scholarly journals An Analysis of Research Trends in the Sustainability of Production Palnning

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 483
Author(s):  
Mohamed Saeed khaled ◽  
Ibrahim Abdelfadeel Shaban ◽  
Ahmed Karam ◽  
Mohamed Hussain ◽  
Ismail Zahran ◽  
...  
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Systems ◽  
Lot Sizing ◽  
Raw Materials ◽  
Social Indicators ◽  
Sustainable Production ◽  
Future Research ◽  
Scheduling Problems ◽  
Planning Problems

Sustainability has become of great interest in many fields, especially in production systems due to the continual increase in the scarcity of raw materials and environmental awareness. Recent literature has given significant attention to considering the three sustainability pillars (i.e., environmental, economic, and social sustainability) in solving production planning problems. Therefore, the present study conducts a review of the literature on sustainable production planning to analyze the relationships among different production planning problems (e.g., scheduling, lot sizing, aggregate planning, etc.) and the three sustainability pillars. In addition, we analyze the identified studies based on the indicators that define each pillar. The results show that the literature most frequently addresses production scheduling problems while it lacks studies on aggregate production planning problems that consider the sustainability pillars. In addition, there is a growing trend towards obtaining integrated solutions of different planning problems, e.g., combining production planning problems with maintenance planning or energy planning. Additionally, around 45% of the identified studies considered the integration of the economic and the environmental pillars in different production planning problems. In addition, energy consumption and greenhouse gas emissions are the most frequent sustainability indicators considered in the literature, while less attention has been given to social indicators. Another issue is the low number of studies that have considered all three sustainability pillars simultaneously. The finidings highlight the need for more future research towards holistic sustainable production planning approaches.

scholarly journals A review of energy-efficient scheduling in intelligent production systems

2019 ◽  
Vol 6 (2) ◽  
pp. 237-249 ◽  
Author(s):  
Kaizhou Gao ◽  
Yun Huang ◽  
Ali Sadollah ◽  
Ling Wang
Keyword(s):  
Energy Efficiency ◽  
Production Scheduling ◽  
Energy Cost ◽  
Energy Efficient ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Future Research ◽  
Scheduling Problems ◽  
Improve Energy Efficiency ◽  
Energy Efficient Scheduling

Abstract Recently, many manufacturing enterprises pay closer attention to energy efficiency due to increasing energy cost and environmental awareness. Energy-efficient scheduling of production systems is an effective way to improve energy efficiency and to reduce energy cost. During the past 10 years, a large amount of literature has been published about energy-efficient scheduling, in which more than 50% employed swarm intelligence and evolutionary algorithms to solve the complex scheduling problems. This paper aims to provide a comprehensive literature review of production scheduling for intelligent manufacturing systems with the energy-related constraints and objectives. The main goals are to summarize, analyze, discuss, and synthesize the existing achievements, current research status, and ongoing studies, and to give useful insight into future research, especially intelligent strategies for solving the energy-efficient scheduling problems. The scope of this review is focused on the journal publications of the Web of Science database. The energy efficiency-related publications are classified and analyzed according to five criteria. Then, the research trends of energy efficiency are discussed. Finally, some directions are pointed out for future studies.

scholarly journals Carbon-Efficient Production Scheduling of a Bioethanol Plant Considering Diversified Feedstock Pelletization Density: A Case Study

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1189
Author(s):  
Xinchao Li ◽  
Xin Jin ◽  
Shan Lu ◽  
Zhe Li ◽  
Yue Wang ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Production Scheduling ◽  
Raw Materials ◽  
Future Research ◽  
Efficient Production ◽  
Emission Model ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Total Profit

This paper presents a dual-objective optimization model for production scheduling of bioethanol plant with carbon-efficient strategies. The model is developed throughout the bioethanol production process. Firstly, the production planning and scheduling of the bioethanol plant’s transportation, storage, pretreatment, and ethanol manufacturing are fully considered. Secondly, the carbon emissions in the ethanol manufacturing process are integrated into the model to form a dual-objective optimization model that simultaneously optimizes the production plan and carbon emissions. The effects of different biomass raw materials with optional pelletization density and pretreatment methods on production scheduling are analyzed. The influence of demand and pretreatment cost on selecting a pretreatment method and total profit is considered. A membership weighted method is developed to solve the dual-objective model. The carbon emission model and economic model are integrated into one model for analysis. An example is given to verify the effectiveness of the optimization model. At the end of the paper, the limitation of this study is discussed to provide directions for future research.

scholarly journals A comprehensive approach for managing feasible solutions in production planning by an interacting network of Zero-Suppressed Binary Decision Diagrams

2015 ◽  
Vol 2 (2) ◽  
pp. 105-112 ◽  
Author(s):  
Keita Takahashi ◽  
Masahiko Onosato ◽  
Fumiki Tanaka
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Binary Decision Diagrams ◽  
Solution Space ◽  
Product Lifecycle Management ◽  
Planning Problem ◽  
Decision Diagrams ◽  
Binary Decision ◽  
Feasible Solutions ◽  
Planning Problems

Abstract Product Lifecycle Management (PLM) ranges from design concepts of products to disposal. In this paper, we focus on the production planning phase in PLM, which is related to process planning and production scheduling and so on. In this study, key decisions for the creation of production plans are defined as production-planning attributes. Production-planning attributes correlate complexly in production-planning problems. Traditionally, the production-planning problem splits sub-problems based on experiences, because of the complexity. In addition, the orders in which to solve each sub-problem are determined by priorities between sub-problems. However, such approaches make solution space over-restricted and make it difficult to find a better solution. We have proposed a representation of combinations of alternatives in production-planning attributes by using Zero-Suppressed Binary Decision Diagrams. The ZDD represents only feasible combinations of alternatives that satisfy constraints in the production planning. Moreover, we have developed a solution search method that solves production-planning problems with ZDDs. In this paper, we propose an approach for managing solution candidates by ZDDs' network for addressing larger production-planning problems. The network can be created by linkages of ZDDs that express constraints in individual sub-problems and between sub-problems. The benefit of this approach is that it represents solution space, satisfying whole constraints in the production planning. This case study shows that the validity of the proposed approach.

scholarly journals A COMPARATIVE STUDY OF THE USABILITY OF DIFFERENT PRODUCTION SCHEDULING ALGORITHMS AND RULES

2021 ◽  
Vol 2 ◽  
pp. 41-46
Author(s):  
Pavol Jurík
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Job Shop ◽  
Flow Shop ◽  
Production Systems ◽  
Scheduling Problems ◽  
History Of ◽  
Service Object ◽  
The Right ◽  
Production Plans

Production scheduling optimization is a very important part of a production process. There are production systems with one service object and systems with multiple service objects. When using several service objects, there are systems with service objects arranged in a parallel or in a serial manner. We also distinguish between systems such as flow shop, job shop, open shop and mixed shop. Throughout the history of production planning, a number of algorithms and rules have been developed to calculate optimal production plans. These algorithms and rules differ from each other in the possibilities and conditions of their application. Since there are too many possible algorithms and rules it is not easy to select the proper algorithm or rule for solving a specific scheduling problem. In this article we analyzed the usability of 33 different algorithms and rules in total. Each algorithm or rule is suitable for a specific type of problem. The result of our analysis is a set of comparison tables that can serve as a basis for making the right decision in the production process decision-making process in order to select the proper algorithm or rule for solving a specific problem. We believe that these tables can be used for a quick and easy selection of the proper algorithm or rule for solving some of the typical production scheduling problems.

scholarly journals Combining Polyhedral Approaches and Stochastic Dual Dynamic Integer Programming for Solving the Uncapacitated Lot-Sizing Problem Under Uncertainty

2021 ◽  
Author(s):  
Franco Quezada ◽  
Céline Gicquel ◽  
Safia Kedad-Sidhoum
Keyword(s):  
Integer Programming ◽  
Production Planning ◽  
Optimization Problem ◽  
Lot Sizing ◽  
Computational Experiments ◽  
Scenario Tree ◽  
Partial Decomposition ◽  
Large Size ◽  
Lot Sizing Problem ◽  
Planning Problems

We study the uncapacitated lot-sizing problem with uncertain demand and costs. The problem is modeled as a multistage stochastic mixed-integer linear program in which the evolution of the uncertain parameters is represented by a scenario tree. To solve this problem, we propose a new extension of the stochastic dual dynamic integer programming algorithm (SDDiP). This extension aims at being more computationally efficient in the management of the expected cost-to-go functions involved in the model, in particular by reducing their number and by exploiting the current knowledge on the polyhedral structure of the stochastic uncapacitated lot-sizing problem. The algorithm is based on a partial decomposition of the problem into a set of stochastic subproblems, each one involving a subset of nodes forming a subtree of the initial scenario tree. We then introduce a cutting plane–generation procedure that iteratively strengthens the linear relaxation of these subproblems and enables the generation of an additional strengthened Benders’ cut, which improves the convergence of the method. We carry out extensive computational experiments on randomly generated large-size instances. Our numerical results show that the proposed algorithm significantly outperforms the SDDiP algorithm at providing good-quality solutions within the computation time limit. Summary of Contribution: This paper investigates a combinatorial optimization problem called the uncapacitated lot-sizing problem. This problem has been widely studied in the operations research literature as it appears as a core subproblem in many industrial production planning problems. We consider a stochastic extension in which the input parameters are subject to uncertainty and model the resulting stochastic optimization problem as a multistage stochastic integer program. To solve this stochastic problem, we propose a novel extension of the recently published stochastic dual dynamic integer programming (SDDiP) algorithm. The proposed extension relies on two main ideas: the use of a partial decomposition of the scenario tree and the exploitation of existing knowledge on the polyhedral structure of the stochastic uncapacitated lot-sizing problem. We provide the results of extensive computational experiments carried out on large-size randomly generated instances. These results show that the proposed extended algorithm significantly outperforms the SDDiP at providing good-quality solutions for the stochastic uncapacitated lot-sizing problem. Although the paper focuses on a basic lot-sizing problem, the proposed algorithmic framework may be useful to solve more complex practical production planning problems.

scholarly journals OPTIMASI JUMLAH PRODUKSI BAJA RINGAN MENGGUNAKAN METODE LINEAR PROGRAMMING

2020 ◽  
Vol 3 (2) ◽  
pp. 313
Author(s):  
Willis Thedra ◽  
Iwan B. Santoso
Keyword(s):  
Linear Programming ◽  
Mild Steel ◽  
Production Planning ◽  
Production Scheduling ◽  
Raw Materials ◽  
Steel Production ◽  
Working Hours ◽  
The Real ◽  
Different Thickness ◽  
Production Target

AbstractLinear programming can analyze various constraints related to the real conditions in the company and provide the best solution. In this research, light steel production planning is carried out for 6 working days, where there are 4 types of mild steel products with different thickness. With this method, production scheduling is obtained per day and the profit gained during the week is, when the price of raw materials is normal, a profit of Rp 179,005,800 was obtained; when the price of raw materials decreased, a profit of Rp 171,143,000 was obtained, and when the price of raw materials rose, a profit of Rp 205,766,400 was obtained. In this study several scenarios were conducted, such as scenario 1, the machine used must not be damaged on the first day of production because the production target will not be achieved, then for scenario 2 an increase in the number of requests was 10% and for scenario 3 the reduction in working hours was obtained for a maximum of one hour, if more than one hour the production target will not be achieved.AbstrakPemrograman linier dapat menganalisis berbagai kendala terkait dengan kondisi nyata di perusahaan dan memberikan solusi terbaik. Pada penelitian ini dilakukan perencanaan produksi baja ringan untuk 6 hari kerja, dimana terdapat 4 jenis produk baja ringan dengan ketebalan yang berbeda-beda. Dengan metode ini didapatkan penjadwalan produksi per hari dan keuntungan yang didapat selama seminggu yaitu, pada saat harga bahan baku normal maka diperoleh keuntungan sebesar Rp 179.005.800,-; saat harga bahan baku turun diperoleh keuntungan sebesar Rp 171.143.000,-, dan saat harga bahan baku naik diperoleh keuntungan sebesar Rp 205.766.400,-. Pada penelitian ini juga dilakukan beberapa skenario seperti skenario 1 mesin yang dipakai tidak boleh mengalami kerusakan pada hari pertama produksi karena target produksi tidak akan tercapai, kemudian untuk skenario 2 peningkatan jumlah permintaan sebesar 10% dan untuk skenario 3 pengurangan jam kerja diperoleh maksimal selama satu jam, jika lebih dari satu jam maka tidak akan tercapai target produksi.

scholarly journals Usulan Kebijakan Persediaan Bahan Baku dengan Metode Lot Sizing pada Perusahaan Manufaktur Gelas Plastik

2018 ◽  
Vol 11 (2) ◽  
Author(s):  
Mirna Lusiani ◽  
Eko Verdianto
Keyword(s):  
Inventory Control ◽  
Production Planning ◽  
Lot Sizing ◽  
Raw Materials ◽  
Raw Material ◽  
Order Quantity ◽  
Inventory Cost ◽  
Cup Product ◽  
Manufacturing Company ◽  
Fixed Period

This research was made with the aim to make production planning and inventory control in manufacturing company of plastic glass, especially for main raw material from 14 oz plastic cup product, that is Resin-HE 2.0 and whitening using lot sizing method. Due to the fluctuating demand and the accumulation of raw materials in the warehouse, the company needs for production planning and inventory control. The lot-sizing method used in this research is Period Order Quantity (POQ), Lot For Lot (LFL) and Fixed Period Requirement (FPR) which each method have a different concept. The result by using FPR Method 3 weeks and LFL in inventory control will give the lowest inventory cost to the company that is equal to Rp. 159.400,00 for Resin-HE 2.0 and Rp. 39.600,00 for whitening.

scholarly journals Extended Model Formulation of the Proportional Lot-Sizing and Scheduling Problem with Lost Demand Costs

2011 ◽  
Vol 5 (1) ◽  
pp. 49-56
Author(s):  
Waldemar Kaczmarczyk
Keyword(s):  
Lot Sizing ◽  
Valid Inequalities ◽  
Mixed Integer ◽  
Extended Model ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Model Formulation ◽  
Mip Models ◽  
Planning Problems ◽  
Lot Sizing And Scheduling

We consider mixed-integer linear programming (MIP) models of production planning problems known as the small bucket lot-sizing and scheduling problems. We present an application of a class of valid inequalities to the case with lost demand (stock-out) costs. Presented results of numerical experiments made for the the Proportional Lot-sizing and Scheduling Problem (PLSP) confirm benefits of such extended model formulation.

A Review of Multi Agent based Production Scheduling in Manufacturing System

2020 ◽  
Vol 14 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Rashpal S. Ahluwalia
Keyword(s):  
Production Scheduling ◽  
Global Economy ◽  
Manufacturing Systems ◽  
Manufacturing Sector ◽  
Local Economy ◽  
Future Research ◽  
Scheduling Problems ◽  
Key Issues ◽  
Multi Agent ◽  
Traditional Approaches

Backgrounds: The manufacturing sector has seen dynamic changes during the last few years, namely the move from product-oriented local economy to customer-driven global economy. In this environment, manufacturing systems have been required to deliver highly flexible, demand-driven and customized products. Hence, multi agent system (MAS) technology can play an important role in making highly responsive production scheduling systems in order to meet dynamic and uncertain changes in demand. Methods: This paper offers a review of MAS for production scheduling problems in manufacturing systems. The objective of the paper is twofold. First, it describes traditional and MAS based approaches for different production scheduling problems and presents advantages of MAS over traditional approaches. Second, it aims to review different MAS platforms and evaluate some key issues involved in MAS based production scheduling. Results: A variety of different MAS applications in production scheduling is reviewed in four categories of key issues: agent encapsulation, agent organization, agent coordination & negotiation and agent learning. Conclusion: Finally, this review presents a conceptual framework to implement MAS in production scheduling and also highlights the future research opportunities as well as challenges.

Penerapan Material Requirement Planning (MRP) dengan Mempertimbangkan Lot Sizing dalam Pengendalian Bahan Baku pada PT. Phapros, Tbk.

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
Adelia Chandradevi ◽  
Nia Budi Puspitasari
Keyword(s):  
Pharmaceutical Company ◽  
Inventory Control ◽  
Production Planning ◽  
Lot Sizing ◽  
Raw Materials ◽  
Raw Material ◽  
Material Requirement Planning ◽  
Material Requirement ◽  
Control Division

PT. Phapros Tbk is one of the oldest and biggest pharmaceutical company in Indonesia. As raw material inventory plays a key role to compete in this type of industry, it is important for PT. Phapros, Tbk to keep it well maintained. However, the Production Planning and Inventory Control Division, whose responsibility is planning and controlling the raw material has not implemented the Material Requirement Planning (MRP) method that causes a problem regarding the overstock of captopril, the ingredient for producing captopril 25 mg tablet. There are too much raw materials ordered and ends up with higher expense. The author proposed a lotting method to develop an efficient raw material planning. Results shows that using Wagner Within Algorithm method can help the company minimizes the total expense spent by Rp 984.977.

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