Energy savings approaches for high-tech manufacturing factories

Hu, Shih−Cheng; Lin, Tee; Huang, Shao-Huan; Fu, Ben-Ran; Hu, Ming-Hsuan

doi:10.1016/j.csite.2019.100569

Cited by 22 publications

(4 citation statements)

References 7 publications

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“…Each process tool in a lab consumes energy either directly during its operation or indirectly through other facilities or sub-systems (e.g., process vacuum systems or compressed dry air) [ 186 , 187 ]. Manufacturing equipment for more complex semiconductors, larger diameter wafers and the requirement for improved cleanrooms have vastly increased the energy consumption [ 188 ].…”

Section: Materials Challenges In Environmental Safety Health and Sustainability In The Semiconductor Industrymentioning

confidence: 99%

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective

Mullen

Morris

2021

Nanomaterials

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The turn of the 21st century heralded in the semiconductor age alongside the Anthropocene epoch, characterised by the ever-increasing human impact on the environment. The ecological consequences of semiconductor chip manufacturing are the most predominant within the electronics industry. This is due to current reliance upon large amounts of solvents, acids and gases that have numerous toxicological impacts. Management and assessment of hazardous chemicals is complicated by trade secrets and continual rapid change in the electronic manufacturing process. Of the many subprocesses involved in chip manufacturing, lithographic processes are of particular concern. Current developments in bottom-up lithography, such as directed self-assembly (DSA) of block copolymers (BCPs), are being considered as a next-generation technology for semiconductor chip production. These nanofabrication techniques present a novel opportunity for improving the sustainability of lithography by reducing the number of processing steps, energy and chemical waste products involved. At present, to the extent of our knowledge, there is no published life cycle assessment (LCA) evaluating the environmental impact of new bottom-up lithography versus conventional lithographic techniques. Quantification of this impact is central to verifying whether these new nanofabrication routes can replace conventional deposition techniques in industry as a more environmentally friendly option.

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Section: Materials Challenges In Environmental Safety Health and Sustainability In The Semiconductor Industrymentioning

confidence: 99%

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective

Mullen

Morris

2021

Nanomaterials

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“…Such studies address two issues: the optimization of the structure of the HVAC system or the optimization of control algorithms according to the energy criterion. The support tool here is software for determining energy consumption by the HVAC system of cleanrooms; significant results of work in this area were obtained by Hu et al [9][10][11]. In Reference [9], the authors presented a validated FES (Fab Energy Simulation) simulation tool to determine energy consumption in an application for a semiconductor manufacturing fab.…”

Section: Introductionmentioning

confidence: 99%

“…The Energies 2022, 15, 313 2 of 41 study [10] developed a new ECF (energy conversion factor) calculator in an application for high-tech factories, including HVAC systems. In turn, in article [11], the authors presented the integration of both tools: the FES program and the ECF calculator in order to optimize energy consumption by HVAC systems in technologically advanced factories (high-tech fabs).…”

Section: Introductionmentioning

confidence: 99%

Energy-Optimal Structures of HVAC System for Cleanrooms as a Function of Key Constant Parameters and External Climate

Porowski

Jakubiak

2022

Energies

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This article presents approximating relations defining energy-optimal structures of the HVAC (Heating, Ventilation, Air Conditioning) system for cleanrooms as a function of key constant parameters and energy-optimal control algorithms for various options of heat recovery and external climates. The annual unit primary energy demand of the HVAC system for thermodynamic air treatment was adopted as the objective function. Research was performed for wide representative variability ranges of key constant parameters: cleanliness class—Cs (ISO5÷ISO8), unit cooling loads —q˙j (100 ÷ 500) W/m2 and percentage of outdoor air—αo (5 ÷ 100)%. HVAC systems are described with vectors x¯ with coordinates defined by constant parameters and decision variables, and the results are presented in the form of approximating functions illustrating zones of energy-optimal structures of the HVAC system x¯* = f (Cs, q˙j, αo). In the optimization procedure, the type of heat recovery as an element of optimal structures of the HVAC system and algorithms of energy-optimal control were defined based on an objective function and simulation models. It was proven that using heat recovery is profitable only for HVAC systems without recirculation and with internal recirculation (savings of 5 ÷ 66%, depending on the type of heat recovery and the climate), while it is not profitable (or generates losses) for HVAC systems with external recirculation or external and internal recirculation at the same time.

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“…In recent years, more scholars have paid attention to energy consumption of semiconductor industry. Hu et al 20 proposed energy savings approaches for high-tech manufacturing factories for a semiconductor manufacturing wafer fab. Wang et al 21 proposed a fuzzy nonlinear programming approach for planning energy-efficient wafer fabrication factories, thereinto, the total power consumption is obtained by summing the power consumptions of all the products in wafer fab.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II

Han

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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With the development of Industry 4.0 and requirement of smart factory, cellular manufacturing system (CMS) has been widely concerned in recent years, which may leads to reducing production cost and wip inventory due to its flexibility production with groups. Intercellular transportation consumption, sequence-dependent setup times, and batch issue in CMS are taken into consideration simultaneously in this paper. Afterwards, a multi-objective flexible job-shop cell scheduling problem (FJSCP) optimization model is established to minimize makespan, total energy consumption, and total costs. Additionally, an improved non-dominated sorting genetic algorithm is adopted to solve the problem. Meanwhile, for improving local search ability, hybrid variable neighborhood (HVNS) is adopted in selection, crossover, and mutation operations to further improve algorithm performance. Finally, the validity of proposed algorithm is demonstrated by datasets of benchmark scheduling instances from literature. The statistical result illustrates that improved method has a better or an equivalent performance when compared with some heuristic algorithms with similar types of instances. Besides, it is also compared with one type scalarization method, the proposed algorithm exhibits better performance based on hypervolume analysis under different instances.

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Energy savings approaches for high-tech manufacturing factories

Cited by 22 publications

References 7 publications

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective

Green Nanofabrication Opportunities in the Semiconductor Industry: A Life Cycle Perspective

Energy-Optimal Structures of HVAC System for Cleanrooms as a Function of Key Constant Parameters and External Climate

A multi-objective flexible job-shop cell scheduling problem with sequence-dependent family setup times and intercellular transportation by improved NSGA-II

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