The Benefits of Connecting Data from Legacy Equipment
Manufacturers can automatically gather and integrate the data from all their production equipment, including legacy assets. Forbes reflects oh how such data can be used to solve existing problems, thus driving significant value in the process.
With all the discussion about digital manufacturing and its associated, sci-fi-sounding new technologies, one critical piece of information hasn’t received enough attention. That is, manufacturers already own the most valuable component required to power their move to the so-called cyber-physical future. It’s the factory data that is generated by what’s sometimes derisively dubbed “legacy equipment.” Manufacturers should think of this resource as their most vital asset because it’s the intellectual property that informs how they make and deliver their products and services.
Importantly, tapping that data isn’t only about transforming into a digital manufacturer; it’s also about manufacturer’s solving their biggest problems. Today’s factories are highly complex, with many data sources, multiple vendors and poor interoperability between equipment and machines. A production line typically has five to 15 machines, all from different vendors and with different protocols. This complexity leads to many problems, including out-of-date operational visibility, reactive maintenance, unplanned downtime, lack of flexibility and long time-to-value.
Add to that the challenges of meeting ever-more demanding customer requirements. Companies higher in the value chain expect more data, such as traceability data, which their customers expect. Also, product complexity is increasing, as is the demand for mass customization, with its requirement to produce small batches of an ever-increasing variety of products.
As if those problems weren’t enough, manufacturers also are struggling to find skilled workers even as their existing workforce prepares to retire. If they don’t capture the retiree’s hard-earned, high-value domain knowledge, manufacturers risk losing it.
The biggest challenge, however, is that legacy systems were not constructed to analyze data; they were built to perform their specific function. As a result, manufacturers have engineers spending 30 to 70 percent of their time looking for information – gathering it from the different systems or manually copying and compiling it in a spreadsheet. With high-value engineers completing low-value tasks, problem-solving takes a back seat, and companies are stuck fire-fighting instead.
Why Tap Legacy Data Now?
Gaining access and leveraging the data currently locked within legacy equipment will help manufacturers solve these problems. Until recently, data from production lines and processes was too difficult, time-consuming and costly to extract and use. The data has been available in the factory equipment and systems, but not accessible or not accessible fast enough.
Now, technology is available to automate the collection, connection and analysis of data from legacy equipment, including PLCs and sensors and process monitoring, production and business planning systems. Even better, the technology can be obtained as a managed service, so manufacturers don’t need extra IT overhead or an army of consultants.
Examples of benefits that companies have gained through digital manufacturing, including digitizing existing assets, according to McKinsey, include the following:
- 3-5% increase in productivity
- 30-50% reduction of total machine downtime
- 20-50% reduction in the cost of inventory holding
- 10-20% reduction in the cost of quality
- 85+% increase in forecasting accuracy
- 5-20% reduction in time-to-market
- 10-40% reduction of maintenance costs
At a fundamental level, access to data from legacy equipment enables manufacturers to solve more existing problems faster. More importantly, it also allows them to solve problems that they’d otherwise not be able to, which can drive more efficiency into the business.
Keep it Simple: Solve a Problem
The good news is that, though new technology is required to take advantage of legacy data, manufacturers don’t need to worry about artificial intelligence and machine learning. Instead, they should think about how to automatically gather and analyze production data to help quickly solve existing problems. Most manufacturers can address many issues using simple analytics, data transparency, data-driven reports and alerting systems.
With a focus on the basics, the low-hanging fruit of leveraging data from existing assets and other investments to solve more problems faster, a mid-size manufacturer can make significant improvements. For example, in about six months, that manufacturer could improve first-pass yield by 25% (reducing the scrap rate from 10 percent to 7.5%) and reap the following financial benefits:
- $16,300 decrease in material cost
- $771,500 drop in machine run time cost
- $931,800 reduction in total existing sales cost
- $194,600 increase in annual production capability
- $382,100 increase in the margin on incremental sales
- $1.3 million in total annualized return opportunity
The First Step to Intelligent Manufacturing
Ultimately, the goal isn’t to “go digital;” it’s to solve problems faster so that you increase your business’ value. By first automatically gathering and integrating the data from all your production equipment – including legacy assets – and then using that data to solve existing problems, you can quickly drive significant value. More importantly, this approach allows you to book the value while you build the datasets that are needed to capitalize on more advanced digital strategies, such as predictive analytics.
Research services provided by Patricia Panchak.