Manufacturing, the industry which makes everything, is itself being remade. As industrial applications of the Internet of Things (IoT) add both continuous connectivity and precise monitoring to more and more machines, data is transforming the way we operate and maintain them. Maintenance is an unsung hero. From printers to power plants, all the amenities of our modern life require machines, and those machines in turn require some TLC.
By 2035, Artificial Intelligence (AI) has the power to increase productivity by 40 percent or more, according to Accenture. For manufacturing companies, integrating AI into legacy information and communications systems will deliver significant cost, time and process-related savings quickly. AI improves the manufacturer's bottom line through intelligent automation, labor and capital augmentation, and innovation diffusion. For example, by analyzing incidents in real time, AI can provide early warning of potential problems and propose alternative solutions. These benefits mean that AI has the potential to boost profitability an average of 38 percent by 2035.
Manufacturing companies face numerous issues that affect yield, particularly problems in the production line. In order to address these problems, production line data must be available, insightful, and relevant for teams on the factory floor. Smart factory solutions offered by Seebo automatically translate data from production processes into intuitive, visual, and actionable insights for quality and maintenance teams, process engineers, and management. In an exclusive chat with Mirror Review, Seebo CEO and Co-Founder LiorAkavia speaks about the Industry 4.0 solutions offered by the company. Lior also explains Seebo's strategy to deliver tools that help manufacturing companies optimize their production processes.
As an upstream oil and gas chief operating officer, you have a huge responsibility for exploration and production (E&P)– e.g., what's your cost per well? And if you get it wrong, you stand to lose a lot of money – and risk your company's future. As a result, you're much more attuned to key performance indicators (KPIs). In fact, you watch them like a mother bird watches its fledglings. And the more you know about those KPIs, the more you obsess about them.
Manufacturers need to reduce the time and effort required to have experts on-site for the maintenance of their equipment. This means finding the right balance for maintenance tasks, which frequently adds unnecessary costs, and increase the risk of failures. Introducing predictive maintenance, based on AI and cellular connectivity can address these issues. Predictive maintenance is all about identifying problems before they occur, and the first step toward implementing it involves introducing sensors on equipment to measure anything measurable. Almost all new state-of-the-art industrial equipment already has embedded sensors.