Saar Yoskovitz discusses maintaining profitability while prioritizing the environment
With the world’s population continually growing and inflation showing only small signs of easing, there will always be a need for affordable goods. In addition, governments, financing and communities worldwide will likely expect meaningful change from businesses in every sector, especially manufacturing. It is crucial for businesses to embrace sustainable practices to combat these environmental challenges and retain customers. By minimizing the environmental impact of production processes and efficiently utilizing energy and natural resources, manufacturers can pave the way for a more sustainable future.
Production has its challenges. To address this issue, manufacturers need to invest in various areas, including technology, equipment, knowledge, and training, to improve sustainability. It’s a balancing act for manufacturers: they need to upgrade to sustainable practices without passing on the cost to consumers and remain ethical.
Agencies such as the Environmental Protection Agency (EPA) are actively supporting manufacturers in their efforts to build a strong and sustainable infrastructure. But how can manufacturers maintain profitability while prioritizing environmental sustainability?
The answer is AI
Manufacturing processes involve complex machinery that requires precise calibration to perform efficiently. Studies have shown that inefficient machinery alone can result in a 12-to-15 percent increase in energy consumption for manufacturers, exacerbating costs and pollution. However, AI, when purpose-built for manufacturing, can provide a comprehensive overview of production lines by delving into their inner workings. By leveraging AI, manufacturers can make informed decisions and continuously improve their processes. AI-powered algorithms can analyse vast amounts of data and provide valuable insights into critical questions, such as predicting machine failures, identifying crucial machine parts on the brink of breakage, and optimizing production lines. These insights lead to enhanced efficiency, improved production health and safety, and reduced waste and pollution. Embracing AI solutions in manufacturing provides manufacturers with the means to solve complex problems that surpass the capabilities of human experience and expertise.
AI not only aids in designing sustainable manufacturing processes but also enables predictive maintenance by proactively monitoring machines. Real-time insights gathered through sensors can continuously assess machine health, allowing manufacturers to optimize quality, yield, waste, and other crucial metrics while minimizing downtime. As factories optimize their operations, the amount of waste and pollution naturally decreases, leading to improved profit margins. And implementing AI is not as complex as it may seem. It only takes three steps.
Evolve traditional mindsets
Manufacturers must abandon the notion that sustainability and profitability are mutually exclusive. AI-powered machine health and process health offer the ideal balance between sustainability and profitability, eliminating the need for compromise by showing manufacturers how they can cut their energy usage through pre-emptive maintenance and by avoiding machine failures. However, changing mindsets is not enough to advance technology and embrace sustainable practices without compromising business success.
Create change management processes
The next step on the path to sustainable manufacturing is planning and developing a well-documented change management process. As AI insights bring about rapid changes, it is crucial to ensure that the team is prepared and capable of adapting quickly. A robust change management process enables smoother transitions, allowing more time to focus on innovation rather than getting the team on board.
Leverage existing tools
Manufacturing processes undergo constant changes, and AI can assist in this transition. By using a reliable platform, manufacturers can track assets and optimize resource usage. Often, companies overlook the available tools as they expand, leading to costly inefficiencies. The use of AI and machine learning solutions can optimize existing equipment and streamline operations. It is important to acknowledge that AI technology is already available and more advanced than ever, making the transition to sustainable manufacturing imperative.
The urgency to transition to sustainable manufacturing is evident as global regulations tighten, and consumers demand transparency for the entire supply chain. Governments worldwide are prioritizing carbon neutrality and manufacturers need to follow suit. Starting and continuing the transition to sustainable manufacturing could be the most important area to prioritize today to not only reduce emissions but also costs.
For a list of the sources used in this article, please contact the editor.
Saar Yoskovitz
Saar Yoskovitz is the Co-Founder and Chief Executive Officer of Augury. Augury machine health solutions eliminate downtime, reduce maintenance costs and maximize productivity for critical machines in industrial and commercial applications. Augury’s solutions combine advanced sensors with powerful AI capabilities and collaboration tools to help teams understand when machines and the processes that depend on them are at risk, coupled with the actionable insights customers need to prevent failures before they threaten production or productivity.