Artificial Intelligence as a tool for industrial energy efficiency25 November 2022
At a time when the French economy is being called upon to be energy sober, it is imperative for the industrial sector to improve its energy performance and meet environmental challenges.
How can this be done? Better energy management, equipment monitoring... What if data analysis could help achieve these energy efficiency goals?
ENERGY EFFICIENCY AS A COMPETITIVENESS BOOSTER
In 2023, gas and electricity market prices will be more than 10 times higher than in 2020. For all manufacturers, reducing their energy bills is becoming a priority in order to remain competitive, in addition to meeting environmental challenges.
While the government has announced a series of measures to support companies in the face of rising energy prices, the transition to Industry 4.0 is now necessary to control energy consumption and reduce costs in the long term.
And for good reason: the industry of the future is an optimised and therefore energy-efficient industry. The time has come for sobriety, energy efficiency and energy savings for processes, equipment and buildings.
HARNESSING YOUR DATA: THE STARTING POINT FOR ENERGY EFFICIENCY
Make your process more reliable and control your energy consumption
In addition to measuring energy consumption (monitoring equipment and utilities), the challenge is to improve energy performance. Today, manufacturers expect to be able to use energy as a lever for competitiveness and continuous improvement.
Making the process more reliable in order to produce better over a given period of time makes it possible to increase performance and quality and to reduce energy consumption. Identifying drifts and over-consumption problems, optimising and predicting consumption are also the keys to energy management.
With analysis tools based on Artificial Intelligence technologies at the service of an energy policy, it is now possible to target energy sobriety, set energy performance objectives and measure results quickly. This is a real asset for optimising industrial processes and equipment for particularly important items such as electric motors (which can represent 80% of an industrial site's consumption), ventilation/air conditioning, pumps, heating or lighting.
Predictive maintenance: part of energy performance
By anticipating production line failures and bringing in maintenance at the right time, data analysis gives industry a new opportunity to reduce energy consumption with predictive maintenance.
How can this be done? By detecting anomalies and deviations linked to over-consumption of energy as early as possible, by ensuring that equipment is operating optimally to avoid any risk of wasting energy and raw materials by using poorly adjusted or faulty equipment, and by eliminating unplanned stoppages in production lines.
According to a McKinsey study, a modernised and optimised industrial process can reduce its energy consumption by 5 to 15% with predictive maintenance technologies.
CSR & Regulation
In a context of increasing CSR challenges, energy sobriety is no longer an option for the industrial sector.
In recent years, Corporate Social Responsibility has been structured around new environmental issues: transparency obligation on CO2 emissions, supply chain responsibility, constraints on energy consumption (RE 2020 standard)...
Industry now has a moral and regulatory obligation to take CSR into account in its strategic decisions.