This article reviews the transformation and application of inspection and measurement (I&M) technology in the manufacturing industry. I&M offers a wealth of information needed in the development of new products. Cummins and Ford are among the pioneers in connecting I&M systems to the rest of their companies’ computerized decision support systems. Both companies are making wider use of I&M information and bringing factory floor and top-level decision-making closer together. Inspection, test, and measurement results are also vital to establishing the performance of the assembly tools and the capabilities of the processes. Lack of good I&M information can help weaken competitiveness and undermine strategies such as design for manufacturing and design for assembly. Timeliness is also crucial. Squirreling I&M data away in engineering silos perpetuates inspection and measurement as the last island of automation, the repository of information learned and lost.

## Article

inspection and measurement technology has transformed manufacturing. Think of the countless qualityassurance successes of Six Sigma, the productivity gains from Lean Manufacturing with its just-intime supply chains and minimal inventories, and kaizen-style continuous improvement.

All would have been difficult or impossible without I&M systems like coordinate measuring machines, which use touch probes to check dimensions and tolerances, and laser and other optical scanning systems that check surfaces for flatness and curvature.

Until recently, however, very few I&M systems were connected to the rest of enterprise. What happened in the factory stayed in the factory. Data stayed in the factory because it was gathered and formatted to meet the needs of each operation, and factories have hundreds of operations.

Each I&M system addresses a particular measurement need of a specific operation. Because each operation had different needs, I&M data from one was not consistent with data from the others.

But I&M data is packed with valuable information that others in the enterprise can use to make better decisions about production operations. I&M can inform managers about conditions and capabilities in the factory daily, by shift, hourly, or even more often.

Equally important, I&M offers a wealth of information needed in the development of new products, which also never ends. Unfortunately, incorporating lessons learned in operations into the requirements for future products is still hit-or-miss for many manufacturers.

This is the big I&M disconnect: Vital I&M information often does not get from production operations to those who need it when they need it.

At Perceptron, the inspection systems and metrology company where I work, we see the unfortunate consequences of this disconnect all the time. Most of our I&M customers have the data but they don’t seem to internalize it. They don’t use data from tooling to search out root causes of production problems. And their product developers don’t apply lessons learned from previous products.

Among the exceptions are Cummins Inc. and Ford Motor Co. Both companies are integrating the information generated by their I&M systems into their mainstream decision support systems.

“Launching” a new product in the factory best illustrates the story. After prototyping and initial customer approvals are out of the way, factory operations crank up. I&M teams in each operation get busy inspecting the first products off the line—a few hundred or a few thousand, depending on volume.

These inspections verify that, as manufactured, the product fulfills all its requirements. These checks also verify that the new operations meet targets for productivity (flow rates and cycle times) and that quality, cost, and safety are not compromised in any way.

I&M data may reveal that overly tight tolerances are requiring more frequent inspection and process adjustment, which can slow production and may lead to high-cost rework. Or perhaps incorrect sequencing in assembly is forcing partial disassembly to install other components. Insufficient clearances in mechanized operations may result in scratches and dents that multiply rework and scrap rates—not to mention upping the risks of machinery crashes.

This is the big I&M disconnect: Vital I&M information often does not get from production operations to those who need it when they need it.

This intelligence in I&M data begs to be applied. For people “downstream” in production, this information can be crucial for troubleshooting. Knowing that data can be trusted, and that its collection is consistent, means less time will be wasted going down blind alleys.

For product developers, I&M information can be vital in avoiding a repeat of design errors.

Cummins and Ford are among the pioneers in connecting I&M systems to the rest of their companies’ computerized decision support systems. Both companies are making wider use of I&M information and bringing factory floor and top-level decision-making closer together. Hundreds of other engineering-intensive manufacturers plan to do likewise. (Perceptron is not directly involved in either the Cummins or the Ford initiative.)

Both Cummins and Ford start with the engineering basics: statistical process control, which extracts value from sets of data, and Six Sigma methods to apply it. Six Sigma and SPC rely on inspection and measurement data to systematically monitor and measure operations.

Tooling and fixtures change constantly, for example, even if basic production systems do not. Operations may be slowed down or speeded up. In automated factories, this process has matured into supervisory control and data acquisition, or SCADA, which keeps each operation within specified production tolerances with adaptive control—automated, machine-to-machine feedback and adjustment. SCADA is inspection and measurement’s big brother.

In addition, manufacturing engineers’ instructions to production workers need regular updates. Small modifications to the product itself may be recommended. And best practices must be kept current.

Both Cummins and Ford start with DMAICR, a widely used engineering methodology for process improvement and troubleshooting. DMAICR is a mnemonic for “define, measure, analyze, improve, control, and replicate,” which is a proven formula for consistency.

## Consistently Tight Tolerances

Based in Columbus, Ind., Cummins makes and markets a range of products, from diesel and natural gas engines to power generation systems. For many years, it has routinely taken I&M and test data and information far beyond everyday re-use in process control and quality assurance. Specifically Cummins uses this data in determining engine service lives and for troubleshooting decades into the future.

“We use that information to verify engine performance in terms of design requirements and customer expectations,” said Robert D. Borchelt, director of manufacturing information technology systems and industrial controls. A Ph.D. in engineering management, he is on the Cummins corporate manufacturing staff.

One Cummins I&M initiative zeroes in on the threaded fasteners used in joining, clamping, and sealing key engine components in final assembly. “We are talking here about the critical bolted joints that hold engines together,” Borchelt said. “We torque each capscrew to a known value of torque in newton-meters or foot-pounds for the designated compression load.”

Three hundred or more connections join engine heads and oilpans to blocks and keep piston connecting rods in place. “Proper insertion of each capscrew is crucial to establish the proper clamping forces for seal integrity,” Borchelt explained.

In statistical process control formats, this information goes directly into the databases of the Cummins Six Sigma quality assurance efforts. “This is the tightest link between the factory floor inspections, tests and measurements, and the manufacturing staff,” he noted. Consistency is reinforced.

Cummins Inc. cumminsengines.com

Founded: 1919

Employees: 46,000

Cummins Inc. designs and manufactures engines and related technologies for transportation, oil and gas production, and power generation. It sells its products in approximately 190 countries and territories. Revenues were $17.3 billion in 2012. Inspection, test, and measurement results are also vital to establishing the performance of the assembly tools and the capabilities of the processes. “To understand a problem you have to have the information to know exactly what happened,” Borchelt noted. “We have trained nearly 14,000 Six Sigma black and green belts who have done around 31,000 projects across the world. We estimate those projects have generated savings on the order of$4 billion a year.”

## Globally Consistent Best Practices

At Ford, the emphasis is on using I&M data to help identify and establish best practices throughout the automaker’s global operations.

According to Jay Zhou, executive technical leader for global quality at Ford headquarters in Dearborn, Mich., the company has four distinct sources, or “domains,” of measurement and feedback— customers, the factory floor, engineering, and suppliers. They are integral parts of Ford’s Quality Operating System.

Embedded in that system is Customer-Driven Six Sigma, Ford’s corporate DMAICR methodology for problem solving and reporting which in turn is part of the Ford Quality Operating System, or QOS.

QOS is being implemented at all of Ford’s 65 major facilities worldwide where it assembles vehicles, engines, and transmissions. Inspections and measurements from plant floors and manufacturing operations are stored and shared among Ford’s plants, Zhou said.

Timeliness is also crucial. Squirreling I&M data away in engineering silos perpetuates inspection and measurement as the last island of automation, the repository of information learned and lost.

Ford insists that feedback be compared across plants, vehicles, and production systems—in a word, that it be consistent. As just one example, the Ford Focus is manufactured at nine plants around the world—in places a different as Germany, Russia, China, and Thailand, and the United States. Ford has cited data from R.L. Polk Co., the auto market research firm, that identifies the Focus as the best-selling vehicle nameplate in the world for 2012, when more than 1 million were sold.

“At Ford’s manufacturing operations, DMAICR specifies gauges to be used, their pressures and settings, and acceptable ranges of read-outs,” Zhou said. QOS makes this possible by spelling out inspections and measurements for each workstation. “There are inspection checkpoints or control points in each department,” he added, “and at every workstation throughout the operations for body assembly, chassis build, interiors or trim installation, and painting, plus power trains and engines.”

Each QOS domain “shares its data with the others,” Zhou said. “This is best managed globally, at the enterprise level, regardless of how enterprise is defined. The standards are clear and concise, but not rigid. We want to make sure we measure the right characteristics of each product or process, and are able to replicate that as best practices at all plants.”

According to Zhou, “We make sure the problems and solutions get into the Ford corporate memory base where standards and best practices live. This is to prevent recurrences and reinforce lessons learned.”

“This has been a huge transformation,” Zhou said. “From a quality and productivity standpoint, the handling of I&M and test data is absolutely the right issue to address.”

## Getting off the Island

Ford Motor Co. corporate.ford.com

Founded: 1903

Employees: 166,000

Ford, one of the traditional Big Three automakers in the United States, sells more than 5 million vehicles a year worldwide. Corporate revenues in 2012 totaled \$134.3 billion. The company has operations on every continent except Antarctica.

Cummins and Ford are working hard to see that I&M is no longer the last island of automation. They are trying to ensure that the capabilities and the challenges of factory floor operations, and I&M in particular, are factored into key decisions promptly and consistently.

As we at Perceptron see it, decision makers still have too little information, not too much, despite all the talk about data tsunamis. The shortages do more than hamper quality assurance and bedevil troubleshooting. Lack of good I&M information can help weaken competitiveness and undermine strategies such as design for manufacturing and design for assembly.

Timeliness is also crucial. Squirreling I&M data away in engineering silos perpetuates inspection and measurement as the last island of automation, the repository of information learned and lost.

Cummins and Ford are bringing consistent I&M data from the factory floor to enterprise-level decision makers. Doing that can itself be a challenge. In the IT world, overcoming I&M disconnects is called governance. Governance committees of experts sort out what information executives need to see, when they need to see it, and in what formats.

Equally important, governance enforces consistency.

It is a cliché to say that businesses “run” on information and that they compete on the basis of the insights gained from that information. But this cliché is true. That’s why information left n an island is about as useful as a ship run aground: It may have done its job, but it won’t take the enterprise anywhere.