Articoli di riviste: "Manufacturing resource planning"

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Rand, G. K., A. Drexl e A. Kimms. "Beyond Manufacturing Resource Planning (MRP II)". Journal of the Operational Research Society 51, n. 2 (febbraio 2000): 248. http://dx.doi.org/10.2307/254269.

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Lekiqi, Bislim. "Human resource planning in manufacturing enterprises". Technium Social Sciences Journal 27 (16 gennaio 2022): 1015–28. http://dx.doi.org/10.47577/tssj.v27i1.6564.

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Enterprises in Kosovo are marking significant development steps by launching quality products and services in the national, regional and international market. In this context, the role and importance of human resources is indisputable, and with it their planning. Reaching international agreements, certification of enterprises with quality standards and increasing purchasing power in Kosovo, is influencing Kosovar enterprises to produce more and more for the domestic market, but also for the international market by increasing exports. The growth trend of Kosovar manufacturing enterprises is positive and based on the current situation, this research conducted through the survey aims to bring information about human resource planning in manufacturing enterprises in Kosovo as an instrument to achieve their goals for next year, but also for the future in general. The results of this research will be able to serve enterprise managers, state decision makers and educational institutions to deepen cooperation with businesses for even deeper research that will serve you for the design of study curricula as well as for the development policies of enterprises and institutions for the future.

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Stray, J., J. W. Fowler, W. M. Carlyle e A. P. Rastogi. "Enterprise-Wide Semiconductor Manufacturing Resource Planning". IEEE Transactions on Semiconductor Manufacturing 19, n. 2 (maggio 2006): 259–68. http://dx.doi.org/10.1109/tsm.2006.873399.

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Denkena, Berend, Marcel Wichmann, Simon Kettelmann, Jonas Matthies e Leon Reuter. "Ecological Planning of Manufacturing Process Chains". Sustainability 14, n. 5 (25 febbraio 2022): 2681. http://dx.doi.org/10.3390/su14052681.

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Production planning is a critical step for the implementation of sustainable production. It is necessary to consider energy and resource efficiency in all planning phases to promote sustainable production. In this paper, an approach for environmental impact assessment in all phases of process chain planning supported by process models is presented. The level of detail of the assessment is determined based on the level of detail of the planning phase. During the assessment, consumption of energy and resources is considered. This approach aims to align planning phases with the objective of sustainable production. In rough planning, the approach allows the selection of an ecologically favorable process chain. In detailed planning, process parameters can be selected based on their ecological sustainability. The approach can be integrated into the planning of process chains in order to consider ecological factors throughout all planning phases. The approach is evaluated by using an exemplary use case. The results indicate that rough planning under the consideration of uncertainties can form a reasonable prediction about resource efficiency for possible manufacturing routes. By systematically selecting a resource-efficient process chain, energy savings of up to 21% can be achieved for the presented use case.

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Soni, Adarsh. "Enterprise Resource Planning Software for Manufacturing Industry". International Journal for Research in Applied Science and Engineering Technology 8, n. 5 (31 maggio 2020): 1836–40. http://dx.doi.org/10.22214/ijraset.2020.5294.

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Ahsan, AMM Nazmul, Md Ahasan Habib e Bashir Khoda. "Resource based process planning for additive manufacturing". Computer-Aided Design 69 (dicembre 2015): 112–25. http://dx.doi.org/10.1016/j.cad.2015.03.006.

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Adams, Fred P., e J. F. Cox. "Manufacturing resource planning: An information systems model". Long Range Planning 18, n. 2 (aprile 1985): 86–92. http://dx.doi.org/10.1016/0024-6301(85)90026-3.

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Jain, A. K., R. G. Kasilingam e S. D. Bhole. "Resource-requirements planning in flexible manufacturing systems". International Journal of Advanced Manufacturing Technology 6, n. 3 (agosto 1991): 232–45. http://dx.doi.org/10.1007/bf02601796.

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Winda, Ika, I. Made e I. Ketut. "Developing Manufacturing Application using Enterprise Resource Planning Concept". International Journal of Computer Applications 164, n. 8 (17 aprile 2017): 19–24. http://dx.doi.org/10.5120/ijca2017913709.

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Otto, T., e J. Vain. "MODEL CHECKING IN PLANNING RESOURCE-SHARING BASED MANUFACTURING". IFAC Proceedings Volumes 39, n. 3 (2006): 535–40. http://dx.doi.org/10.3182/20060517-3-fr-2903.00279.

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Maxie Burns, O., David Turnipseed e Walter E. Riggs. "Critical Success Factors in Manufacturing Resource Planning Implementation". International Journal of Operations & Production Management 11, n. 4 (aprile 1991): 5–19. http://dx.doi.org/10.1108/01443579110136221.

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Lee, TaeHyung, Young B. Moon e Heeseok Lee. "Enterprise resource planning survey of Korean manufacturing firms". International Journal of Management and Enterprise Development 3, n. 6 (2006): 521. http://dx.doi.org/10.1504/ijmed.2006.010351.

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Katerattanakul, Pairin, Soongoo Hong e Jinyoul Lee. "Enterprise resource planning survey of Korean manufacturing firms". Management Research News 29, n. 12 (dicembre 2006): 820–37. http://dx.doi.org/10.1108/01409170610717835.

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Olhager, Jan, e Erik Selldin. "Enterprise resource planning survey of Swedish manufacturing firms". European Journal of Operational Research 146, n. 2 (aprile 2003): 365–73. http://dx.doi.org/10.1016/s0377-2217(02)00555-6.

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JONES, D. A. "A prototype expert system for manufacturing resource planning". International Journal of Computer Integrated Manufacturing 1, n. 3 (luglio 1988): 165–70. http://dx.doi.org/10.1080/09511928808944358.

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Chou, Y. C., e R. C. You. "Resource Portfolio Planning Methodology for Semiconductor Wafer Manufacturing". International Journal of Advanced Manufacturing Technology 18, n. 1 (1 luglio 2001): 12–19. http://dx.doi.org/10.1007/s001700170089.

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Thamaraiselvan, V., e N. Ramakrishnan. "Flexible Process Planning Design and Resource Optimization". Shanlax International Journal of Management 8, S1-Feb (26 febbraio 2021): 38–48. http://dx.doi.org/10.34293/management.v8is1-feb.3756.

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Manufacturing processes undergo various transformations based on technological advancements and industry expectations. At initial times, during the period of first Industrial revolution, products were getting manufactured using human capabilities and skills. Then, electrically-driven motors, machines and conveyors were used. Now in the fourth Industrial revolution, Industries are equipped with automation, robots and cyber-physical systems. But adopting such technologies requires a high capital investment which cannot be accommodated by some start-ups. In this research paper, a case of a start-up which manufactures straws and vessel scrubbers in an eco-friendly manner as an initiative towards sustainability has been discussed. The key product of the company is biodegradable straws which are manufactured from coconut leaves through a set of processes. The scope of the research is to develop a labour-intensive process planning model. Managing contemporary issues is a big task for the company because of the dynamic nature of the environment. In this case, the demand for straws changes based on customer preference and accordingly, the manufacturing processes need to be revised. Hence, developing a rigid planning model is not an effective solution, so that, flexible manufacturing process needs to be developed. There is always a scope of improvement towards betterment and optimization in a manufacturing process. It is not necessary that the improvements should lead to drastic results. Japanese manufactures who bring the Toyota Production System (TPS) believe that small improvements in a continual basis will fetch better results in terms of quality, efficiency and lead time reduction. Once the model is developed, areas of improvement to optimize the resources are found out and iterations of process planning model were carried over to improve the efficiency. Through the study, it is found that the development of a flexible process plan is required to compete with the changing business scenarios.

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Reiff, Colin, Matthias Buser, Thomas Betten, Volkher Onuseit, Max Hoßfeld, Daniel Wehner e Oliver Riedel. "A Process-Planning Framework for Sustainable Manufacturing". Energies 14, n. 18 (14 settembre 2021): 5811. http://dx.doi.org/10.3390/en14185811.

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Process planning in manufacturing today focuses on optimizing the conflicting targets of cost, quality, and time. Due to increasing social awareness and subsequent governmental regulation, environmental impact becomes a fourth major aspect. Eventually, sustainability in manufacturing ensures future competitiveness. In this paper, a framework for the planning of sustainable manufacturing is proposed. It is based on the abstraction and generalization of manufacturing resources and part descriptions, which are matched and ranked using a multi-criteria decision analysis method. Manufacturing resources provide values for cost, quality, time and environmental impacts, which multiply with their usage within a manufacturing task for a specific part. The framework is validated with a detailed modeling of a laser machine as a resource revealing benefits and optimization potential of the underlying data model. Finally, the framework is applied to a use case of a flange part with two different manufacturing strategies, i.e., laser metal-wire deposition and conventional milling. The most influential parameters regarding the environmental impacts are the raw material input, the manufacturing energy consumption and the machine production itself. In general, the framework enabled the identification of non-predetermined manufacturing possibilities and the comprehensive comparison of production resources.

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Ming-wei, Jiang, e Li Shi-lian. "A hybrid system of manufacturing resource planning and just-in-time manufacturing". Computers in Industry 19, n. 1 (aprile 1992): 151–55. http://dx.doi.org/10.1016/0166-3615(92)90015-f.

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Misita, Mirjana, Nebojsa Lapcevic, Danijela Tadic, Dragan D. Milanovic e Ankica Borota-Tisma. "New model of enterprises resource planning implementation planning process in manufacturing enterprises". Advances in Mechanical Engineering 8, n. 5 (maggio 2016): 168781401664626. http://dx.doi.org/10.1177/1687814016646263.

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GAO, Shiwen. "Manufacturing Resource Planning Technology Based on Genetic Programming Simulation". Chinese Journal of Mechanical Engineering 22, n. 02 (2009): 177. http://dx.doi.org/10.3901/cjme.2009.02.177.

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Towers, Neil, Alan Knibbs e Nikos Panagiotopoulos. "Implementing manufacturing resource planning in a Greek aerospace company". International Journal of Operations & Production Management 25, n. 3 (marzo 2005): 277–89. http://dx.doi.org/10.1108/01443570510581871.

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Zhang, Yuyun, Shaw C. Feng, Xiankui Wang, Wensheng Tian e Ruirong Wu. "Object oriented manufacturing resource modelling for adaptive process planning". International Journal of Production Research 37, n. 18 (dicembre 1999): 4179–95. http://dx.doi.org/10.1080/002075499189727.

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Kee, H. Clark, e Roy L. Post. "Manufacturing resource planning on a PC local area network". ACM SIGAPL APL Quote Quad 16, n. 4 (maggio 1986): 6–16. http://dx.doi.org/10.1145/22008.22010.

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Maropoulos, P. G., K. R. McKay e D. G. Bramall. "Resource-Aware Aggregate Planning for the Distributed Manufacturing Enterprise". CIRP Annals 51, n. 1 (2002): 363–66. http://dx.doi.org/10.1016/s0007-8506(07)61537-6.

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Vandaele, Nico, e Liesje De Boeck. "Advanced Resource Planning". Robotics and Computer-Integrated Manufacturing 19, n. 1-2 (febbraio 2003): 211–18. http://dx.doi.org/10.1016/s0736-5845(02)00081-9.

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Xu, Wei, e Yinyun Yu. "Optimal Allocation Method of Discrete Manufacturing Resources for Demand Coordination between Suppliers and Customers in a Fuzzy Environment". Complexity 2018 (29 agosto 2018): 1–18. http://dx.doi.org/10.1155/2018/1410957.

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Discrete manufacturing products are often assembled from multiple parts through a series of discrete processes. How to effectively configure resources in a discrete manufacturing environment is an important research topic worthy of attention. Based on an in-depth analysis of the discrete manufacturing operation model and the manufacturing resource allocation process, this paper fully considers the uncertainty factors of the manufacturing resource customers and the interests of the manufacturing resource suppliers and proposes a bilevel planning model under a fuzzy environment that comprehensively considers the customers’ expectation bias and the suppliers’ profit maximization. The method firstly uses a language phrase to collect the language evaluation of the customers and suppliers for manufacturing tasks and uses a trapezoidal fuzzy number to convert the language evaluation phrase into a value that can be calculated. Then, we use the prospect theory to optimize the constraint indicators based on the language evaluation of customers and suppliers. Next, the bilevel planning model for optimal configuration of manufacturing resources in discrete manufacturing environment is established under the consideration of the respective interests of both the customers and the suppliers, and the fast nondominated sorting genetic algorithm (NSGA-II) is used to solve the model. Finally, an example is given to verify the validity and feasibility of the model.

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Gaines, D. M., F. Castan˜o e C. C. Hayes. "MEDIATOR: A Resource Adaptive Feature Recognizer that Intertwines Feature Extraction and Manufacturing Analysis". Journal of Mechanical Design 121, n. 1 (1 marzo 1999): 145–58. http://dx.doi.org/10.1115/1.2829415.

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A deterrent to practical use of many feature extraction systems is that they are difficult to maintain, either because they depend on the use of a library of feature-types which must be updated when the underlying manufacturing resources change (e.g. tools and fixtures), or they rely on the use of task-specific post processors, which must also be updated. For such systems to become practical, it must be easy for a user to update the system to match the current resources. This paper presents MEDIATOR (Maintainable, Extensible Design and manufacturing Integration Architecture and TranslatOR). MEDIATOR is a resource adaptive feature extraction and early process planning system for 3-axis milling. A resource adaptive system is one that changes its behavior as the manufacturing resources in a shop change. MEDIATOR allows users to select from a standard set of tools and fixtures, and automatically identifies any changes in the features that result. It attains its resource adaptive behavior by blurring the line between feature extraction and process planning; descriptions of the manufacturing resources are used to directly identify manufacturable areas of the part. A non-programmer can easily update MEDIATOR by selecting different shop resources.

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ZHANG, FA PING. "RESEARCH ON GRAPH THEORY-BASED MANUFACTURING SETUP PLANNING". Journal of Advanced Manufacturing Systems 07, n. 02 (dicembre 2008): 313–18. http://dx.doi.org/10.1142/s0219686708001541.

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Automatic generation of manufacturing setup planning is studied in this work. The mathematical model to describe the tolerance information and datum-machining feature relationship has been formulated based on extended graphics. By means of the transformation between the feature tolerance relationship graph(FTG) and the datum-machining feature relationship graph (DMG), the algorithm to automatically generate setup planning has been given based on the tolerance analysis and manufacturing resources capability model. The algorithm can identify the machining feature and datum, optimize setup groups based on the manufacturing resource capability and tolerance analysis, as well as minimize the influence of the locating error stack-up on the machining quality. Finally, a case study of setup planning is presented to verify the feasibility of the methodology.

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Perdana, Yandra Rahadian. "Adoption of Enterprise Resources Planning (ERP) In Indonesian Manufacturing Companies". GATR Journal of Business and Economics Review 5, n. 3 (30 dicembre 2020): 86–93. http://dx.doi.org/10.35609/jber.2020.5.3(2).

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Objective – Enterprise resource planning (ERP) is a technology that supports the management of supply chain activities. ERP consists of modules that have various operational and strategic functions. The more modules that are used, the higher the adoption rate is. This study aims to examine the adoption rate based on the modules used. Methodology/Technique – Manufacturing companies in Indonesia were selected as samples to answer the objective of this research and 155 respondents were obtained. The response from each respondent was categorised into two levels of adoption. The companies that adopted 1 to 4 modules were categorised as partial adopters, while companies that adopted five modules were considered to be full adopters. Findings & Novelty – This research found that 39 (25%) companies had fully adopted the ERP modules, 24 companies (15%) had adopted four modules, 29 companies (19%) adopted three modules, and 26 companies (17%) used two modules. Lastly, 37 companies (24%) used one module. Accordingly, the dominant choice is to partially adopt the technology. Type of Paper: Empirical. JEL Classification: O14, 032, O33. Keywords: Technology; Supply Chain; Enterprise Resource Planning (ERP); Adoption; Manufacturing Companies; Resource-Based View (RBV). Reference to this paper should be made as follows: Perdana, Y.R. 2020. Adoption of Enterprise Resources Planning (ERP) In Indonesian Manufacturing Companies, J. Bus. Econ. Review, 5(3) 86–93 https://doi.org/10.35609/jber.2020.5.3(2)

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Sun, Yan Fang. "Compare Business Process between Construction and Manufacturing on the Application of ERP". Advanced Materials Research 243-249 (maggio 2011): 6273–78. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.6273.

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To illustrate that the application of ERP in construction industry is feasible and necessary, this paper analyzes the business process of construction industry based on the four development phases of ERP in manufacturing -- basic MRP, closed-loop MRP, manufacturing resources planning(MRP-II), enterprise resource planning(ERP), and compares the business process between construction and manufacturing. Finally it concludes that there exist many similarities in construction and manufacturing and implement ERP in construction industry is feasible to some extent.

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Жилкин, О. Н., e А. Н. Жилкина. "ERP systems in modern finance management". Экономика и предпринимательство, n. 12(125) (16 febbraio 2021): 1239–42. http://dx.doi.org/10.34925/eip.2021.125.12.249.

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В статье рассмотрены особенности ERP-систем, систем управления всеми видами ресурсов предприятия (Enterprise Resource Planning) с точки зрения финансистов, Система основана на Концепция планирования производственных ресурсов Manufacturing Resource Planning, MRP II. Делается акцент на том, что в отличие от финансово-управленческих информационных систем, в которых производственные функции выступают в качестве «приложения» к финансовым модулям, ERPсистемы построены по более логичному принципу - от производственных процессов к финансам, указываются ограничения использования системы. The article discusses the features of ERP systems, as a systems for managing all types of enterprise resources (Enterprise Resource Planning) from the point of view of financiers. The system is based on the Manufacturing Resource Planning concept, MRP II. The emphasis is made on the fact that, unlike financial and management information systems, in which production functions act as an "application" to financial modules, ERP systems are built on a more logical principle - from production processes to finance, restrictions on the use of the system are indicated.

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Sulaksmi, Andri. "Perencanaan Pengendalian Persediaan Bahan Baku dengan Metode Manufacturing Resource Planning". Jurnal Teknik Industri 9, n. 1 (22 febbraio 2009): 14–21. http://dx.doi.org/10.22219/jtiumm.vol9.no1.14-21.

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Planning material control have a purpose to compile a system capable to yield information to conduct correct action (reordering, scheduleng repeat, determining the amount of requirement at the time of is correct). One of the step performed within standard material control that is deermining best raw material ordering method utilize to get the expense of mot message of minimum. Utilize to support plan produce which have been made and fulfill Planned Order Release pursuant to calculation of MRP hence one of the capacities type from company that is labour factor had also have to be reckoned by do existing amount last for fulfilling requirement which have been reckoned. The object of this UD PATRIOT which located in Mojokerto.This company produce various shoes type which in its operation have constrain in determining best ordering method to each every ordered by raw material item as well as standart material control system which good to menimalize production cost. Planning material control by using this MRP II system was proposed to be applied by at company utilize to yield correct action that is determining maount, time, scheduling repeat, and ordering execution requirement of raw material. With applying MRP II can cost effective equal to Rp4,372,413.88 or 35.91% from expense of before using MRP II.

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G, Ramya, e Chandrasekaran M. "AN INTEGRATION OF MANUFACTURING RESOURCE PLANNING AND JOB SHOP SCHEDULING". International Journal on Design and Manufacturing Technologies 6, n. 2 (2012): 29–45. http://dx.doi.org/10.18000/ijodam.70117.

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Annamalai, C., e T. Ramayah. "Enterprise resource planning (ERP) benefits survey of Indian manufacturing firms". Business Process Management Journal 17, n. 3 (7 giugno 2011): 495–509. http://dx.doi.org/10.1108/14637151111136388.

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Naim, Iram, Tripti Mahara e Ashraf Rahman Idrisi. "Improvement in Procurement through Energy Resource Planning for Manufacturing Organization". International Journal of Business Excellence 19, n. 1 (2019): 1. http://dx.doi.org/10.1504/ijbex.2019.10018659.

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Naim, Iram, Tripti Mahara e Ashraf Rahman Idrisi. "Improvement in procurement through energy resource planning for manufacturing organisation". International Journal of Business Excellence 22, n. 4 (2020): 451. http://dx.doi.org/10.1504/ijbex.2020.111477.

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Lundell, Peter, e Björn Östlund. "A decision support system for long range manufacturing resource planning". Engineering Costs and Production Economics 12, n. 1-4 (luglio 1987): 159–64. http://dx.doi.org/10.1016/0167-188x(87)90074-7.

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Lee, H. "A HESS for resource planning in service and manufacturing industries". Expert Systems with Applications 10, n. 1 (1996): 147–56. http://dx.doi.org/10.1016/0957-4174(95)00041-0.

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Subramanya, N., A. R. Satheesh Kumar, Vikas Yadav e R. K. Venkatesh. "Manufacturing process planning in aerospace systems". IOP Conference Series: Materials Science and Engineering 1258, n. 1 (1 ottobre 2022): 012027. http://dx.doi.org/10.1088/1757-899x/1258/1/012027.

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Process planning is a task comprising a broad range of activities to design and develop an appropriate manufacturing process for producing a part. Interpretation of the part design, selection of manufacturing processes, definition of operations, operation sequences, machining datums, geometrical dimensions and tolerances are some common activities associated with the task. Manufacturing process planning can be defined as systematic determination of detailed methods by which work pieces or parts can be manufactured economically and competitively from raw material stage to final finished size. Geometrical features, dimensional sizes, tolerances, materials, and finishes, are analyzed evaluated to determine appropriate sequence of processing operations, which are based on specific, available resources viz machinery and manpower. Inputs to process planning are designing data, raw material data, resource data (machining data, tooling data, fixture data etc), quality requirement data, production type data etc. The output of a process planning is a process document which is an important document in production management. The paper mainly discusses about production planning and control of metallic manufacturing activities in an aerospace Research and Development (R&D) industry, main emphasis on manufacturing process planning. The general process planning methodology adopted in an aircraft industry is discussed. Elements and Functions of process planning, model of process planning, main mission of process planning, the interaction of processes and its process performance indices are discussed and presented. Importance of manufacturing process planning in an aerospace R&D industry is debated. Also, a case study of process planning adopted for manufacturing of a critical Aircraft system component is discussed.

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Chen, James C., Cheng Ju Sun e Po Tsang B. Huang. "Integrated Capacity Planning System for IC Backend Factory". Key Engineering Materials 450 (novembre 2010): 369–72. http://dx.doi.org/10.4028/www.scientific.net/kem.450.369.

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Integrated Circuit (IC) manufacturing consists of four major phases - wafer fabrication, wafer probe, IC packaging, and final test. Wafer fabrication and wafer probe belong to front-end process, while IC packaging and final test belong to backend process. In this research, integrated capacity planning system (ICPS) is proposed for IC backend manufacturing by taking into account the capacity and capability of resources. This study develops integrated infinite capacity planning integrating the capacity planning of both IC packaging and final test processes to minimize the standard deviations of machine utilization and kit utilization as well as the total extra capacity requirement (as a percentage) exceeding the capacity limit of machine and kit. ICPS applies the concept of workload leveling and infinite capacity planning on dual resources. ICPS consists of five modules: Work-In-Process (WIP) Pulling Module, Lot Release Module, Resource Selection Module, Workload Accumulation Module, and Workload Balance Module. WIP-Pulling Module pulls WIP from the end of the process route to meet the master production schedule (MPS). If WIP cannot meet the MPS requirement, Lot Release Module is executed. ICPS will use Resource Selection Module to accumulate the required resource capacity along its routine at different time buckets. Workload Accumulation Module simultaneously accumulates the workload of the major resources. Workload Balance Module levels the loading of resources by adjusting the lot’s start time using these resources. ICPS is developed in Microsoft Visual Basic and industrial data are used to test its performance. The results show that ICPS is effective and efficient to balance the workload of resources for IC backend factories including packaging and final test.

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Amalnik, Morteza Sadegh. "A Reference Model and a vision for manufacturing system for 2030". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, n. 7 (30 aprile 2015): 5861–68. http://dx.doi.org/10.24297/ijct.v14i7.1899.

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The manufacturing enterprises are now experiencing high pressure of competition. In addition, the advancement in computer software, hardware, networks, information technologies and integration has been gradually reshaping the manufacturing companies by shifting from the industrial age to the information and knowledge era. Due to these elevated competitiveness and advanced computer technology, a number of new manufacturing and management strategies (e.g., Lean production, Just in time, Kaizen, Concurrent Engineering (CE), Cellular Manufacturing (CM), Agile manufacturing, Business process re-engineering (BPR), Agent-based systems (ABS), Computer Integrated Manufacturing (CIM), virtual manufacturing system have emerged for the innovation of manufacturing industries. The developments in organizational concepts created new concepts such as Smart organizations, Centers of excellence, Intelligent enterprises, Integrated enterprises, Virtual enterprises, Virtual enterprises networks, Dynamic enterprises, Extended enterprises, Agile enterprises, Lean enterprises, Process-driven organizations, e-enterprises, Borderless enterprises, Complicated or complex manufacturing systems, Flat structures and others. These terms have been used by researchers to describe various aspects of enterprises and its operational aspects. Although they have different definitions and scopes, there are several common issues: integration of enterprise functions; integration of enterprise resources; and collaboration. In addition Various vendors produced software applications such as Materials Requirement Planning (MRP), Manufacturing Resource Planning (MRP II), Enterprise Resource Planning (ERP),CAD/CAM systems, Manufacturing Execution System (MES), Advanced Planning & Scheduling System (APS), Supply Chain Execution (SCE), Customer Relationship Management (CRM), Advanced Order Management (AOM), Warehouse Management Systems (WMS), Transport Management System (TMS) and others. This paper proposes a Reference Model and vision for Manufacturing System for 2030 and discussed various aspects of future manufacturing enterprise..It supports the inter-enterprise functions/resources integration and collaboration over the networked environment.

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Tan, Shiang Yen, Idrus Rosnah e Wai Peng Wong. "Misfits between Manufacturing Resource Planning (MRPII) System and Manufacturing Environment: A Misfit-Inviability Model". Advanced Materials Research 383-390 (novembre 2011): 6784–91. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6784.

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Misfit between Manufacturing Resource Planning (MRPII) system and the manufacturing environment of adopting organization are well known in contributing to the failure of the system implementation and jeopardizing the system performance. Hence, it is vital to have a better understanding of the system-context misfit problem. Nevertheless, limited studies have empirically examined the relationship between the misfit and the system outcome, especially at the dimensional level of the variables. The purpose of this paper is to introduce a Misfit-Inviability Model (MIM) to conceptualize of relationships between MRPII misfit, extent of organizational readiness, and MRPII system outcome, at the dimensional level of each variable and grounded on strong theoretical foundations. The MIM is an enhancement of existing Fit-Viability Model (FVM). In terms of implication, the new model manages to represent the system adoption as a dynamic process over time, by incorporating implementation contingencies. Additionally, the framework serves as a general model that can be adapted to assess the relationship between outcome of various information systems and the misfits. Future research may include more testing and validation of the dimensions and constructs used in the model.

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Birthare, Shailesh, e Surabhi Tripathi. "Business Role Security in Enterprise Resource Planning System". International Journal of Research in Engineering, Science and Management 3, n. 12 (6 dicembre 2020): 6–7. http://dx.doi.org/10.47607/ijresm.2020.394.

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Enterprise Resource Planning, a collective integrated approach for all business solutions, has been broadly accepted across various industries since 1990 as the upcoming generation of Manufacturing Business System and Manufacturing Resource Planning software. ERP can be taken as to be “the cost of entry for running and growing a business” (Kumar and van Hillegersberg, 2000). An ERP is an information system, which seamlessly integrated and configured for planning, execution and managing all the resources and their maximum use in the enterprise, and streamlines and incorporates the business threads within and across the functional or technical boundaries in the enterprises. With the use of such information system, an organization can automate its elementary business requirements by reducing the complexity and cost of the related integrations for its components. Enterprise may also apply business process reengineering for optimum utilization of its ERP system, and finally output as growth in business can be recorded. Thus, ERP Security plays major role in protecting an organization business data and their employee’s and customer information as well. Study of Access Control Model of ERP Security is very important to keep the enterprise IT environment safe and secure. This paper focuses on the Risk of Fraudulent behavior of user roles across in terms of usage of ERP system. The case study used the information and data based on questionnaire and various inputs from industry experts.

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Bamber, Greg J. "MANUFACTURING TECHNOLOGIES AND HUMAN RESOURCE MANAGEMENT". Prometheus 5, n. 2 (dicembre 1987): 409–18. http://dx.doi.org/10.1080/08109028708629451.

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Xiao, Yan Qiu, Lei Wang e Qi Li. "Research on the Integration Model of Process Planning and Job-Shop Scheduling". Applied Mechanics and Materials 513-517 (febbraio 2014): 1605–8. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1605.

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In order to meet the flexible requirements of enterprise production, an integrated optimization model based on the virtual manufacturing unit of process planning and job-shop scheduling is established. The model makes manufacturing resources information as a combining point and makes the two separate system integrated optimization. Then process route is established in three stages. At the same time uses hierarchy parallel operation mode to transfer and sharing the information of manufacturing resource by the layer of enterprise, work shop and parts. And the parallel mode of process and scheduling work meet the match selection of process and resources, this provides a theoretical basis for the real-time optimization of process planning and shop scheduling.

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Peslak, Alan R. "Enterprise resource planning success". Industrial Management & Data Systems 106, n. 9 (dicembre 2006): 1288–303. http://dx.doi.org/10.1108/02635570610712582.

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Chryssolouris, G., D. Mavrikios, N. Papakostas, D. Mourtzis, G. Michalos e K. Georgoulias. "Digital manufacturing: History, perspectives, and outlook". Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, n. 5 (1 maggio 2009): 451–62. http://dx.doi.org/10.1243/09544054jem1241.

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Digital manufacturing has been considered, over the last decade, as a highly promising set of technologies for reducing product development times and cost as well as for addressing the need for customization, increased product quality, and faster response to the market. This paper describes the evolution of information technology systems in manufacturing, outlining their characteristics and the challenges to be addressed in the future. Together with the digital manufacturing and factory concepts, the technologies considered in this paper include computer-aided design, engineering, process planning and manufacturing, product data and life-cycle management, simulation and virtual reality, automation, process control, shopfloor scheduling, decision support, decision making, manufacturing resource planning, enterprise resource planning, logistics, supply chain management, and e-commerce systems. These technologies are discussed in the context of the digital factory and manufacturing concepts.

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LEUS, ROEL, e WILLY HERROELEN. "Stability and resource allocation in project planning". IIE Transactions 36, n. 7 (luglio 2004): 667–82. http://dx.doi.org/10.1080/07408170490447348.

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Thilmany, Jean. "It’s All About Togetherness". Mechanical Engineering 123, n. 08 (1 agosto 2001): 64–67. http://dx.doi.org/10.1115/1.2001-aug-5.

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This article focuses on various features of product data management system (PDM). A PDM system manages all forms of product data; that is, computer-aided design or text files, or anything else concerning product development. PDM systems also ensure that bills of material are generated on the design side. The bill of material describes exactly what parts will be used in each manufactured product. Using the bill of material (BOM), a manufacturing engineer determines the most efficient set of operations to manufacture a product and may request a design modification to streamline production. BOM development should logically take place in the PDM system at the same time the product is being developed and then should be released to the enterprise resource planning system—and thus to the manufacturing side—when the product design is complete. An enterprise-resource planning system is a company’s operational, planning, and control system used to manage the resources of the manufacturing part of the operation.

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