A Study on Joint Production Sequencing, Production Rate, and Admission Controls for Maximizing Energy Consumption Efficiency in a Make-to-Order System with Multiple Customer Classes

2019 ◽  
Vol 30 (4) ◽  
pp. 391-405
Author(s):  
Eungab Kim
Keyword(s):  
Energy Consumption ◽  
Production Rate ◽  
Joint Production ◽  
Order System ◽  
Make To Order ◽  
Multiple Customer Classes ◽  
Consumption Efficiency

scholarly journals Optimization of Laser Engraving of Acrylic Plastics from the Perspective of Energy Consumption, CO2 Emission and Removal Rate

2021 ◽  
Vol 5 (3) ◽  
pp. 78
Author(s):  
Mohammad Muhshin Aziz Khan ◽  
Shanta Saha ◽  
Luca Romoli ◽  
Mehedi Hasan Kibria
Keyword(s):  
Energy Consumption ◽  
Production Rate ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Scanning Speed ◽  
Gas Emissions ◽  
Laser Engraving ◽  
Co2 Gas ◽  
Optimal Set

This paper focuses on optimizing the laser engraving of acrylic plastics to reduce energy consumption and CO2 gas emissions, without hindering the production and material removal rates. In this context, the role of laser engraving parameters on energy consumption, CO2 gas emissions, production rate, and material removal rate was first experimentally investigated. Grey–Taguchi approach was then used to identify an optimal set of process parameters meeting the goal. The scan gap was the most significant factor affecting energy consumption, CO2 gas emissions, and production rate, whereas, compared to other factors, its impact on material removal rate (MRR) was relatively lower. Moreover, the defocal length had a negligible impact on the response variables taken into consideration. With this laser-process-material combination, to achieve the desired goal, the laser must be focused on the surface, and laser power, scanning speed, and scan gap must be set at 44 W, 300 mm/s, and 0.065 mm, respectively.

scholarly journals Superabundant design

2016 ◽  
Vol 5 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pablo R. Velasco González
Keyword(s):  
Energy Consumption ◽  
Production Rate ◽  
Electronic Devices ◽  
Production Cycle ◽  
Trace Back ◽  
The Creation ◽  
Definition Of ◽  
Time And Energy

Tiziana Terranova draws attention to the necessity of questioning how algorithmically enabled automation works “in terms of control and monetization” and “what kind of time and energy” is being subsumed by it (Terranova 387). Cryptocurrencies are payment technologies that automate the production of money-like tokens (Bergstra and Weijland) following algorithmic rules to maintain a fixed production rate. Different kinds of energy and residues, which are not always acknowledged, are involved in this process. Here I distinguish between two closely linked layers in the Bitcoin token production: first, an algorithmic layer, which contains the instructions and rules for the creation of bitcoins; second, a hardware layer, which performs and embodies the former. While these layers work together, I will argue that they enact their own kind of logics of energy and waste. I will begin at the more visible end of the production cycle, the hardware layer, where the definition of waste and energy consumption is shared with many electronic devices; then I will trace back its algorithmic layer, which as I argue, follows a different logic.

scholarly journals Dynamic sourcing strategies for supply disruptions under consumer stockpiling

2021 ◽  
Author(s):  
Shanshan Li ◽  
Yong He ◽  
Li Zhou
Keyword(s):  
Order System ◽  
Joint Decision ◽  
Sourcing Strategies ◽  
Make To Order ◽  
Sourcing Strategy ◽  
Holding Cost ◽  
Future Consumption ◽  
Inventory Holding ◽  
Relative Factors

AbstractThis paper considers a make-to-order system where production gets disrupted due to a random supply failure. To avoid potential stock-out risk and responding price increase during disruption, customers might decide to stockpile extra units for future consumption. We investigate the contingent sourcing strategy for the manufacturer to cope with the disruption. To this end, we first discuss the optimal post-disruption stockpiling decision for customers. In view of expected disruption duration, price rise, and inventory holding cost, three types of stockpiling behavior are analytically provided for the customers: non-stockpiling, gradual stockpiling, and instantaneous stockpiling. Next, a model is formulated to optimize the joint decision of contingent sourcing time and quantity, with the objective of maximizing profit expectation. Finally, by conducting numerical analysis, we generate further insights into the role of relative factors and provide specific managerial suggestions on how to adapt dynamic contingent sourcing strategies to alleviate different disruptions, under different market environments and customer behaviors.

An optimal inventory model with interaction of lot size, production rate and lead-time in a fuzzy back-order system

2019 ◽  
Vol 53 (2) ◽  
pp. 517-538
Author(s):  
S. Priyan ◽  
P. Mala ◽  
S. Tiwari
Keyword(s):  
Decision Making ◽  
Production Rate ◽  
Lead Time ◽  
Trade Credit ◽  
Strategic Decision ◽  
Sensitivity Analyses ◽  
Order System ◽  
Lot Size ◽  
Order Rate ◽  
Back Order

This paper examines the decision-making about the interaction of lot size, production rate and lead time between a vendor and a buyer with the consideration of trade credit and fuzzy back-order rate. We assume that the lead time demand is distribution free and the back-order rate is triangular fuzzy number. An economic model is design to determine the optimal lot-size, production rate and lead time while minimizing system total cost. A minimax approach is applied to tackle the model and designed an iterative algorithm to obtain the optimal strategy. Numerical example and sensitivity analyses are given to demonstrate the performance of the proposed methodology and to highlight the differences between crisp and the fuzzy cases. This paper provides optimal decision support tools for managers in the form of mathematical model that improve operational, tactical, and strategic decision making in the fuzzy system. This paper aims to raise the awareness of managers with regard to realistic inventory problems.

Performance of Fuel Cell and Engine Based Cogeneration Systems in Heating and Cooling Applications

2004 ◽  
Author(s):  
Gregory J. Kowalski ◽  
Mansour Zenouzi
Keyword(s):  
Carbon Dioxide ◽  
Fuel Cell ◽  
Production Rate ◽  
Thermal Load ◽  
Carbon Dioxide Production ◽  
Thermodynamic System ◽  
Order System ◽  
Environment Impact ◽  
Heating And Cooling ◽  
Carbon Dioxide Production Rate

A generalized thermodynamic model is developed to describe cooling, heating and power generating systems. This model is based on reversible power generation and refrigeration devices with practical, irreversible heat exchanger processes provides valuable information on a system’s performance and allows easy comparisons among different systems at different loading conditions. Using both the first and second laws as well as the carbon dioxide production rate allows one to make a first order system assessment on its energy usage and environment impact. The use of the exergy destruction rate and insuring that its behavior be consistent with that of the first law performance is a important to insure that the thermodynamic system boundaries are correctly and completely defined. The importance of the total thermal load to required power ratio (HLRP) as a scaling parameter is demonstrated. While the reported results confirmed that generalized trends are not possible identify, a number of trends for limited conditions have been identified. The results have shown that a combined vapor compression/absorption refrigeration has higher first law utilization factors and lower carbon dioxide production rate for system with higher refrigeration to total thermal load ratios for all HLRP values. Fuel cell based subsystems outperform engine based subsystems for systems with large refrigeration loads.

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