An efficient production scheduling based on queuing theory in systems with synchronous part transfer during a demand response event

Author(s):  
Alemayehu Addisu ◽  
Hakim Badis ◽  
Laurent George ◽  
Pierre Courbin
2015 ◽  
Vol 48 (8) ◽  
pp. 385-390 ◽  
Author(s):  
Chudong Tong ◽  
Nael H. El-Farra ◽  
Ahmet Palazoglu

2019 ◽  
Vol 15 (2) ◽  
pp. 942-953 ◽  
Author(s):  
Xu Gong ◽  
Ying Liu ◽  
Niels Lohse ◽  
Toon De Pessemier ◽  
Luc Martens ◽  
...  

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1189
Author(s):  
Xinchao Li ◽  
Xin Jin ◽  
Shan Lu ◽  
Zhe Li ◽  
Yue Wang ◽  
...  

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.


2017 ◽  
Vol 168 ◽  
pp. 239-253 ◽  
Author(s):  
Xu Gong ◽  
Marlies Van der Wee ◽  
Toon De Pessemier ◽  
Sofie Verbrugge ◽  
Didier Colle ◽  
...  

2013 ◽  
Vol 572 ◽  
pp. 235-238
Author(s):  
Soumia Ichoua ◽  
Agnes Pechmann

In this paper we investigate the elaboration of an efficient production schedule for sustainable manufacturing systems. Because renewable energies are irregular by nature as they often depend on meteorological conditions (e.g. wind and solar energy), their use in the competitive field of manufacturing production must be addressed with caution. The challenge is to elaborate a reliable production schedule that accommodates energy stochastic fluctuations while satisfying customer and operational constraints. We propose to solve the problem using a meta-heuristic based on Tabu search and discuss major elements that are critical to the success of this approach.


Author(s):  
Miguel A. Peinado-Guerrero ◽  
Nicolas A. Campbell ◽  
Jesus R. Villalobos ◽  
Patrick E. Phelan

Abstract A framework is proposed for demand-side load management (DSLM) of manufacturers participating in demand response (DR) programs. Utilities are increasingly focused on enticing their portfolios of energy end-users to adjust their energy use patterns in a mutually beneficial manner such as with DR programs. DR programs allow the utility to receive bulk peak load reduction and the participating end-user to receive credit towards their electricity bills. Once an end-user is enrolled in a DR program, they receive periodic requests for some amount of load reduction, typically the day before. Failing to respond to a DR signal will usually cost the end-user handsomely. The end-user is often left to their own discretion on how to attain the level of load reduction requested by the utility. For a manufacturer, this means if the request in load reduction is high enough, they will need to figure out how to curtail production. On the other hand, if the load reduction requested is small enough to need no disruption to production, the utility may be missing out on untapped DR capabilities that could be offered from the ability of the manufacturer to reschedule their production. In either case, the availability of an optimal plan for the manufacturer to best schedule its production in response to a DR event can maximize the benefits for both parties. Most of the research found in literature addresses production scheduling with minimal energy use or cost with respect to a time-of-use price tariff. A system that communicates the desires of the utility to the end-user for a DR event and provides the end-user with support in the decision-making process remains to be developed. The framework proposed addresses these shortcomings, considering the introduction of IoT capabilities and the physical constraints of the manufacturer.


2018 ◽  
Vol 66 (6) ◽  
pp. 492-502 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Sujil A

Abstract In a highly competitive environment, effective production is one of the key issues which can be addressed by efficient production planning and scheduling in the manufacturing system. This paper develops an agent-based architecture which enables integration of production planning and scheduling. In addition, this architecture will facilitate real time production scheduling as well as provide a multi-agent system (MAS) platform on which multiple agents will interact to each other. A case study of job-shop manufacturing system (JMS) has been considered in this paper for implementing the concept of MAS. The modeling of JMS has been created in SimEvents which integrates an agent-based architecture developed by Stateflow to transform into dynamic JMS. Finally, the agent-based architecture is evaluated using utilization of each machine in the shop floor with respect to time.


2021 ◽  
Vol 104 ◽  
pp. 104359
Author(s):  
Guiliang Gong ◽  
Raymond Chiong ◽  
Qianwang Deng ◽  
Wenwu Han ◽  
Like Zhang ◽  
...  

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