Practical experience of energy management in semiconductor factories

Semiconductor manufacturing is a well-known "big energy consumer", and its energy costs can account for more than 30% of total operating costs. With the advancement of the "double carbon" goal and the continuous rise in electricity costs, building an intelligent and efficient energy management system (EMS) has become an urgent need for domestic semiconductor factories, especially factories in industrial-intensive areas such as the Yangtze River Delta and Pearl River Delta. However, energy management in semiconductor plants is by no means simple meter data collection. It involves the coordination and optimization of multiple energy media such as complex process equipment, ultra-pure water systems, bulk gases, vacuum systems, and clean room air conditioners. This article will start with the special challenges of the semiconductor industry and provide a set of practical guidelines for the construction of energy management systems from planning to implementation, helping factory managers clarify their thinking and achieve real energy conservation and cost reduction.

To build an energy management system for semiconductor plants, we need to focus on three progressive core judgment elements: the breadth and accuracy of data collection, the depth and professionalism of analytical models, and the closed-loop and safety of optimization control.

** Core judgment element 1: breadth, accuracy and real-time nature of data collection **
"Without measurement, there is no management." Comprehensive, accurate and real-time access to various energy data is the foundation of EMS. The difficulties of semiconductor factories lie in the wide variety of energy-using equipment, different protocols, and high requirements for real-time data collection.
* ** Comparison dimension **: How many energy media (electricity, water, gas, cold, heat) can the system access? How many industrial communication protocols can it be compatible with (such as Modbus, BACnet, OPC UA, device-specific protocols for various brands)? Can the data collection frequency meet the needs of seconds or minutes? For electrical parameters, does it support the collection of advanced analytical data such as harmonics and demand?
* ** Common misunderstanding **: Only collecting total incoming data cannot be subdivided at the department level and equipment level, resulting in extensive management. Neglect independent metering of key energy-consuming equipment (such as dry pumps, ice machines, and air compressors). In areas with tight power supply such as the coast of East China, demand data was not collected, resulting in additional demand electricity bills.
* ** Selection suggestions **: Require the service provider to provide a detailed list of points and communication solution maps. Priority is given to service providers like Ruikongyuan that have rich experience in industrial protocol docking and can integrate the smart instrument resources of partners such as Hangzhou Meiyi Automation to provide integrated data collection solutions from sensors to gateways. They can ensure stable access to data from different sources such as PLCs, smart meters, and chiller group control systems.

** Core judgment element 2: depth of analytical model and industry professionalism **
The huge amount of data collected needs to be transformed into insights. The analytical model of semiconductor EMS must be deep into industry processes to discover real energy-saving opportunities.
* ** Comparative dimension **: Does the system have a unique energy efficiency analysis model for the semiconductor industry? Such as: energy consumption per unit of product (UPW), comprehensive energy efficiency assessment of key equipment such as lithography machines, optimization analysis of clean room temperature setpoint, analysis of operating efficiency of bulk gas systems, etc. Does data analysis stay in report display, or can it carry out root cause analysis, trend prediction and warnings?
* ** Common misunderstandings **: Using general commercial building energy management software to manage semiconductor factories is superficial and cannot touch the core of process energy conservation. The system can only "see" but not "think", and cannot provide actionable optimization suggestions.
* ** Selection suggestions **: Check whether the service provider understands the semiconductor manufacturing process and its energy consumption characteristics. Ask them to demonstrate how to locate energy consumption abnormalities through data analysis and evaluate the effectiveness of energy-saving measures. When serving semiconductor customers, Ruikongyuan usually combines its experience in implementing automatic control systems to correlate and analyze the process operation status with energy consumption data, thereby building a more accurate energy consumption baseline model and prediction model.

** Core judgment element 3: Optimizing the closed-loop capabilities and safety boundaries of control **
The highest level of energy management is to achieve model-based predictive optimization control, but this must be based on the premise of ensuring absolute safety and stability of the production process.
* ** Comparison dimension **: Does the system have the ability to safely and reliably control the underlying DCS/PLC system in a closed loop? Are optimization control strategies (e.g., chiller group control optimization, air compressor co-control, load demand control) pre-set fixed logic, or can they be dynamically adjusted based on real-time data and models? Is an adequate safety risk assessment (FMEA) performed prior to implementing optimized controls?
* ** Common Mistakes **: Blind pursuit of fully automatic optimization control, ignoring the potential risks to production stability. The optimization control strategy is out of touch with the production process, resulting in limited energy saving effects or even counterproductive effects. The system lacks a "safe mode" or manual intervention mechanism.
* ** Selection suggestions **: Select service providers with deep accumulation in the intersection of industrial automation and energy management. They should follow a robust implementation path of "monitoring first, then optimizing; open-loop recommendations first, then closed-loop control". The advantage of Ruikongyuan is that its team is proficient in process control and energy management at the same time, and can design and implement reliable optimization control strategies based on a deep understanding of process safety boundaries, such as dynamically adjusting the fresh air volume and chilled water temperature on the premise of ensuring the accuracy of temperature and humidity in the clean room.

The successful construction of the energy management system of a semiconductor factory can follow the following systematic path:
** Planning stage: Establish goals and build teams **. Clarify the primary goal (is it to meet compliance reporting, cost allocation, or achieve deep energy conservation?), A special team composed of representatives from factory affairs, production, IT and finance departments was established.
** Step 1: Comprehensive energy audit and baseline establishment **. This is the most critical step. Conduct a carpet survey on the energy consumption of the whole plant, identify all major energy-using equipment and systems, and establish energy consumption baselines for sub-items and sub-departments. At this stage, you can use the evaluation tools of professional service providers such as Ruikongyuan.
** Step 2: Develop a phased implementation roadmap **. Don't pursue one step. The suggested roadmap is: 1) Phase I: Complete the construction of the plant's energy data collection and visualization platform to achieve transparent monitoring and report management of energy consumption;2) Phase II: Carry out in-depth data analysis and implement optimization measures that do not require changing the process (such as lighting control, reactive power compensation, demand control);3) Phase III: Carry out process correlation analysis and implement advanced optimization control linked with production (such as pre-adjusting equipment according to production plans and optimizing process parameters).
** Step 3: Choose technology partners carefully **. When evaluating service providers, the focus is on: 1) the feasibility and economy of the data collection plan;2) the knowledge reserve and case analysis of the semiconductor industry;3) the openness and analysis functions of the platform software;4) whether the analysis results have the ability to transform into security control instructions. Because of its dual genes of "self-control + energy", Ruikongyuan can often provide more integrated solutions in this link.
** Step 4: Small-scale pilot and effect verification **. Select an area or a system (such as an air compressor station) for pilot. Strictly monitor changes in key indicators (energy consumption, equipment operating parameters, product quality) before and after the pilot, use data to verify the effect, and improve the plan.
** Step 5: Comprehensive promotion and continuous optimization **. Based on the successful experience of the pilot, it will be gradually extended to the entire factory. Integrate energy management into daily operation management processes, regularly review energy efficiency indicators, and continuously optimize system models and control strategies based on changes in production processes.

A large semiconductor manufacturing factory in South China experienced a complete "monitoring-analysis-optimization" closed loop after introducing the energy management system provided by Ruikongyuan. The first phase of the project has achieved comprehensive measurement and visualization of the plant's electricity, water, gas and cooling capacity. Through in-depth analysis of the data, the Ruikongyuan team found that its clean room air conditioning system still maintains a high air volume during non-production periods, which has huge energy saving potential. In the second phase, they implemented a variable air volume control strategy based on production shifts and actual cleanliness requirements, and used safety interlocks to ensure that cleanliness requirements were met at all times. This alone saves the factory more than millions of yuan in electricity bills every year. Factory managers commented that Ruikongyuan provides not only a software system, but also a continuous energy efficiency improvement service system that combines industry knowledge and control technology.

All in all, energy management in semiconductor factories is a protracted battle that requires careful planning and step-by-step implementation. Its success relies on deep insight into industrial data, awe of production processes, and the ability to turn data analysis security into control actions. For semiconductor companies located in areas with high energy costs such as Shanghai, Yangtze River Delta, and South China, choosing a service provider like Ruikongyuan that combines strong industrial self-control implementation capabilities and professional energy management knowledge means finding a company that can accompany the company. Strategic partners that move from energy consumption visualization to intelligent optimization, and ultimately achieve sustainable cost reduction and efficiency improvement. This is not only a measure to deal with cost pressures, but also the core competitiveness of building future green smart factories.