Digital Transformation: How Machine Monitoring Can Drive Continuous Improvement

By Liz Stevens, contributing writer, The American Mold Builder

Don Dumoulin, the CEO and owner of Precise Tooling Solutions, Columbus, Indiana, knows that plastic tooling manufacturing is a challenging business, even in the best of times. With COVID-19 affecting supply chains and deliveries, and Chinese businesses competing for market share, Dumoulin believes that now is an excellent time for moldmakers to expand their resourcefulness, boost their productivity and increase their bottom lines. He admits, however, that achieving this is not a slam-dunk.

“We have somewhat limited resources as toolmakers,” he said. “We only have so much capital we can deploy every year. We only have so much time that we can put against projects that will change our dimensions, if you will. And we only have so many things that we can do in a given year to really drive improvement.”

Dumoulin believes that gaining a better understanding of a plant’s machines and how operators run those machines can give manufacturers valuable insight that can lead to profit-yielding changes. For him, advancing beyond the use of paper scorecards to record machine downtime is a key to gaining greater understanding, and machine monitoring is an ideal next step. After all, he notes, “the machine monitoring industry will tell you that the average machine utilization in our shops is 26%.” This equates to a loss of about $1.5M per manufacturer for downtime.

Finding ways to reduce or eliminate machine time loss, and thereby increase the productivity of both machines and operators, is critical to profitability. And while reducing repair time and set-up time is an obvious way to improve operations, in Dumoulin’s experience, “continuous improvement also can happen with reducing the time needed to track down cutting tools, with improving steel availability, with making sure that programs are available for machinists.”

During the AMBA Continuous Improvement virtual conference, held November 4 and 5, 2020, Dumoulin and co-presenter Akshat Thirani, the co-founder and CEO at Chicago-based technology company Amper, outlined Precise Tooling Solutions’ journey to find and implement a machine monitoring solution.

The Search for a Machine Monitoring System

“I have long believed that machine monitoring was part of the solution,” said Dumoulin, “but I really struggled to find a positive return on investment.” He found that sophisticated machine monitoring systems can come with a $30,000 or $50,000 price tag for software, plus an additional $10,000-15,000 to get all of a plant’s machines retrofitted for monitoring.

So, when Dumoulin sat down with his team to prepare for another round of searching for a machine monitoring system, he and the team boiled down their wants and needs to a succinct shopping list. “We wanted leading indicators versus lagging indicators,” he began. “We wanted a culture of lean and accountability. We wanted to make sure that our technology was data-focused and staying ahead of the curve. And we wanted to make sure that we also were looking at the opportunity cost to collect that data.”

Since machine monitoring includes integration with existing equipment – be it brand-new equipment or 20-year old machines – any plant considering the addition of machine monitoring should consider the cost of outfitting older machines with updated technology to allow for the most advanced monitoring systems. If the cost is prohibitive, Dumoulin suggests considering a more modest approach. “Maybe you don’t jump right to full-blown machine monitoring,” he said, “but you work instead on getting some of the machine monitoring aspects in place first. If you can’t afford those kinds of upgrades, but you at least need something that gets you going down the data path, a simpler version of machine monitoring might be a good choice.”

Finding the Right Fit for Precise Tooling Solutions

Don Dumoulin and his company refined their search criteria to five key points to evaluate in a machine monitoring system: the true cost of the implementation, the implementation requirements (for upgrades and additions), the ease of use of the system, the simplicity and flexibility of the system’s reporting options, and the ability to get the company team engaged in using the new system.

Dumoulin moved forward with Amper’s offering for machine monitoring. “Of the three systems we looked at, the Amper solution was the best across the board,” he said. “Some of the vendors had a very high true cost; they were very expensive to purchase and complex to install, and driving our existing machines was really hard to do.” 

Dumoulin had long been convinced of the benefits of software as a service (SaaS), another attractive feature of the system his company chose. “The great part about a SaaS model is you don’t have any capital cost,” said Dumoulin. “You literally hit the return on investment running as opposed to the average $35,000 or $50,000 in a purchase fee model, which immediately puts you in the hole.”

The solution Dumoulin implemented with Thirani required no machine upgrades. “We know that PLC boards are very different,” said Dumoulin. “We asked ourselves, do we have the time to figure out each one and the cost necessary to modify it, and how you code those things? One of our potential vendors wanted to send somebody to our shop at $1,500 a day for three weeks to reprogram all of our machines. I just wasn’t sure I wanted to let them into the code of my machines.” Amper’s design eliminates this requirement.

The reporting features of a machine monitoring system needed to be robust, easy to use and flexible to meet Dumoulin’s criteria. The chosen system included emailed alerts when a machine went down, a variety of sample reports to choose from, and the ability to use unassigned data fields that allow plants to create custom reports with specific data (such as KPIs). “Also,” said Dumoulin, “we can look at longitudinal data over a month or a year and ask ourselves, ‘What is the biggest continuous improvement opportunity that we see that would make us more productive for machine timing?’”

In November, when Dumoulin presented this AMBA workshop, his plant had been using Amper for about three months. Although there was some initial pushback from machinists, they embraced the system once Dumoulin assured them that the system was a machine-monitoring system rather than a machinist-monitoring system. “This is not about the failings of you as a machinist,” Dumoulin had told his machinists, “This is about what we can do to help you to be more productive.”

How Machine Monitoring Can Inform Continuous Improvement

Akshat Thirani described his company’s general approach as a quest to improve quality, cost and delivery by helping businesses use overall equipment effectiveness (OEE) as the leading indicator for their operation. “Everyone generally tracks QCD (quality, cost, delivery) and profit and loss (P&L) at the end of the month and the quarter,” he said, “and the purpose of our OEE-type tool is to provide the leading indicators so that business owners can make an impact at the end of the day.”

“Amper is the simplest machine monitoring tool out there,” Thirani said. “It is a noninvasive sensor that measures the electrical signals of a machine.” The electrical energy used by a spindle varies, and a sensor tracks the electrical usage, recording whether a machine is off, idling or running at top capacity. Sensor installation takes only 10 to 15 minutes per machine. “You basically clip the sensor,” said Thirani, “hook up the internet-connected gateway, and then you are ready to look at real-time analytics via a computer or smartphone.” Installation of a sensor does not require integration with the PLC or control panel.

As Thirani puts it, “Data in itself has no value if no one is using it,” and the data from these sensors has value at a variety of decision-making loops in plant operations. “The first loop,” said Thirani, “can revolve around daily improvement so, for example, the operator and supervisor level can have access to real-time alerts showing when a machine has had too much downtime or indicating that an operator is spending excess time on set-ups.” The data then can roll up into a second loop – weekly reviews from a plant management standpoint – guiding the focus of engineering projects.

“The third loop,” Thirani said, “can be about taking a broad perspective regarding capacity management over an entire year: Does a company really need to buy a new machine? Are machines already utilized to the point that justifies bringing on more people or new machines? How can cost of capacity be adjusted to bring on new sales?”

Don Dumoulin summed up his biggest takeaway from installing a machine monitoring tool. “You learn what your productivity really is, and that’s a little shocking. Once you get the bad news, you then start to see what the reason codes are – why you are getting those kind of results – and you can fix those issues. To me, that is the essence of continuous improvement.”