Relevant bibliographies by topics / Production-Inventory Planning Problem

Academic literature on the topic 'Production-Inventory Planning Problem'

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Published: 6 September 2023

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Journal articles on the topic "Production-Inventory Planning Problem"

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Lin, Jennifer, Henry C. J. Chao, and Peterson Julian. "Planning Horizon for Production Inventory Models with Production Rate Dependent on Demand and Inventory Level." Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/961258.

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This paper discusses why the selection of a finite planning horizon is preferable to an infinite one for a replenishment policy of production inventory models. In a production inventory model, the production rate is dependent on both the demand rate and the inventory level. When there is an exponentially decreasing demand, the application of an infinite planning horizon model is not suitable. The emphasis of this paper is threefold. First, while pointing out questionable results from a previous study, we propose a corrected infinite planning horizon inventory model for the first replenishment cycle. Second, while investigating the optimal solution for the minimization problem, we found that the infinite planning horizon should not be applied when dealing with an exponentially decreasing demand. Third, we developed a new production inventory model under a finite planning horizon for practitioners. Numerical examples are provided to support our findings.
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Silva Filho, Oscar S. "Production Planning Problem with Inventory Boundary Affected by Demand Uncertainty." IFAC Proceedings Volumes 33, no. 17 (July 2000): 651–56. http://dx.doi.org/10.1016/s1474-6670(17)39480-6.

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Filho, Oscar S. Silva. "A CONSTRAINED STOCHASTIC PRODUCTION PLANNING PROBLEM WITH IMPERFECT INFORMATION OF INVENTORY." IFAC Proceedings Volumes 38, no. 1 (2005): 121–26. http://dx.doi.org/10.3182/20050703-6-cz-1902.01504.

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Gang, Duan, Chen Li, Li Yin-Zhen, Song Jie-Yan, and Akhtar Tanweer. "Optimization on Production-Inventory Problem with Multistage and Varying Demand." Journal of Applied Mathematics 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/648262.

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This paper addresses production-inventory problem for the manufacturer by explicitly taking into account multistage and varying demand. A nonlinear hybrid integer constrained optimization is modeled to minimize the total cost including setup cost and holding cost in the planning horizon. A genetic algorithm is developed for the problem. A series of computational experiments with different sizes is used to demonstrate the efficiency and universality of the genetic algorithm in terms of the running time and solution quality. At last the combination of crossover probability and mutation probability is tested for all problems and a law is found for large size.
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Liu, Guo Li, Jun Zhao, and Wei Wang. "Optimal Planning for Product Blending." Advanced Materials Research 339 (September 2011): 358–61. http://dx.doi.org/10.4028/www.scientific.net/amr.339.358.

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This paper deals with the product blending problem originating from the production system of a large typical oil refinery. A deterministic mixed integer programming model is proposed. The objective is to make an effective production-inventory plan for product blending unit (PBU) in order to meet the demand of product oil with no backlogging allowed and minimize the total costs, that is, the sum of purchasing, production, inventory and setup costs. The constraints related to material balance, different capacities and different production schemes are considered. A numerical example is subsequently provided to illustrate the broad applicability of the proposed model.
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Gligoric, Zoran, Cedomir Beljic, Branko Gluscevic, and Cedomir Cvijovic. "Underground Lead-Zinc Mine Production Planning Using Fuzzy Stochastic Inventory Policy / Planowanie Wydobycia Cynku I Ołowiu W Kopalniach Podziemnych Z Wykorzystaniem Podejścia Stochastycznego Z Elementami Logiki Rozmytej Do Określania Niezbędnego Poziomu Zapasów." Archives of Mining Sciences 60, no. 1 (March 1, 2015): 73–92. http://dx.doi.org/10.1515/amsc-2015-0006.

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Abstract Methodology for long-term underground lead-zinc mine planning based on fuzzy inventory theory is presented in this paper. We developed a fuzzy stochastic model of inventory control problem for planning lead-zinc ore production under uncertainty. The final purpose of this article is to find the optimal quantity of mined ore that should be stockpiled, in order to enable “feeding” of mineral processing plant in cases when the production in underground mine is interrupted, by using Possibilistic mean value of fuzzy number for defuzzing the fuzzy total annual inventory costs, and by using Extension of the Lagrangean method for solving inequality constrain problem. The different types of costs involved in mined ore inventory problems affect the efficiency of production scheduling. Dynamic nature of lead and zinc metal price is described by Ornstein-Uhlenbeck stochastic mean reverting process. The model is illustrated with a numerical example.
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Adhi Wicaksana, Bagus Ismail, and Erni Suparti. "Optimisasi Jumlah Produksi Menggunakan Model Newsboy dan Perencanaan Pengendalian Bahan Baku Menggunakan Material Requirement Planning (MRP)." PROZIMA (Productivity, Optimization and Manufacturing System Engineering) 2, no. 2 (June 25, 2019): 88. http://dx.doi.org/10.21070/prozima.v2i1.1918.

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A company have to do inventory control for available guarantying of material, component or item at the time to fulfill production schedule, and available guarantying of product become to consumer and take care of inventory at minimum condition. As object of research is CV. Cita Nasional located in Salatiga. Problems that exist in the CV. Cita Nasional often experience shortages of raw materials caused by internal and external factors. The approach taken to solve this problem by making a production plan using the Newsboy Problem because milk products including perishable product and raw material inventory planning (MRP). From the calculation results obtained the company must produce optimal demand every Monday to Sunday. While the raw material inventory plan using Economic Order Quantity (EOQ) method. Company decreased cost for fresh milk amounting to Rp.35.526.780 and decreased raw material expense cost for whey powder amounting to Rp. 22.573.650.
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Ogunwolu, Ladi, O. A. Alli, Chidi Onyedikam, and A. A. Sosimi. "Multi-Item Multi-Period Dynamic Capacity-Constrained Lot-Sizing Model with Parallel Machines and Fuzzy Demand." Advanced Materials Research 367 (October 2011): 627–38. http://dx.doi.org/10.4028/www.scientific.net/amr.367.627.

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Multi-item, multi-period production systems are prevalent in traditional production and distribution settings. A dynamic lot size production scheduling model (DLSPM) for multi-Production/inventory item multi-period production system with parallel machines is proposed in this paper. A mathematical framework that extends the DLSPM to multi-Production/inventory item-multi-period production planning constrained by storage space was built. The criteria of DLSPM explore optimal production schedule with the constraints of inventory, backlogs, production and demand to minimize the total inventory costs over finite planning horizon. Demand analogous to a typical production environment considered includes dynamic deterministic and fuzzy demand. The model was tested with both deterministic and fuzzy demand spread over ten years, for five equal planning periods, with a two Production/inventory item and two parallel machine test bed. From the various demand types, several iterations (sub problems) were generated and optimality condition was then verified. To capture the imprecision that is often inherent in the estimated future demand, demand was specified by fuzzy numbers and modeled using the triangular membership function distribution. Centre of gravity defuzzification scheme was used within finite intervals to obtain defuzzified demand. Tora Operations Research software was used to run the model using a test problem. Computational results vindicate the robustness and flexibility of the approach based on the quality of the solutions obtained.
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Wang, Neng Min, Zheng Wen He, Qiu Shuang Zhang, and Lin Yan Sun. "Single Item Lot Sizing Models with Bounded Inventory and Remanufacturing." Advanced Materials Research 102-104 (March 2010): 791–95. http://dx.doi.org/10.4028/www.scientific.net/amr.102-104.791.

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Dynamic lot sizing problem for systems with bounded inventory and remanufacturing was addressed. The demand and return amounts are deterministic over the finite planning horizon. Demands can be satisfied by manufactured new items, but also by remanufactured returned items. In production planning, there can be situations where the ability to meet customer demands is constrained by inventory capacity rather than production capacity. Two different limited inventory capacities are considered; there is either bounded serviceables inventory or bounded returns inventory. For the two inventory case, we present exact, polynomial time dynamic programming algorithm based on the idea of Teunter R, et al. (2006).
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Wu, Jing, Dan Zhang, Yang Yang, Gongshu Wang, and Lijie Su. "Multi-Stage Multi-Product Production and Inventory Planning for Cold Rolling under Random Yield." Mathematics 10, no. 4 (February 15, 2022): 597. http://dx.doi.org/10.3390/math10040597.

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This paper studies a multi-stage multi-product production and inventory planning problem with random yield derived from the cold rolling process in the steel industry. The cold rolling process has multiple stages, and intermediate inventory buffers are kept between stages to ensure continuous operation. Switching products during the cold rolling process is typically very costly. Backorder costs are incurred for unsatisfied demand while inventory holding costs are incurred for excess inventory. The process also experiences random yield. The objective of the production and inventory planning problem is to minimize the total cost including the switching costs, inventory holding costs, and backorder costs. We propose a stochastic formulation with a nonlinear objective function. Two lower bounds are proposed, which are based on full information relaxation and Jensen’s inequality, respectively. Then, we develop two heuristics from the proposed lower bounds. In addition, we propose a two-stage procedure motivated by newsvendor logic. To verify the performance of the proposed bounds and heuristics, computational tests are conducted on synthetic instances. The results show the efficiency of the proposed bounds and heuristics.
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Dissertations / Theses on the topic "Production-Inventory Planning Problem"

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Cheah, Boon Soon. "Multi-item, single facility lot sizing problems." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259521.

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Arifin, Nadia Aulia, and 娜迪雅. "The Integrated Production-Inventory-Distribution Planning Problem (Case Study in Asia)." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/54157955069809710402.

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碩士
國立清華大學
工業工程與工程管理學系
103
Optimization is widely applicable solution for most engineering problems including production, transportation, and distribution. Furthermore, in a global supply chain, products transferred needs to be optimized in either cost efficient or required time-window manner. Temperature sensitive and perishable products (TSPP) is one type of commodities that need special consideration during shipment, defined as cold freight distribution. As customer demand become more varied and competition become fiercer, freight transportation needs to be more flexible thus still managed to be efficient. This flexibility is contradictive to the optimal cost solution, which made most of shipments is either not cost effective or dealing with high damage rate due to long shipment. This research proposed a mathematical model to integrate production, transportation, and inventory aspects for TSPP in global supply chain (GSC). The mathematical model is aim to minimize all costs functions and increase flexibility. This research is an application of MINLP model to solve a study case of frozen products in multiple vendor and multiple buyer problem.
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Books on the topic "Production-Inventory Planning Problem"

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Production, planning, and controlling: A problem-based approach. Tinley Park, Ill: Goodheart-Willcox Co., 1998.

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Mercan, Hasan Murat. Multi-family dynamic lot sizing problems with coordinated replenishments. 1990.

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Nowak, Dariusz, ed. Production–operation management. The chosen aspects. Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu, 2021. http://dx.doi.org/10.18559/978-83-8211-059-3.

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The aim of the e-book is to present the theoretical, cognitive and practical aspects of the essence and complexity of operational management in a production company. The presented modern production methods together with the challenges and problems of contemporary enterprises should better help to understand the issues of sustainable development, with particular emphasis on waste. The book consists of six chapters devoted to relevant and topic issues relating to the core business of an industrial enterprise. Chapter 1 The nature of the industrial enterprise is an introduction to further considerations and deals with the essence of the basic aspects of the company. Both popular and less known definitions of an enterprise, its features, functions and principles of operation are presented. An important part of the chapter is the presentation and formulation of strategic, tactical and operational goals. Moreover, the division of enterprises is presented with the use of various criteria and the features of the industrial market, which make it distinct. Chapter 2 The operational management evolution and its role in the industrial enterprise discusses the evolution and concept of production and operational management. The management levels were also presented, indicating their most important functions. An integral part of the chapter is the essence of the production system, viewed through the prism of the five elements. Chapter 3 Functions and role in operations management presents the issues concerning the organization of production processes, production capacity and inventory management. This part also presents considerations on cooperation and collaboration between enterprises in the process of creating value. Chapter 4 Traditional methods used in operational activities focuses on methods such as benchmarking, outsourcing, core competences, JIT, MPR I and MRP II, as well as TQM and kaizen. Knowledge of these methods should contribute to understanding the activities of modern enterprises, the way of company functioning, the realization of production activities, as well as aspects related to building a competitive position. Chapter 5 Modern methods used in production-operations management discusses the less common and less frequently used production methods, based on a modern and innovative approach. In particular, it was focused on: Shop Floor Control and cooperative manufacturing, environment-conscious manufacturing (ECM) and life-cycle assessment ( LCA), waste management and recycling, Electronic Data Interchange (EDI), virtual enterprise, World Class Manufacturing (WCM), Quality Function Deployment (QFD) and House of Quality (HOQ), theory of constraints (TOC), Drum Buffer Rope (DBR), group technology (GT) and cellular manufacturing (CM), Demand Chain Management and competitive intelligence (CI). In the last section discusses: the role of sustainable statistical process control and Computer-Aided Process Planning in context formatting of information management. Chapter 6 Problems of sustainable development and challenges related to production and operations management describes the problem and challenges related to production and operations activities. In particular, attention was paid to the threats related to changes in global warming, the growing scale of waste, or the processes of globalization. It was pointed out that the emerging problem may be both a threat and a chance for the development of enterprises. An integral part of the chapter are also considerations on technical progress, innovation and the importance of human capital in operational activities.
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Book chapters on the topic "Production-Inventory Planning Problem"

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Ekşioğlu, Sandra Duni, and Mingzhou Jin. "Cross-Facility Production and Transportation Planning Problem with Perishable Inventory." In Computational Science and Its Applications - ICCSA 2006, 708–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11751595_75.

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Ohta, Hiroshi, Aritoshi Kimura, and M. Abdur Rahim. "A Generalized Integrated Economic Model for Inventory and Quality Control Problems." In Integrated Models in Production Planning, Inventory, Quality, and Maintenance, 145–60. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1635-4_8.

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Reid, Jill, and Lotfi Tadj. "Optimal Control of the Integrated Marketing-Production Planning Problem." In Handbook of Research on Promoting Business Process Improvement Through Inventory Control Techniques, 349–70. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3232-3.ch019.

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We consider in this paper the integrated marketing – production planning problem and propose an optimal control approach to derive the optimal solution. The state variables are the inventory level and the stock of goodwill and the control variables are the production rate and the advertising rate. Both cases where the firm adopts a continuous-review and a periodic-review policy are considered. The optimal states and controls are obtained explicitly. Illustrative examples are presented. Sensitivity analysis shows the effect of some system parameters on the optimal solution.
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Zeddam, Besma, Fayçal Belkaid, and Mohammed Bennekrouf. "Combining Fix and Relax Heuristic and LP-Metric Method to Solve the Multi-Objective Integrated Production-Routing Problem." In Logistics and Supply Chain Management in the Globalized Business Era, 244–65. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8709-6.ch011.

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Production routing problem is one of the problems of the integrated planning that interests in optimizing simultaneously production, inventory, and distribution planning. This chapter has the purpose of developing two mono-objective models for the production-routing problem: one of them minimizes the total costs which is the classical objective while the other one minimizes the energy consumed by the production system. A bi-objective model is then proposed to combine the two objectives mentioned previously using LP-metric method. To solve big instances of the problem in reasonable time, an approximate approach is proposed using the rolling horizon-based fix and relax heuristic. Finally, computational results are presented to compare the solutions obtained by both approaches.
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Barron, Yonit. "Fluid Inventory Models under Markovian Environment." In Logistics Engineering [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.104183.

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Today’s products are subject to fast changes due to market conditions, short life cycles, and technological advances. Thus, an important problem in inventory planning is how to effectively manage the inventory control in a dynamic and stochastic environment. The traditional Economic Order Quantity (EOQ) and Economic Production Quantity (EPQ) both are widely and successfully used models of inventory management. However, both models assume constant and fixed parameters over time. Unfortunately, most of these assumptions are unrealistic. In this study, we generalize the EOQ and EPQ models and study production-inventory fluid models operating in a stochastic environment. The inventory level increases or decreases according to a fluid-flow rate modulated by an n-state continuous time Markov chain (CTMC). Our main objective is to minimize the expected discounted total cost which includes ordering, purchasing, production, set up, holding, and shortage costs. Applying regenerative theory, optional sampling theorem (OST) to the multi-dimensional martingale and fluid flow techniques, we develop methods to obtain explicit formulas for these cost functionals. As such, we provide managers with a useful framework and an efficient and easy-to-implement tool to coop with different demand–supply patterns.
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Medaglia, A. L. "Applications of JGA to Operations Management and Vehicle Routing." In Handbook of Research on Nature-Inspired Computing for Economics and Management, 625–41. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59140-984-7.ch041.

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Two of the most complex activities in production and operations management (POM) are inventory planning and operations scheduling. This chapter presents two problems related to these activities, namely, the capacitated lot-sizing and scheduling problem and the capacitated vehicle routing problem. For each of these problems, the authors discuss several solution methods, present a competitive genetic algorithm, and describe its implementation in the Java Genetic Algorithm (JGA) framework. The purpose of this chapter is to illustrate how to use JGA to model and solve complex business problems arising in POM. The authors show that JGA-based solutions are quite competitive and easier to implement than widely used methods found in the literature.
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van Santen, Rutger, Djan Khoe, and Bram Vermeer. "Robust Logistics." In 2030. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780195377170.003.0024.

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Our lives seem to revolve around schedules. If we don’t honor them with second-to-second precision, we miss our trains and our workplace rosters fall apart. We’re reliant on one another, and we constantly have to coordinate our schedules with those of others. Planning is crucial to our industry, too. If you unexpectedly run out of nuts and bolts, you can’t make any more cars, and the entire production process grinds to a halt. No manufacturer can afford that, so industrial companies employ large teams of specialists whose job is to ensure there are never any shortages of key parts. A worldwide logistic network has become our industry’s lifeblood. The central issue facing logistics is that of reliability. How do you keep your supply network intact? And how do you limit the consequences if it fails? These are questions that go far beyond the supply of nuts and bolts for new cars. Reliable logistics touches equally on the web of interactions that determine food production and the optimization of the Internet. It also extends to power supply, telecommunications, and workforce. Reliable networks make our society tick. But they face uncertainties of various kinds. That lends a broader significance to insights gained from industrial logistics, which offer us tools we can use to optimize networks and account for uncertainties in other areas as well. The reliability of a supply network is intimately bound up with the inventories you need to maintain. Businesses hold millions of dollars’ worth of supplies in their warehouses to make absolutely certain they never cease production due to a failure in the supply chain. So the key question is how large a stock do you need to hold of each component? Smart planning to hold down inventory levels in your warehouse generates immediate savings. On the other hand, you need enough stock to ensure continuity should anything go wrong. Optimizing storage is a common problem in supply networks. There is always a trade-off between the reliability of the network and the need for it to be profitable in an economic sense.
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Maithel, R. "SOME FINDINGS FROM STUDIES IN TECHNOLOGY11Technology is defined to include manufacturing processes, equipment, manufacturing, management technology (quality control, production and inventory planning and control and production facilities maintenance techniques), product/process development, human resources management techniques, marketing management techniques, and financial management techniques. ADOPTION." In Information Control Problems in Manufacturing Technology 1992, 13–24. Elsevier, 1993. http://dx.doi.org/10.1016/b978-0-08-041897-1.50008-0.

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Conference papers on the topic "Production-Inventory Planning Problem"

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Filho, Oscar S. Silva. "Stochastic Production Planning Problem under Unobserved Inventory System." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282228.

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Tursunov, Bobir. "Strategic Planning of Production Capacities in Textile Enterprises." In International Conference on Eurasian Economies. Eurasian Economists Association, 2018. http://dx.doi.org/10.36880/c10.02179.

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In the article the author studied the process of planning production capacities at textile enterprises. The author considers the production capacity as a reflection of the maximum possible release of the ready-to-sell products of the relevant nomenclature within the established timeframe while effectively using the production potential of the enterprise. This implies the full use of all economic resources based on the use of advanced technology, advanced forms and methods of organizing labor and production. An important task for enterprises in the use of production capacity is to plan production capacity. Since in the case of not matching the production capacity to the parameters of the market environment, the enterprise has the risk of losing its target market due to the expectation of manufacturing an order or the capture of a larger market share by competitors. Otherwise, excess capacity will cause problems in the formation of market demand, which will inevitably lead to loss of income due to excessive costs to maintain the production system in an optimal state, such as: inventory, depreciation, staff salaries. Founded that solving the problem of planning production capacity lays the foundation for ensuring rhythmicity. The concept of strategic capacity planning relies on achieving economies of scale and development curves, focusing the capacity and flexibility of production. At the end of the article has been visually presented the process of capacity planning and suggests the decision tree, balance models, breakeven analysis and sensitivity analysis as evaluation methods for solving the design problem of production capacity.
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Plangsrisakul, Kanapath, Tuanjai Somboonwiwat, and Chareonchai Khompatraporn. "Make-To-Order Production Planning With Seasonal Supply In Canned Pineapple Industry." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0199.

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This research studies a make-to-order production planning in a canned pineapple industry. Pineapple is a seasonal perishable fruit. Thus, the cost of fresh pineapple which is the main raw material in canned pineapple is inexpensive during its season. The color of the pineapple also determines the price of the canned pineapple. However, the availability of different colors (called “choice” and “standard”) is dependent. Specifically, if the ratio of the choice color is more, the ratio of the other color is less. There are several costs involve such as fresh pineapple cost, can cost, sugar cost, water cost, labor cost, energy cost, and inventory cost. The problem is formulated as a mathematical model to maximize the total profit over four-months planning horizon. Two supply uncertainty cases are tested which are low and high ratios of the choice color. The results show that the profit depends on available color ratios of the pineapple. The production planning is best if it matches with the availability of the color ratios. In certain months, some fresh pineapple purchased exceed the need of the production because of the dependency of the two colors. The inventory holding cost also influences the production decision—whether to produce the canned pineapple in earlier months or it is better to produce only the canned pineapple when it is needed to serve the customer orders.
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He, Guoxi, Yongtu Liang, Limin Fang, Qi Zheng, and Liying Sun. "Optimization of Planning and Scheduling of Refinery Product Based on Downstream Requirements." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64150.

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The disconnect between the optimization systems of upstream production and downstream demand poses a legitimate problem for China’s refined oil industry in terms of overproduction waste. Established methods only partially model the refinery system and are unable to integrate detailed production plans or meet market demands. Therefore, the research on production scheduling optimization combined with the demand of downstream pipeline network has very real applications that not only reduce the consumption of human/material resources, but also increase economic efficiency. This paper aims to optimize the production scheduling of refined oil transportation based on the demand of downstream product pipelines by analyzing the relationships between crude oil supply, refinery facility capacities and refinery tanks storage. The new model will minimize the refined production surplus therefore minimizing refinery costs and wastage. This is done by implementing models custom designed to optimize the three subsystems of the overall process: oil product blending scheduling optimization, producing and processing equipment scheduling optimization, and mixed crude oil scheduling optimization. We first analyzed the relationship between all the production units from the crude oil to the distributional destinations of oil products. A mathematical model of the refinery production scheduling was then built with minimum total surplus inventory as the objective function. We assumed a known downstream demand and used a step by step model to optimize oil stocks. The oil blending plan, production scheduling, amount of crude oil, and refined oil mixing ratios were all derived from the model using three methods: a nonlinear method called Particle Swarm Optimization (PSO), the simplex method and the enumeration method. The evidence laid out in this paper verifies our models functionality and suggests that systems can be significantly optimized by using these methods which can provide solutions for industries with similar challenges. Optimization of the refinery’s overall production process is achieved by implementing models for each of the three distinguished subsystems: oil blending model, plant scheduling model, and the mixed crude oil refining model. The demand dictates the final production quantities. From those figures we are able to place constraining limits on the input crude oil. The refined oil production scheme is continuously enhanced by determining the amount of constituent feed on the production equipment according to the results of previous production cycle. After optimization, the minimum surplus inventory of the five oil components approach their lower limits that were calculated using our models. We compare the literature on scheduling optimization challenges both in China and abroad while providing a detailed discussion of the present situation of Chinese refineries. The interrelationships of production processes on each other are revealed by analyzing the system and breaking it down to three fundamental parts. Basing the final production predictions on the downstream demand, we are able to achieve a minimum refinery surplus inventory by utilizing a comprehensive refinery scheduling model composed of three sub-models.
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Xu, Ning, Qi Liao, Yongtu Liang, Zhengbing Li, and Haoran Zhang. "Integrated Scheduling for a Multi-Product Pipeline Network With Delivery Due Dates." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78057.

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Currently, pipeline is the most effective way to transport large-volume products over long distance. To effectively satisfy market demands for multiple refined products by delivery due dates, the multi-product pipeline network usually transports several refined products in sequence from refineries to certain destinations. The integrated scheduling of multi-product pipeline network, including inventory management, transport routes planning, batch sequence, batch volume, et al., is one of the most strategic problems due to its large-scale, complexity as well as economic significance. This subject has been widely studied during the last decade. However, most researches focus on large-size scheduling models whose computational efficiency greatly decreases for a complex pipeline network or a long time horizon. Aiming at this problem, the paper develops an efficient decomposition approach, which is composed of two mixed integer linear programming (MILP) models. The first model divides the entire time horizon into several intervals according to delivery due dates and optimizes the transport routes and total transport volume during each interval with considering market demand, production campaigns and inventory limits. Then the solved results are used by the second model which sets the objective function as the membership function based on fuzzy delivery due dates. Besides, a series of operational constraints are also considered in the second model to obtain the optimal batch sequence, batch volume, delivery volume and delivery time in each node. Finally, the proposed approach is applied to a Chinese real-world pipeline network that includes 5 complex multi-product pipelines associated with 6 refineries and 2 depots. The results demonstrate that the proposed approach can provide a guideline for long-term pipeline network scheduling with delivery due dates.
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Al Braiki, Warda Awadh, Rayner Samuel Davila, Adriana Del Carmen Molina, Mohammed Azhar, Zayed Iqbal Shaik, Afra Saeed Alyaqoubi, and Haitham Alaa Eldin. "Digital Transformation Drives Reduction of the Inactive Strings Count. A Success Story in a Major National Oil Company." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211040-ms.

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Abstract This paper demonstrates a successful case story of how harnessing digitalization has significantly improved the Management of Inactive wells. An integrated web-based application was developed in house and fully deployed across the Company. It has demonstrated an immense added value by bringing key stakeholders in an automated and collaborative environment to standardize and improve the existing well reactivation cycle and mitigating well & facilities integrity threats. Inactive Strings Management System (ISMS) is tailored made for multiple disciplines such as production, petroleum, well integrity, facilities and reservoir engineers, as well as Corporate Units and Management, all connected through standards automated workflows. The new solution is composed by 13 main modules that covers the whole well reactivation cycle: a) Data Entry b)Validation, c) Endorsement, d) Live Well Inventory, e) Tracking and Monitoring, f) Well Problem & Status, g) Dashboards, h) Well history, i) Well Prioritization, j) Manager Approval, and k) Level 2 KPI's. 1) Managing Problematics Wells, and m) Project Related. The Inactive String Management Tool has proved to be vastly beneficial. Since its implementation in December 2021, it has successfully supported the reactivation of around 810 strings, and monitoring over 4800 operating strings, with an associated cumulative oil rate gain of 490,000 barrels, translated into a profit of around $23 MM (USD), and shortened the well reactivation cycle by 20%. The solution had led to major improvements on the current business and system processes by addressing major challenges including data integrity issues, lack of automation, systems integration, poor tracking of well reactivation actions, and most importantly, absence of a systematic approach to prompt multidisciplinary well revision by having a unique planform to manage the inactive strings, thru standardization of best practices and lessons learned across Assets. It has increased the well problem visibility and accountability of key stakeholders to firm, maturate and accelerate well reactivation actions in an automated and collaborative environment, reducing silos, ensuring alignment, sharing knowledge and information more effectively. Improved resources planning and production gain without jeopardizing well and facilities integrity. This solution is part of the Oil and Gas 4.0 company digital transformation strategy, encourages collaboration across departments, fostering a digital culture to rapidly react to business changes. It has laid down the foundation to sustain growth and a competitive edge in the digital age by applying deeper and more targeted analytics that enable better business decision-making, such as predictive analytics, artificial intelligence, and business process management.
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7

Jimenez, Guillermo, Arturo Molina, and Luis Canche. "Manufacturing Execution Systems Interoperability and Web Services Technologies." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-82330.

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Manufacturing Execution Systems (MES) rely between the shop floor and many systems that support the operation of a manufacturing enterprise such as Production and Inventory and Enterprise Resource Planning Tools. Interoperability with a multitude of platforms is thus one of the main problems to solve for implementation of a MES. This paper describes a software architecture based on the use of Web services technologies and discusses how interoperability issues are resolved in a much more seamless manner than with other previous middleware technologies.
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Fesenko, Dmitry Evgenievich. "The Image of the Future is Born in Urban Planning: Changing the Settlement Model as a Tool for Macroeconomic Transformations." In 6th International Conference “Futurity designing. Digital reality problems”. Keldysh Institute of Applied Mathematics, 2023. http://dx.doi.org/10.20948/future-2023-20.

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The article consists of three sections - two descriptive and one prescriptive. The first one proposes an analysis of the crisis phenomena in the settlement system: from its imbalance and delegation of the functions of strategizing spatial development from the state to development, to the absence in the Gradcodex of a provision on the development of the General Scheme of settlement and monopolization, the absorption of SMEs in the field of development. The second includes a list of the consequences of maintaining the status quo in the field of resettlement: from desertification of the country's territories and depopulation, spurred on by the migration of the population to the largest cities, to a further increase in the number of storeys and building density with the miniaturization of apartments in high-rises and the continuation of the policy of deindustrialization of the country. The third section formulates proposals aimed at changing the country's spatial development strategy, among them - the development of a General Settlement Scheme in the field of low-rise housing in accordance with the principles formulated by the Initiative Group, and a Strategy for the placement and development of productive forces, aimed at dispersed placement of production capacities, inventory of low-rise construction technologies, development of organizational and financial mechanisms to support low-rise construction based on accumulated regional experience, reorientation of transport infrastructure construction from a limited number of agglomerations towards the development of projects aimed at linking the country's space, legislative limitation of monopolization processes in the field of development and construction, creation Committee for Architecture and Urban Planning under the President of the Russian Federation, whose tasks would include, first of all, the strategizing of spatial development, etc.
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