human in the loop at selected application cases relevant to production environments. Such placement benefits from the joint management of linked maintenance data and knowledge, expands the power of machine learning for asset awareness with embedded event detection, and facilitates IoT-driven analytics for product lifecycle management

    Sales and Operations Planning: a comparison between the demand-driven and traditional approaches

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    [EN] Supply Chain Management (SCM) is an important concept to establish links among companies. With the aim to reach the SCM goals, companies must define processes that links the decisions areas. In this context, a process to be dealt is the Sales and Operations Planning (S&OP). The S&OP is a tactical planning process, executed on monthly-basis and led by senior management with the aim to balance demand, production, distribution, procurement and finance, to ensure the plans and performance are aligned to support the business strategic plan. In this sense, a literature review was presented in this paper in order to compare the traditional approach and the demand-driven approach for the S&OP. As expected, because of the more complex environment to be dealt in a demand-driven environment, the S&OP evolved to be able to be executed properly. However, further studies in this area should be developed in order to obtain a final framework for the demand-driven S&OP, to analyse applications in industries, to understand performance implications and to develop a performance framework for the demand-driven S&OP.Bozutti, D.; Esposto, K. (2019). Sales and Operations Planning: a comparison between the demand-driven and traditional approaches. International Journal of Production Management and Engineering. 7(1):23-38. https://doi.org/10.4995/ijpme.2019.9469SWORD233871Ambe, I.M., Badenhorst-Weiss, J.A. (2011). An automotive supply chain model for a demand-driven environment. Journal of Transport and Supply Chain Management, 1(1), 1-22. https://doi.org/10.4102/jtscm.v5i1.18APICS. (2006a). Detailed Scheduling and Planning (3th ed.). Virginia: APICS.APICS. (2006b). Execution and Control of Operations (3th ed.). Virginia: APICS.APICS. (2006c). Master Planning of Resources. (T. F. Cox, M. R. Gartner, T. P. Geraghty, G. L. Kilty, C. V. Nemer, & M. Ross, Eds.) (3th ed.). Virginia: APICS.APICS. (2006d). Strategic Resources Management (3th ed.). Virginia: APICS.APICS. (2016). APICS Dictionary. (P. H. Pittman & J. B. Atwater, Eds.) (15th ed.). Chicago: APICS.Arnold, J.R.T., Chapman, S.N. (2004). Introduction to Materials Management (5th ed.). New Jersey: Pearson.Bjartnes, R., Strandhagen, J.O., Dreyer, H., Solem, K. (2008). Intelligent and demand driven manufacturing network control concepts. In Third World Conference on Production and Operations Management.Bower, P. (2015a). Party Crasher? APICS Magazine, 25(September/October).Bower, P. (2015b). The S&OP Elevator Pitch. APICS Magazine, 25(July/August).Bower, P. (2016a). Intangibles. APICS Magazine, 26(July/August).Bower, P. (2016b). Planning to Plan. APICS Magazine, 26(September/October).Bower, P. (2016c). S&OP Prophecies. APICS Magazine, 26(January/February).Bozutti, D.F., Bueno-da Costa, M.A., Ruggeri, R. (2010). Logística: Visão Global e Picking (Série Apon). São Carlos: Edufscar.Brereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M. (2007). Lessons from applying the systematic literature review process within the software engineering domain. Journal of Systems and Software, 80(4), 571-583. https://doi.org/10.1016/j.jss.2006.07.009Budd, J., Knizek, C., Tevelson, B. (2012). The Demand-Driven Supply Chain; Making It Work and Delivering Results. BCG perspectives.Burrows, R.P. (2012). The Market-Driven Supply Chain: a revolutionary model for sales and operations planning in the new on-demand economy. New York: AMACOM - American Management Association.Cecere, L., Barrett, J., Mooraj, H. (2009). Sales and Operations Planning: Transformation From Tradition. Industry Value Chain Strategies, (May), 9.Chase, R.B., Jacobs, F.R., Aquilano, N.J. (2006). Administração da Produção para a Vantagem Competitiva. (R. B. Taylor, Ed.). São Paulo: Bookman.Chatzopoulos, C., Gračanin, D., Veža, I., Tsigkas, A. (2012). Demand-Driven Supply Chain using Lean & Agile Principles: A Culture for Business Excellence. In Proceedings of International Conference for Entrepreneurship, Innovation and Regional Development. https://doi.org/10.13140/2.1.1422.8488Conforto, E.C., Amaral, D.C., Silva, S.L. Da. (2011). Roteiro para revisão bibliográfica sistemática : aplicação no desenvolvimento de produtos e gerenciamento de projetos. 8° Congresso Brasileiro de Gestão de Desenvolviemnto de Produto - CNGDP 2011, (1998), 1-12. Retrieved from http://www.ufrgs.br/cbgdp2011/downloads/9149.pdfCook, D.J., Mulrow, C.D., Haynes, R.B. (1997). Systematic Reviews: Synthesis of Best Evidence for Clinical Decisions. In Annals of Internal Medicine (Vol. 126, 376-380). https://doi.org/10.7326/0003-4819-126-5-199703010-00006Corrêa, H.L., Corrêa, C.A. (2017). Administração de Produção e Operações - Manufatura e Serviços: uma abordagem estratégica (4th ed.). São Paulo: Atlas.Corrêa, H.L., Gianesi, I.G.N., Caon, M. (2007). Planejamento, programação e controle da produção: MRP II/ERP : conceitos, uso e implantação (5a ed.). São Paulo: Atlas.De Souza, M.T., Carvalho, R. De. (2010). Revisão integrativa: o que é e como fazer. Einsten, 8, 102-107. https://doi.org/10.1590/S0104-07072008000400018Denyer, D., Tranfield, D. (2009). Producing a Systematc Review. In D. A. Buchanan & A. Bryman (Eds.), The SAGE Handbook of Organizational Research Methods (pp. 671-689). Thousand Oaks, CA: Sage Publications Inc.Dreyer, H.C., Strandhagen, J.O., Romsdal, A., Hoff, A. (2010). Principles for real-time, integrated supply chain control: An example from distribution of pharmaceuticals. IFIP Advances in Information and Communication Technology, 338 AICT, 187-194. https://doi.org/10.1007/978-3-642-16358-6_24Feng, Y., D'Amours, S., Beauregard, R. (2008). The value of sales and operations planning in oriented strand board industry with make-to-order manufacturing system: Cross functional integration under deterministic demand and spot market recourse. International Journal of Production Economics, 115(1), 189-209. https://doi.org/10.1016/j.ijpe.2008.06.002Fernandes, F.C.F., Godinho, M. (2010). Planejamento e Controle da Produção: dos fundamentos ao essencial. São Paulo: Atlas.Gollamudi, R. (2013). Demand Driven S&OP - Maximizing Output To Match Demand Variation. BristleCone: Your Supply Chain Optimized, 22.Hadaya, P., Cassivi, L. (2007). The Role of Joint Collaboration Planning Actions in a Demand-driven Supply Chain. Industrial Management & Data Systems, 107(7), 954-978. https://doi.org/10.1108/02635570710816694Ihme, M., Stratton, R. (2015). Evaluating Demand Driven MRP: a case based simulated study. In International Conference of the European Operations Management Association (pp. 1-10). Neuchatel.Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33, 1-26.Lambert, D.M., Cooper, M.C. (2000). Issues in Supply Chain Management. Industrial Marketing Management, 29(1), 65-83. https://doi.org/10.1016/S0019-8501(99)00113-3Lapide, B.Y.L. (2009). The S&OP Rudder. Supply Chain Management Review, 13(2), 4-6.McCollum, B. (2011). Know Your S&OP. APICS Magazine, 21(January/February).Mendes, P., Leal, J.E., Thomé, A.M.T. (2016). A maturity model for demand-driven supply chains in the consumer product goods industry. International Journal of Production Economics, 179, 153-165. https://doi.org/10.1016/j.ijpe.2016.06.004Miclo, R., Fontanili, F., Lauras, M., Lamothe, J., Milian, B. (2016). An empirical study of Demand-Driven MRP. In 6th International Conference on Information Systems, Logistics and Supply Chain - ILS Conference 2016 (pp. 1-7).Murray, P. (2016). Warding Off Activist Investors. APICS Magazine, 26(March/April).Novaes, A.G. (2007). Logística e Gerenciamento da Cadeia de Distribuição (6a ed.). Rio de Janeiro: Elsevier.Pedroso, C.B., Silva, A.L. (2015). Dinâmica de implantação do Sales and Operations Planning: principais desafios. Gestão & Produção, 22(3), 662-677. https://doi.org/10.1590/0104-530X1754-14Pires, S.R.I. (2004). Gestão da Cadeia de Suprimentos: Conceitos, Estratégias, Práticas e Casos. São Paulo: Atlas.Schneider, J. (2013a). Getting Tough with S&OP. APICS Magazine, 23(November/December).Schneider, J. (2013b). S&OP Step by Step. APICS Magazine, 23(September/October).Schneider, J. (2014). Seeing Your S&OP. APICS Magazine, 24(May/June).Shapiro, B.P. (1977). Can Marketing and Manufacturing Coexist? Harvard Business Review, 55(5), 104-114.Smith, C. (2015). The power of decoupling: Unlocking the Secret to Demand Driven Material Requirements Planning (DDMRP). Demand Driven Institute.Smith, C., Ptak, C. (2011). Topic : Demand Driven MRP 21st Century Supply Chains Require New Demand Driven Rules and Tools. Demand Driven Institute, (April).Smith, C., Ptak, C., Ling, D. (2017). The Demand Driven Adaptive Enterprise Model: The Case for a New System of Enterprise Management. Demand Driven Institute.Stock, J.R., Boyer, S.L. (2009). Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management, 39(8), 690-711. https://doi.org/10.1108/09600030910996323Swaim, J.A., Maloni, M., Bower, P., Mello, J. (2016). Antecedents to effective sales and operations planning. Industrial Management & Data Systems, 116(6), 1279-1294. https://doi.org/10.1108/IMDS-11-2015-0461Thomé, A.M.T., Scavarda, L.F., Fernandez, N.S., Scavarda, A.J. (2012). Sales and operations planning and the firm performance. International Journal of Productivity and Performance Management, 61(4), 359-381. https://doi.org/10.1108/17410401211212643Verdouw, C.N., Beulens, A.J.M., Trienekens, J.H., Wolfert, J. (2010). Process modelling in demand-driven supply chains: A reference model for the fruit industry. Computers and Electronics in Agriculture, 73(2), 174-187. https://doi.org/10.1016/j.compag.2010.05.005Vollmann, T.E., Berry, W.L., Whybark, D.C., Jacobs, F.R. (2005). Manufacturing Planning and Control Systems for Supply Chain. New York: McGraw-Hill.Wallace, T.F., Stahl, R.A. (2008). Sales & operations planning: the how-to handbook (3rd ed.). Cincinnati, Ohio: T.F. Wallace & Co.Weintraub, I. (2000). The impact of alternative presses on scientific communication. International Journal of Grey Literature, 1(2), 54-59. https://doi.org/10.1108/14666180010327195Winig, L. (2016). A Data-Driven Approach to Customer Relationships: A Case Study of Nedbank's Data Practices in South Africa. In MIT Sloan Management Review (p. 16)

    Ventilation-on-Demand: Quantity or Quality — A Pilot Trial at Barrick Gold\u27s Bousquet Mine

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    Common to many established mines in Canada, is the problem that their ventilation systems are continually being stretched to meet new needs that were not anticipated in the original design. This can be the result of a variety of different factors, such as the discovery of new reserves at depth, accelerated production, new worker exposure regulations or a change of mining method. At Bousquet, the ventilation of a new multilevel mining block over 1 km away from the existing bottom of the mine presents a challenge. The airflow available for this region is limited to 57 m3/s by the size of a ventilation drift and raise, and by the total volume the mine can supply. This volume is sufficient only if it can be directed to the desired locations, namely where the diesel equipment is operating and with minimal losses (\u3c10%). Due to the mobile nature of the mining equipment and changing production areas, such tight management of air can only be achieved with Ventilation on Demand . This paper describes a pilot trial, within the existing mine, of an automated demand based ventilation management system. Vehicle tracking and identification determine ventilation demand, location and duration. Specific air volumes are achieved with remote controlled regulators, and auxiliary fan systems and verified with airflow monitors. Air quality is monitored with gas sensors. Based upon this trial the mine will be able to determine the viability of an air quality driven system over an engine based air quantity dictated system. This would then, with the approval of the local regulators, allow the mine to operate its ventilation more efficiently and gain the maximum benefit of cleanengine technology and exhaust treatment devices

    6G Underlayer Network Concepts for Ultra Reliable and Low Latency Communication in Manufacturing

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    Underlayer networks in the context of 6G for manufacturing are crucial. They address the evolving needs of highly interconnected and autonomous systems in industry. The digitalization of manufacturing processes, driven by the Internet of Things and increased data availability, enables more efficient and demand-driven production. However, wireless connectivity, which offers flexibility and easy integration of components, comes with challenges such as signal interference or high latency. A new management system is needed to coordinate and route traffic of multiple networks in a specific coverage area. This paper proposes underlayer networks designed for manufacturing, providing low latency, reliability, and security. These networks enable wireless connectivity and integration of wireless technologies into the manufacturing environment, enhancing flexibility and efficiency. The paper also discusses network slicing, spectrum sharing, and the limitations of current wireless networks in manufacturing. It introduces a network concept for underlayer networks and evaluates its application in closed-loop communication for machine tools. The study concludes with future research prospects in this area

    Climate's Long-term Impact on New Zealand Infrastructure (CLINZI) - A Case Study of Hamilton City, New Zealand

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    Infrastructure systems and services (ISS) are vulnerable to changes in climate. This paper reports on a study of the impact of gradual climate changes on ISS in Hamilton City, New Zealand. This study is unique in that it is the first of its kind to be applied to New Zealand ISS. This study also considers a broader range of ISS than most other climate change studies recently conducted. Using historical climate data and four climate change scenarios, we modelled the impact of climate change on water supply and quality, transport, energy demand, public health and air quality. Our analysis reveals that many of Hamilton City's infrastructure sectors demonstrated greater responsiveness to population changes than changes in gradual climate change. Any future planning decisions should be sensitive to climate change, but not driven by it (even though that may be fashionable to do so). We find there is considerable scope for extending this analysis. First, there is a need for local infrastructure managers to improve the coverage of the data needed for this kind of study. Second, any future study of this kind must focus on daily (rather than monthly) time steps and extreme (as well as gradual) climate changes.Climate change, infrastructure, integrated assessment, adaptation, Agricultural and Food Policy, Community/Rural/Urban Development, Crop Production/Industries, Environmental Economics and Policy, Farm Management, International Relations/Trade, Land Economics/Use, Livestock Production/Industries, Political Economy,

    A demand-driven approach for a multi-agent system in Supply Chain Management

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    This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit. © 2010 Springer-Verlag Berlin Heidelberg
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