IIoT and cloud for SMEs

IIoT and cloud for SMEs: Four key considerations
By Dwayne Divers February 29, 2016

Dwayne Divers is director of manufacturing strategy for Dude Solutions. Courtesy: Dude SolutionsManaging equipment uptime and reliability in the manufacturing environment is no easy task. Maintenance and operations teams everywhere are challenged with aggressive production schedules, limited maintenance budgets, and scarce resources. This is especially true for small and medium-sized enterprise (SME) manufacturers that may not have the same scale or budget as today’s largest manufacturers.

For independent manufacturers with homegrown or client-server-based solutions, there are a number of reasons to consider the benefits of the cloud and the Industrial Internet of Things (IIoT). The biggest rewards of adopting a cloud-based or IIoT-leveraged model include proactive asset management and higher overall equipment effectiveness (OEE).

But implementation alone isn’t enough. To maximize output and minimize cost for higher reliability on the plant floor, here are four considerations for making the cloud and IIoT work on your plant floor.

1. Adopt run time or cycle-count preventive maintenance (PM): While the automation available with the IIoT and cloud-based solutions can help you implement your PM strategy, calendar-based PM routines (which are the easiest to implement) may not be the most efficient. It can be more cost-effective to schedule preventive-maintenance activities by cycle counts or run time when equipment has a variable utilization schedule.

This is especially true if the PM activity is restorative, such as replacing or reconditioning components to run more effectively with high reliability. Counting the repetitive process cycles or run time—the number of starts on a motor, the number of hours it is running, or the gallons of liquid a pump is pumping—is more efficient than scheduling by the calendar.

Cloud-enabled solutions can automatically feed the run time or cycle-count data to the computerized maintenance management system (CMMS). This also provides visibility into whether there is too much preventive maintenance and where there are cost-savings opportunities with a more trimmed program.

2. Track key operating parameters: Measuring important operating parameters through automated software is essential as it enables effective PM programs to turn into predictive-maintenance programs. By tracking operating parameters such as temperatures, pressures, and quality—all of which represent equipment health—trends can be identified and can even indicate potential equipment failures. Rather than communicate to the asset-management system manually, ensure the software automates data collection and issues corrective work orders so technicians can adequately investigate trends that may indicate a potential failure.

3. Use standard failure codes: Similar to tracking key operating parameters, using standard failure codes to communicate issues to the technician before he or she goes onsite can increase efficiency and troubleshooting. Production automation software that collects information about the problem and assigns standard failure codes can automatically create corrective work orders for emergency breakdown work. While even the IIoT and cloud can’t 100% prevent emergency breakdowns, automation and integration will support more efficient work order generation and identify operating measures that can result in a more productive predictive-maintenance asset strategy.

4. Use data to improve operations: Once automated, create a process to use the data. With the aforementioned considerations in place, equipment data should indicate warnings before equipment failures so you can catch things before they break down. The data also can be used to analyze where there are opportunities to improve operations by:

  •  Minimizing the need to remove equipment from service for restoration
  •  Providing the ability to focus on the most-common failures that were identified and coded through the automation.

This is a key benefit. More automation and integration will produce better data and better analysis and should be a key focus area in plant operations.

For example, in a part-casting operation, the number of parts produced is tracked in the production automation software. As the parts are made, the casting form begins to deteriorate and become contaminated. A PM schedule is developed to refurbish the casting form and is best implemented based on the optimum number of parts made before the quality of the part is affected.

Rather than having a technician manually track and enter the number of parts made, IIoT and the cloud enable the production automation software to communicate the cycle counts to the CMMS, which generates the PM work order at the precise time. For plant engineers and maintenance managers, this results in not only reduced labor costs, but also higher OEE, increased uptime, and greater reliability.

Dwayne Divers is director of manufacturing strategy for Dude Solutions.