January 15, 2016 / benchmarking, best practices, blade failure, bottlenecks, continuous improvement, LIT, predictive management, preventative maintenance, productivity, strategic planning
The U.S. manufacturing landscape is changing, and industrial metal-cutting companies are no exception. Technology has created an increasingly connected industry, and manufacturers are realizing that while traditional lean practices have proved successful in the past, when it comes to operational efficiency, data and other advanced “smart” technologies are the wave of the future.
One area that is quickly gaining popularity is the use of predictive technologies. As reported in a recent Manufacturing.net article, nearly three dozen manufacturing company executives and national research facility directors identified predictive data analytics as the number one advanced manufacturing technology critical to growth, as part of a study conducted by Deloitte Global and the U.S. Council on Competitiveness.
Predictive analytics utilizes a variety of statistical and analytical techniques to develop mathematical models that “predict” future events or behaviors based on past data. As the study explains, this allows companies to uncover hidden patterns, relationships, and greater insights by analyzing both structured and unstructured data.
Several industries are already benefiting from the use of predictive technologies. Healthcare, for example, is using predictive analytics to improve the effectiveness of new procedures, medical tests, and medications. Manufacturing companies are using the technology to identify quality and production issues, as well as optimize delivery and distribution. Other industries, such as aerospace, automotive, and consumer products, are also finding interesting applications.
Thyssen Krupp, for example, recently used predictive analysis to improve the reliability of more than 1.1. million elevators it maintains worldwide. With the help of Microsoft cloud technology, the company gathered data from thousands of sensors and systems in its elevators to measure motor temperature, shaft alignment, cab speed and door functioning. After being sent to the cloud, the data is then displayed on a single dashboard in real-time. The data is also used in predictive model formulas, helping technicians know when and where a failure may occur.
The trend is also finding its way into industrial metal cutting. Data from the LENOX Institute of Technology’s Benchmark Survey of Industrial Metal-Cutting Organizations suggests that investing in smarter, more predictive operations strategies can help companies gain additional productivity and efficiency on the shop floor.
Although not through the use of analytics, the benchmark survey found that industry leaders are using strategies such as planned maintenance and blade care to prevent downtime and predict blade failure. Specifically, the benchmark study found that:
- 67% of industrial metal cutting operations that follow all scheduled and planned maintenance on their machines also report that their job completion rate is trending upward year over year—a meaningful correlation. The implication is that less disruptive, unplanned downtime and more anticipated, planned downtime translates into more jobs being completed on time.
- 51% of organizations that “always” follow scheduled and preventative maintenance plans say that blade failure is predicted “always” or “mostly.”
While there is no question that predictive analytics is still an emerging area, it is clear that proactive strategies are key in today’s uncertain market. Whether you invest in advanced predictive analytics software or simply stick to your preventative maintenance program, finding ways to anticipate future events and reduce unplanned downtime can help your operation gain efficiency and, more importantly, stay competitive.
What predictive operational strategies are you using to make your operation more efficient?