Utopias are common in fiction, but for manufacturers a world without unplanned downtime would be the perfect utopia. The question becomes: is abolishing unplanned downtime a far-fetched dream, or is it closer than we think? According to research by Oneserve (Exeter, England), machine downtime is costing British manufacturers over $225.9 billion a year. Unplanned downtime halts production, but it can also lead to wasted raw materials or damage to the system itself, amplifying the cost beyond loss of production. Further research conducted by GE Digital (San Ramon, CA) found that 70 percent of companies lack full awareness of when their equipment is due for maintenance, upgrade or repair. These figures are troubling, because unplanned downtime is having a huge impact on productivity and causing major losses to the economy. Manufacturers must be aware of when maintenance is required in order to lower this figure. Does it have to be this way?
Machines break down – it’s an unfortunate fact of everyday life. However, there are signs of machine failure that can be monitored and managed. For example, vibration analysis or analyzing the speed of machine tools can provide insight into the condition of equipment, indicating that it may be about to break down. Proactively monitoring equipment and scheduling maintenance in advance can drastically reduce the risk of machine breakdown, which is why preventative maintenance is taking manufacturing by storm. What does preventative maintenance mean for downtime? Gone are the days when manufacturers must make a run to failure, calendar or usage-based approaches, all of which involve waiting for a motor to fail or a heat transfer system to leak before taking action. Plant managers can now plan regular inspections, upgrades and troubleshooting on equipment to avoid breakdowns. This is good news, because Industry 4.0 is increasing manufacturers’ capabilities to a stage where maintenance can be data-driven.
Information collected by sensors on the factory floor can be relayed to a plant manager and used to make real-time decisions on servicing and maintenance. The use of a digital twin – a virtual representation of a factory’s operations – combined with machine learning software could allow the system to identify and plan for faults in advance. In the future, this could involve a system self-diagnosing and self-repairing: ordering a replacement part or machine from an automation equipment supplier and planning automated maintenance. Could zero downtime ever be possible? Manufacturers seem to think so: eight in ten companies surveyed by GE Digital thought digital tools could eliminate unplanned downtime and 72 percent of them said that zero unplanned downtime is a high priority. Taking a proactive approach to maintenance is the best way to reduce your shop’s risk of unplanned downtime. As Industry 4.0 develops and more connected sensors, digital twins and machine learning software are developed and implemented, downtime will reduce. We may be a way away from the perfect paradise, but we are certainly on the right track.
Snow Wins Resistance Welding Award
Tom Snow, chairman of T. J. Snow Co. (Chattanooga, TN) was recognized with the Elihu Thomson Resistance Welding Award at Fabtech 2021, held in Chicago in September.
Hexagon to Build Ecosystem to Help Overcome Challenges in Additive Manufacturing
Hexagon’s Manufacturing Intelligence division has announced its plan to build a flexible, open additive manufacturing (AM) ecosystem to help overcome complexities in 3D-printing processes and to support customers in building their product development and manufacturing workflows.
GE Additive and Wichita State Team Up to Help Adoption of Metal Additive Manufacturing by DoD
GE Additive and Wichita State University’s National Institute for Aviation Research have signed a non-binding memorandum of understanding as the cornerstone of a new, collaborative effort aimed at supporting the U.S. Department of Defense‘s accelerated adoption of metal additive manufacturing technology.