May 1, 2016 / best practices, customer satisfaction metrics, industry news, KPIs, lean manufacturing, LIT, operations metrics, performance metrics, productivity, quality, strategic planning
As companies look for new ways to stay competitive, more and more manufacturers are utilizing “big data” and analytics in their operations. In fact, according to the results of a survey from Deloitte and the Council on Competitiveness, these types of advanced technologies have the power to put the U.S. back on the map as the most competitive manufacturing nation.
“CEOs say advanced manufacturing technologies are key to unlocking future competitiveness,” the report summary states. “As the digital and physical worlds converge within manufacturing, executives indicate the path to manufacturing competitiveness is through advanced technologies, ranking predictive analytics, Internet-of-Things (IoT), both smart products and smart factories via Industry 4.0, as well as advanced materials as critical to future competitiveness.”
Specifically, the report states that the application of these more advanced and sophisticated product and process technologies will help the U.S. and other traditional manufacturing powerhouses of the 20th century (i.e. Germany, Japan, and the United Kingdom) reclaim their spots as the most competitive nations in 2016. The U.S. in particular is expected to take the number one spot away from China by the end of the decade.
What does this mean for industrial metal-cutting organizations? It means that if you haven’t already considered using data and software analytics in your facility, it may be time to revisit the idea. If data-driven manufacturing has the ability to make nations more competitive, that certainly says something about what it can do for individual companies.
Metrics that Matter
For many industrial manufacturers, the thought of using data may seem a bit daunting; however, it doesn’t have to be as complicated as it sounds. For example, a metal service center featured here in a white paper started by developing an internal software system that automatically tracks the number of square inches processed by its existing sawing equipment. At any point, the manager can go to a computer screen, click on a particular band saw or circular saw, and see how many square inches each saw is currently processing and has processed in the past. Gathering this type of data allows the service center to easily track trends and quickly detect problem areas.
Richards Industries, a Cincinnati, OH, company that manufactures industrial valves, is using data in a similar way, according to a recent article from Modern Machine Shop. Although the company has been practicing lean manufacturing for years, it recently installed a machine-monitoring system that enables shop floor personnel to track activities and record the performance of its machine tools. “Like readings from a Fitbit or Jawbone, the data gathered and analyzed by this system is making the company more aware of how well machine time and manpower count toward productivity,” Modern Machine Shop reports.
Of course, these are just two examples. There are many other ways manufacturers can utilize data and advanced analytics to improve their operations. An article from IndustryWeek calls out a few key metrics industrial metal-cutting companies should consider as they implement data and analytics tools into their factory:
- Line speed by product. Take note of when and how often your line manufactures certain types of products; and then use tools to track the time and effort required to generate meaningful output for each. That way, you’ll have a better handle on what mix would produce the greatest profit.
- Granular utilization data. Look at the specific days and hours your factory produces its greatest output, as well as at what mix and with which operators on the floor. In other words, study the conditions that lead to the very best outcomes and then seek to reproduce those outcomes on a regular basis.
- Error rates correlated by product and employee. Avoiding mistakes is every bit as important as optimizing your mix and hours on the floor. Use Big Data and analytics tools to study error rates and then correlate the results by product and employee.
- Assembly speed by product and employee. Careful and error-free production is important, but so is speed, especially for facilities that deal with high volume. By using data and analytics tools to segment production, you can get a clearer understanding of what products are easier to produce and then ask your floor leaders why.
Whether you decide use data to gain productivity, monitor machines, or improve quality, the point is that data-driven manufacturing is here, and companies big and small are taking advantage of its many benefits. If you haven’t jumped on the bandwagon yet, don’t get overwhelmed. Just get started.
How are you utilizing data to improve your operations and stay competitive?