Apr 11, 2018

By Silke Schmidt, University of Wisconsin-Madison, Phys.org “Although smartphones and tablets are ubiquitous, many of the companies that make our everyday consumer products still rely on paper trails and manually updated spreadsheets to keep track of their production processes and delivery schedules,” says Leyuan Shi, a professor of industrial and systems engineering at the University of Wisconsin-Madison. That’s what she hopes to change with a research idea she first published almost two decades ago. During the past 16 years, Shi has visited more than 400 manufacturing companies in the United States, China, Europe, and Japan to personally observe their production processes. “And I have used that insight to develop tools that can make these processes run much more smoothly,” she says. These tools are based on the notion of a “digital twin,” or a computer representation of physical assets (machines and people) and processes that helps managers better operate the systems that connect them. Take, for example, a car manufacturing company with 15 different suppliers, each of which delivers a specific car part. As these parts arrive at the company, they are assembled by people who work in different departments, such as sheet metal cutting, heat treatment, welding, painting and so forth. The overall goal of this manufacturing system is to fill a set number of vehicle sales orders. That’s a classic example of a supply chain: a set of processes that link raw source materials to final consumer products. A company’s goal for making supply chain manufacturing more efficient might include decreasing production downtime due to delivery delays for required parts, and better adjusting to unpredictable events, such as rush orders, machine breakdowns, or defective parts. The technology Shi has developed helps managers meet these goals. With a database system, user software and equipment sensors, it creates a digital twin of what is physically happening at the supply facilities and shop floors. Managers can use that digital representation to visually track the global production progress in real time and adjust workflows as needed. The tool provides continuously updated start times for each assembly stage and constantly refined delivery times for the customers who ordered the cars. “That’s what we mean by smart manufacturing,” Shi says. The technology...

Jul 5, 2017

By Jeff Kavanaugh, Manufacturing Business Technology Every day, we hear of new examples of artificial intelligence (AI) being used to support, or supplant, the human workforce. Many of these discussions revolve around consumer-facing situations. However, the AI wave could have an even larger impact on the manufacturing sector, with its complex processes and machine-to-machine interactions spanning products and assets, within factories and across global supply networks. This was highlighted in a recent study that investigated the approach of senior decision-makers in large organizations toward AI and its future applications. Consider the digitization of factories. Flush with data from a sensor-enabled landscape, they’ve had a chance to join the ranks of the information intelligentsia and effectively drive rich floor output. Unfortunately, some in the manufacturing sector have ignored or even denied the disruptive impact of digital technologies. It took leaders like GE to envision how the Industrial Internet could become real for manufacturers.  Smart Manufacturers are Automating Data According to Oxford Economics, the Industrial Internet, with its connected sensors, represents more than 60 percent of the gross domestic product for the top 20 national economies. So for those using data automation to make more informed decisions, the opportunity — and also competition — is exploding with the emerging Industrial Internet binding products, equipment, and systems in a web of communication. Eventually, Industrial IoT will permeate global supply chains, allowing manufacturers to accelerate product launch, coordinate demand-supply planning, and optimize production, in ways not possible without such advanced collaboration. Currently, the Industrial Internet is still in early development, but early adopters are seeing anecdotal successes as proof of concept projects continue to mount.  Smart Manufacturers Can Automate Processes, too The recent Infosys study, Ampliyfing Human Potential: Towards Purposeful Artificial Intelligence, surveyed 1,600 IT and business decision-makers from organizations of more than 1,000 employees with $500M or more annual revenue and from a range of sectors. The research was carried out in the U.S. and six other manufacturing and industrial nations. It found companies planning to or currently using AI technology, such as robotics, anticipate a nearly 40 percent boost to their organization’s revenue by 2020. The economics of investing in robotic efficiencies is not lost on manufacturers. An example is...

Dec 19, 2016

By Steven Blue, President & CEO of Miller Ingenuity Featured on IEN Don’t bother with smart manufacturing if you have a dumb workforce. And if your workforce is dumb, it’s your fault, not theirs. Someone asked me recently my thoughts on Smart Manufacturing. The so-called IT revolution in the factory. They couldn’t believe that I didn’t see Smart Manufacturing as the salvation of American manufacturing. Don’t misunderstand me. Smart Manufacturing has a place in reviving American manufacturing. I have a smart factory. We employ the latest in pick to light systems, automated CNC machines and seamless integration from order inquiry to accounts receivable. But that isn’t where I started my revolution. And you shouldn’t either. The problem with many CEO’s today is they have turned away from the astonishing potential of the workforce and turned toward automation instead. Big mistake. But I hear it all the time. What is the sense in spending millions on automating your factory if our workforce could care less? What is the sense in buying expensive machine tools if your workforce can’t wait to get to the bowling alley, yet drag themselves to work? I’ll tell you why. Because too many CEO’s view their employees as expendable assets. They should view them as renewable resources. And renew them. Don’t bother with smart manufacturing if you have a dumb workforce. And if your workforce is dumb, it’s your fault, not theirs. Don’t bother with an IT revolution. Your revolution has to start with a “Smart Workforce”. You have to make a new compact with your employees. You need to ignite the human spirit in your workforce. Imagine this. What would happen if every day your employees came to work excited to do better today than they did yesterday? Imagine how your company would soar if your employees were absolutely dedicated to supporting the mission and each other in attaining it? Imagine what it would be like if your employees were like Cirque de Soleil performers? This is the place where I get blank stares from many CEO’s. They don’t like the “soft stuff.” “Give me the hard stuff,” they say. “Tell me how to build a smart factory, not a...

Nov 15, 2016

By Christopher Mims, Wall Street Journal The aim is to make factories more productive, less costly to operate and more reliable Here’s a paradox of America’s highly automated, increasingly labor-independent manufacturing: While sophisticated, for the most part, it isn’t all that high-tech. Picture metal-stamping machines in an auto-parts factory that can easily have a long useful life of up to 40 years. Now picture the assembly line just outside Austin, Texas, where Samsung Electronics Co. makes core chips for Apple Inc.’s iPhones. I toured the facility last summer. It is a pristine white environment filled with WALL-E-like robots ferrying boxes full of silicon wafers from one station to the next. Every detail of the factory is measured by sensors pouring data into a centralized repository where it can be processed to optimize production. The only humans present are there to fix the machines doing all the work. But that means there is still a big opportunity to use in manufacturing all the learning Silicon Valley has applied to, for example, advertising. “People are really thinking about applying venture capital and technology innovation to things that are 10 times the size of the ad market,” says Jon Sobel, chief executive of Sight Machine Inc., which helps companies process all the data coming off their assembly lines. Manufacturing is a $12 trillion industryglobally a year. Annual spending on ads globally is just north of a half a trillion dollars. This transformation in the way we make things has many names—the fourth industrial revolution, the industrial Internet of Things, smart factories—but at base it is about harvesting as much data as possible from all the machines in factories, shipping it to the cloud, parsing it with artificial intelligence, and using the results to make those factories more productive, less costly to operate, and more reliable. The goal is to break data out of its silos—the machine, the factory floor, the shipping and logistics system—and pool it in a way allows for real-time decision-making. Here are examples of what this “revolution” can accomplish: deciphering how ambient air temperature affects productivity of an entire factory. Or ramping up and down production in a way that is more responsive to...

Nov 9, 2016

“Pratt & Whitney Searching for Products, Services to Ramp Up Monthly Engine Production” By Brett Brune, Editor, Smart Manufacturing Manufacturing Engineering CHICAGO—Pratt & Whitney is aggressively searching for smart manufacturing solutions that will allow it to successfully ramp up monthly production of engines for military and commercial aerospace engines, Kimberley Hagerty, Hot Section Module Center lean transformation manager, said yesterday at the 2nd Smart Factory World Symposium. In 2010 P&W delivered about 55 engines a month. In 2017, that number grows to about 100 engines a month. And in 2024, it continues to climb to about 158 engine deliveries a month, she said.  “And I’m doing that with 20-year-old technology and 20-year-old manufacturing processes and a very well-seasoned workforce” that adds significant complexity to the digital manufacturing transformation of the East Hartford, CT-based firm, Hagerty  said during a panel talk on best practices.  “So the challenges ahead of me are steep.” In an interview with Smart Manufacturing magazine after the panel discussion, Hagerty said she is “fresh into the exploratory phase” to find products and services her firm needs. She has mapped out her requirements. “Now, I’m reaching out to the service providers” and scheduling visits to firms using products and services that might well work for Pratt & Whitney. She joined the firm five years ago, after retiring from the US Air Force as the chief of strategic planning and analysis. The only tech move she’s made so far for her division at Pratt & Whitney is to enroll in the Forcam Academy, for shop-floor management. Forcam software was already deployed at a P&W Facility in Middletown, CT, and GKN, one of Pratt & Whitney’s suppliers. “Forcam is one of the resources I reached out to as far as a serviced provider, because they provide a service I need from a machine health monitoring and data analytics standpoint.” Hagerty told the crowd at yesterday’s smart manufacturing conference, which Forcam organized, that she commonly uses over 1,000 machines in four different states to build one customer’s engine. “I’ll start production in Connecticut, do an interim shipment to another facility, do another manufacturing step there and send it to another facility in another state and do another...