The Standards Of Digital Transformation – KPIs Of Digital Manufacturing
Digital Transformation (DT) has been breaking the limits of what we have known as long-standing manufacturing standards. Change of this magnitude requires a fitting set of criteria that accurately defines the meaning of success. This article features some of the top key performance indicators (KPIs) of digital manufacturing.
Operational Availability
One of the fundamental indicators of manufacturing performance is whether a facility operates according to its intended capacity. Operational availability refers to the duration that a system is available for productive work and is not experiencing unexpected downtime. A digitally-capable facility aims to improve availability. And while it seems intuitive for mature companies, it can pose a challenge for transitioning processes.
For example, it is easy to imagine that a fully robotic production line can work tirelessly for hours on end. However, if these high-tech machines are new additions to a facility, there could be a demanding learning curve before perfecting the maintenance practices. An experienced maintenance team that can service a conventional piece of equipment in a couple of hours will not necessarily fix new specialized equipment as quickly. Repair time and familiarity with the required tasks both factor into overall operational availability.
A stable, well-planned process fits into predictable outcomes and consistent availability more easily. Improving operational availability alongside DT suggests achieving the benefits of new technology instead of new tools becoming a hindrance.
Reactive Maintenance Percentage
While it is fundamental to know the capacity of a facility to perform work, there could be many possible actionable areas. Measuring the amount of reactive maintenance is a more specific metric that can open up improvement opportunities to increase uptime.Â
A National Institute of Standards and Technology (NIST) report showed that the top 25% of establishments relying on reactive maintenance were associated with more than three times more downtime than the bottom 25%. Aiming to reduce the amount of reactive maintenance paves the way for cost savings in the long run by reducing nonproductive time.Â
A reduction in reactive maintenance work may indicate that new tools are working, especially if coupled with a decrease in equipment breakdowns.Â
Overall Cycle Time
Some of the most sought-after technologies in digital manufacturing involve automation and autonomous systems. Seeing a decreasing cycle time for each unit produced is a perceptible and measurable metric that demonstrates productivity.
The reduction in overall cycle time can originate from several applications of digital technology. For instance, using automated machines in production can speed up manufacturing processes such as welding, assembly, and painting. Another application of automation is in incorporating robotic systems into quality inspection procedures. In both scenarios, reducing manual work can result in significant cycle time efficiencies. Â
Operational Improvement
DT typically involves a collective of initiatives rather than a single, isolated project. When thinking about performance indicators, it makes sense to consider the total impact of digitalized processes.Â
Operational improvement evaluates the combined list of processes transitioning digitally and their aggregate impact on productivity. It gives the company insights into the success of the assumed technologies. Moreover, this KPI can provide information about areas that require additional training, underutilized systems, or a possible elimination of redundant steps.
Throughput
The production capacity of a facility remains to be a primary concern for manufacturing companies. Having an initial idea of overall availability and cycle time should equip manufacturers with the information to face continuous demand. Tracking throughput on top of these metrics describes the state of production capability in line with ongoing DT initiatives.
Analysis of throughput data together with cycle time and availability can help a company learn about the drivers of improvements. Conversely, it can also highlight pain points and bottlenecks in the manufacturing process. The desired trends for throughput include increases, accompanied by reduced cycle time, and maintained or improved availability.Â
Quality
Equally important as increasing productivity is ensuring that products attain a high level of quality. Quality, or the rate of quality products, describes how well a manufacturer eliminates defects in the final product.Â
We previously mentioned that robotics is a proven way to reduce cycle times. An additional benefit is that precise controls and measurements also become achievable. For instance, optical measuring machines enable facilities to make more reliable process controls. Such tasks were previously dependent on manual devices like calipers and micrometers. The result is an increase in the accuracy of creating quality products in a fraction of the time.
Overall Equipment Effectiveness (OEE)
As the name suggests, Overall Equipment Effectiveness factors in multiple performance indicators, providing a more holistic view of effectiveness. The components of OEE include equipment availability, performance efficiency, and product quality.
Monitoring a multi-dimensional metric such as OEE provides a more expansive view for the company. Modern software takes the metric a step further by including root cause analysis procedures and recommendations for solutions. Achieving perfect OEE, in simple terms, means that the facility is creating high-quality products in the most efficient way possible.
Return on Investment
Out of 125 manufacturing leaders surveyed, more than half identified a positive ROI as the measure of a successful DT program. On top of all the technological technicalities involved in DT, it all boils down to how the initiative resonates with the broader business objective.
While ROI seems like a straightforward KPI, it requires proper attention in scoping terms and definitions. For instance, it should consider milestones within the project duration that would require significant resource outflow, and set the right expectations with management. Similarly, projections of value payback should be practical and evidence-based. The calculation of ROI figures also needs to align reasonably with market fluctuations and industry contingencies.
A healthy ROI of a digitally-focused initiative speaks volumes about the business case for undertaking the project. However, keep in mind that it is also valuable to consider the ROI of all DT initiatives as a whole. Think of a DT program as an overall strategy that uses the collective power of technology rather than collecting multiple tools working independently.
Conclusion
The availability of technology and the shift to digitalized processes have paved the way for a traditional facility to become a smart factory. As these new tools improve production capabilities, what we know as KPIs need to adapt accordingly. After all, if you are relying on performance indicators to tell you a story about your plant, you want that story to be as accurate as possible.
Author: Eric Whitley
Eric Whitley has 30 years of experience in manufacturing, holding positions such as Total Productive Maintenance Champion for Autoliv ASP, an automotive safety system supplier that specializes in airbags and restraint systems. He is also an expert in lean and smart manufacturing practices and technologies. Over the years, Eric has worked with all sectors of industry including Food, Timber, Construction, Chemical and Automotive to name a few. Currently, he’s a part of the L2L team.
