Made with FlowPaper - Flipbook Maker
< PreviousSET POINT A lot of news was made at K 2022 in October. One notable announcement involved the official delivery by Gerd Liebig, CEO of Sumitomo Demag (SHI), of an IntElect all-electric injection machine to long-time customer TE Connectivity, for use at its Esztergom, Hungary, production site. What set this delivery apart from others, is that this was the 80,000th IntElect machine that SHI has sold since 1986, when the line was introduced. That’s a lot of machines. The milestone unit was built at SHI’s plant in Wiehe, Thuringia, Germany, where SHI has exclusively manufactured the IntElect series for the past six years following a production changeover. SHI has supplied TE Connectivity, a specialist in connection and sensor products, with more than 500 injection machines over 35 years. “Passing over our 80,000th machine to [them] validates from [all] our customers’ perspective the quality of our products and their consequent loyalty,” said Liebig at a ceremony on Oct. 24. The 80,000th machine was an IntElect 2 S 100/470-110, described by SHI as “fast and energy-efficient.” TE Connectivity is a global technology provider with headquarters in Schaffhausen, Switzerland. The company, in business since 1973, designs, manufactures and markets connectivity and sensor products for transportation, industrial applications, medical, power, data communications and households. In 2021, TE Connectivity generated sales of $14.9 billion. It employs over 85,000 people, including more than 8,000 engineers. SHI MAKES A NOTABLE MACHINE DELIVERY AT K manufacturing rates.” “9T Labs is at the forefront of a new field of composite manufacturing that has real-world implications for structural and processing simulation, material compositions and characterization, experimental testing and application engineering,” says Eichenhofer. “This partnership with Purdue is an additional step toward building a consortium of partners from academia and industry to penetrate the market and accelerate the adoption of AFT and composite materials for a broad application field.” that enters a nearby waterway; or 2) Pick an existing, proven project or program that reduces or eliminates plastics pollution, which can be cost-effectively replicated and scaled. The two winning teams were from Ateneo de Manila University in the Philippines: » The Theme One winner was Team Help Help Hooray. Their case study profiled a zero-waste initiative on Apo Island in their home country and offered a framework to extend the model to other coastal islands in the Philippines and the broader Asian region. » Team Dreamers & Doers earned the top Theme Two prize and also was the overall winner. They showcased the Aling Tindera Network, a waste-to-cash program that involves local networks of women micro-entrepreneurs, most of whom own “sari-sari” stores (small, home-based convenience stores found in many Filipino neighborhoods). In their presentation, they suggested Thailand as the country that could best benefit from a similar program. Dr. Justin Robertson, associate professor at City University of Hong Kong, which co-organized the project along with CAPP and ORA, notes: “Students quickly grasp that innovation also means identifying what is working and ensuring that good ideas do not get lost. Through research, foresight and planning, university students from a range of disciplines proved capable of uncovering high-impact projects and setting out a vision of how they could be replicated in other parts of the region.” “This competition is unique globally,” Steir says, “in that it is focused on exposing and celebrating existing, scalable programs that are working within communities, and is not a startup competition for new ideas that are unproven.” Woodring adds: “As a long-term resident of Hong Kong and as someone who has carried out extensive programs within East Asia, it was exciting to see the attention to detail, the depth of their answers, the passion shown by the student teams, and how much they understood the situations and opportunities.” To learn more about the project, view the 10 final presentations or watch a video of the awards program at https://makethecase.capp.global. After earning recognition for the India project from the United Nations Environmental Program, CAPP intends to launch its third edition of Make the Case—India soon, and plans to turn Make the Case—East Asia into an annual event, with the next contest in 2023. Purdue and 9T Labs, p. 6 Anti-Pollution, p. 6 Gerd Liebig, center, hands over SHI’s 80,000th IntElect electric injection machine at K 2022 to TE Connectivity. Courtesy of Sumitomo Demag 8 | PLASTICS ENGINEERING | NOV/DEC 2022 | www.plasticsengineering.orgTHE LEGAL ANGLE Of all the facts about the government’s “Green Guides,” maybe the most surprising is how many companies don’t know they exist. Although the Green Guides—the government’s attempt to help companies keep from misleading consumers when they make label and advertising claims about the environmental attributes of their products and packages—have existed since 1992, it’s not uncommon still to run into companies that get pretty far along in their product, package and label development process without realizing there are legal standards for when one can claim recyclability, degradability and other attributes. “Green Guides” is a nickname. The formal name is Guides for the Use of Environmental Marketing Claims. The Guides offer guidance from the Federal Trade Commission for companies that want to make claims in their labeling, advertising, promotional materials or “any other forms of marketing.” They cover claims about general environmental benefits; carbon offsets; certifications and seals of approval; compostable claims; degradable claims; free-of claims; non-toxic claims; ozone-safe and ozone-friendly claims; recyclable claims; recycled content claims; refillable claims; renewable energy claims; renewable materials claims; and source reduction claims. The FTC can, and does, take enforcement actions against companies, including big-name retailers, that make a marketing claim that isn’t consistent with the Guides. FTC last updated the Guides in 2012, but it recently said another round of updates can be expected soon. Future columns will detail some of what the Guides advise, but now we’ll focus on the overall themes. Says FTC, “sometimes what companies think their green claims mean and what consumers really understand are two different things.” So, the Guides are there to help companies better understand consumers’ understanding of claims, explain what types of substantiation (i.e., proof) are needed for claims and offer guidance about how to qualify claims so they’re not deceptive. The word “qualify” here means to add to the wording of your claim qualifications, caveats or explanatory text. It’s the “unqualified” claims that often attract trouble (as do outright false claims, of course). If you don’t include qualifications or explanations, FTC will assume you mean to convey what most consumers think a term means, and if that meaning doesn’t fit your product, they’ll say you’re misleading consumers. For example, many products or packages claim to be “recyclable.” The Guides recite that an unqualified claim that a package or product is “recyclable” should only be made where recycling of that package is available to a “substantial majority” of the population, which FTC says is 60 percent or more. If it isn’t, you could still make the claim that it’s recyclable, but your claim would need to be qualified by appropriate words or phrases to explain the limitations. I have seen the Guides described by other legal observers as “not binding,” but I don’t think that’s right. A company whose claims don’t comport with the Guides is accused of violating the FTC Act, not the Guides as such. In any such enforcement action, the FTC must prove that the challenged act or practice is unfair or deceptive in violation of Section 5 of the FTC Act, which says that “Unfair methods of competition in or affecting commerce, and unfair or deceptive acts or practices in or affecting commerce” are unlawful. Penalties for such violations can include fines that sometimes are used for refunds to consumers, and orders to stop making the claims. Some states like California have incorporated the Guides into their consumer protection laws, so states too might take enforcement actions. These days, the pressure is greater than ever to find something beneficial— anything—to say about one’s product or package so consumers know it’s not an environmental scourge. Plastics manufacturers are no doubt feeling more pressure to address the environmental effects of their products, and to tout environmental benefits in labeling and advertising, thanks to consumer interest and increasing state and even federal legal changes that require or impose incentives for such. More soon on the Guides, and the likely updates FTC will make to them. Eric F. Greenberg is Principal Attorney of Eric F. Greenberg, PC, Chicago, with a practice concentrated in food and drug law, packaging law and commercial litigation. Website is www. Ericfgreenbergpc.com. This column is informational only and not legal advice. A version of this column appeared in the August edition of Packaging World. GREEN GUIDES LURK BEHIND LABEL CLAIMS BY ERIC F. GREENBERG www.plasticsengineering.org | NOV/DEC 2022 | PLASTICS ENGINEERING | 9M ore recycled plastics of high purity are needed to meet demand from companies that have pledged to increase the use of post-consumer recycled (PCR) plastics in their packaging. Part of the solution may be found in new technology powered by artificial intelligence (AI) and harnessed by manufacturers of equipment for sorting a post-consumer waste stream into multiple value streams. Determining how best to recover plastics depends on the type of waste and recyclables collection in use, which varies widely around the world. In some countries (and even in some parts of the U.S.), there is little to no accessible collection of recyclable materials. In much of the U.S., as well as some countries in Central and South America and a few in Europe, the dominant approach is single-stream recycling, in which the consumer separates recyclables from the landfill stream (and in some cases, a separate organic waste stream), but all recyclable materials are collected together and sorted into material-specific bales by the material recovery facility (MRF). Some European countries such as Germany practice multistream recycling, in which the consumer sorts recyclable materials such as paper, metals, glass and plastics into separate containers. “Proponents of single-stream recycling say that it is easier to rely on technology employed by MRFs than to rely on consumers to do the initial sorting,” says Eric Olsson, plastics segment manager at Tomra Recycling North America, Charlotte, N.C., which is owned by Tomra Systems ASA, of Asker, Norway. Automated systems are increasingly being used at MRFs to sort materials efficiently and cost-effectively, he adds. AI and Deep Learning Automated sorting separates waste into different streams based on differences in chemical or physical properties, including size, density, shape or material type. Optical sorting uses visible light sensors, which are a type of color camera, or near infrared (NIR) light sensors, which identify material by its spectroscopic signature. Data from the sensors are processed by the system’s software, which identifies an item and decides to keep or divert it using air valves or robotic arms. The software “learns” how to do this sorting using AI based on either classical machine learning (ML) or, more recently, with deep learning. AI has been used in recycling technology for more than 30 years, but the recent ability to store very large datasets in the cloud and analyze them using deep learning has propelled the ability of algorithms to a new level, says Ty Rhoad, regional director of the Americas for Tomra Recycling. Deep learning algorithms employ convolutional neural networks that are more complex and sophisticated than classic ML, and they learn from cloud-based datasets how to recognize images. “With camera-based sorting, what the human eye can distinguish can be replicated by deep learning applied on camera images with more consistency and sometimes greater accuracy,” says Rhoad. Tomra introduced a deep learning technology in 2019 called Gain as an add-on option to its Autosort machines used for sorting at MRFs. Gain algorithms, trained with large datasets of thousands of images, can increase sorting throughput and purity of existing machines. Tomra says that these algorithms offer the potential for machines to quickly adapt to changes in the material stream. AI can, by using the cloud, be shared across machines within a company’s network. Amanda Marrs, senior director of product at Amp Robotics in Denver, says that Amp’s deep-learning AI platform, AI Neuron, was launched in 2014 and continues to “grow smarter and more effective” in identifying patterns and features. “We continuously collect random samples from all the facilities that use our systems, annotate them, add them to our database and retrain our neural networks. We also test our networks to find models that perform best on a target material and do additional training on materials that our systems have trouble identifying correctly,” says Marrs. Sortation equipment driven by machine learning generates high-quality recycled plastics BY JENNIFER MARKARIAN An automated line uses AI to sort recyclables at a single-stream material recovery facility. Courtesy of BHS UPS RECYCLING PAYOFF 10 | PLASTICS ENGINEERING | NOV/DEC 2022 | www.plasticsengineering.orgAI systems have high detection accuracy compared to optical systems without AI, she notes. For example, HDPE bottles and jugs may have labels that make it difficult to detect the underlying object’s chemical composition. “An AI-driven computer-vision system, in contrast, can determine that a bottle is HDPE and not something else by recognizing attributes like color, opacity and form factor,” Marrs explains. Bulk Handling Systems (BHS) of Eugene, Ore., designs and manufactures sorting systems and has installed its equipment, including patented technology from its National Recovery Technologies (NRT) subsidiary, at many U.S. MRFs and plastics recyclers, says Thomas Brooks, chief technology officer. The company’s ColorPlus system, which uses red/green/blue (RGB) sensors for optical sorting, is used in plastics recycling to separate colored PET from clear PET or colored HDPE from natural HDPE, an important capability because bottles of different color go to different markets. NRT’s SpydIR system uses reflective and transmissive NIR to separate by material composition, e.g., polyolefins from PET. BHS’ Max-AI machine vision system combines data from NIR and color sensors with machine vision AI, so it can sort by multiple characteristics at once. “It is the same concept as facial recognition software. Data come through the optical sensors, and the software makes decisions based on what it sees,” Brooks says. “NIR can identify the material type, but you might also want to know if it’s a thermoform [structure] or if it has a label, which you can see with the RGB camera.” Max-AI systems were installed, for example, for front- end sorting at a recycled PET facility, where the AI separates PET bottles from non-PET bottles and from PET clamshells and thermoforms. Automated sorting lines have typically been run in linear setups, with multiple optical sorters used to separate different materials, but a new, patented process from BHS uses a loop to recover different types of material with only one optical sorter equipped with machine vision and an advanced controls system. Material is held in a temporary bunker between passes, and the fully autonomous system uses data from the AI vision system paired with the optical sorter to make decisions about how to optimally sort the next pass. The first BHS container loop line is being installed in a single-stream MRF in Canada, Brooks reports. Purifying Recycled Flake The next step after sorting is typically to shred Graphic shows a fully automated container line loop using AI-powered vision systems and robotic sorters that are programmed to separate a different material on each pass through the loop. Material can be held in the storage bunkers between passes. Courtesy of BHS Machine vision driven by AI processes images and classifies data in categories by material type, color and other characteristics to distinguish different recyclables for high-speed, automated sorting. Courtesy of Amp Robotics www.plasticsengineering.org | NOV/DEC 2022 | PLASTICS ENGINEERING | 11the bales of sorted plastics into flake. AI is now enabling improved sorting at this stage. Olsson says that Tomra’s new Innosort Flake equipment uses next-generation Autosort software with Gain AI. “The equipment’s job is to upgrade the plastics waste stream to a higher level of quality,” he remarks. “Initially, it was used to purify relatively clean PET flake to create bottle-grade PET flake. But in addition to purifying PET, it now handles waste streams with high contamination at a high throughput. This capability will allow automation to go into additional markets to recover more material.” Because the system has cameras on both sides, it can identify and sort out contamination, such as flake with a piece of label on it, says Olsson. As another example, the Innosort equipment can take bottle-cap flake, which is a low-margin mixed material, and sort out two or three higher-value purified products by color and material, leaving a smaller amount of mixed material. “Sorting at the flake stage can be a game changer,” adds Olsson. For example, a whole appliance can be shredded and the components—e.g., rubber seal, ABS housing—separated as flake. “There are a lot of things we haven’t even tried yet. Wherever there are waste streams, people should be encouraged to look at what can be done with that material.” Although optical sorters have been widely adopted over the past few decades, many U.S. MRFs continued to use manual labor for quality control tasks. Today, however, adoption of fully automated systems is beginning to take off, driven partly by current workforce shortages. Brooks says that the return on investment of robotic sortation systems varies—ROI will be shorter in a big city with a large facility and high labor rates, for example. BHS typically sees ROI in less than three years. Olsson says that facilities with older, less efficient optical sorting technology also benefit from new AI-driven systems. “Older sorting technology has more trouble responding to changes in packaging types, is limited in what it can sort and has more errors than newer technology. Errors result in either a recyclable package being rejected, which increases yield loss, or recirculating multiple times, which increases operating costs,” he says. Adopters see a quick ROI with new systems because more efficient sorting reduces yield loss and operating costs. Olsson suggests that as collection from consumers increases, equipment that can sort more types of material from dirtier or less-pure streams will be crucial to enable more recovery of plastics for reuse. “Our technology is designed to shift the economics of recycling,” says Marrs. “The problem is that the cost of sorting erodes the value [of materials]. If you reduce the cost of sorting, the margin you can extract on all those materials increases.” AI- driven technology makes secondary sortation of mixed bales coming from a primary MRF both technically and economically feasible, she says. “Our technology allows our secondary sortation operations to create specific product blends for different end markets. As commodity markets shift, our AI and sorting equipment adjust to sort commodities and purities that fit real-time market needs.” Amp recently introduced an infrastructure business model in which the company builds and runs secondary sortation facilities. “The ability to sort marginal volumes of recyclables from residual streams of waste, otherwise destined for landfills, makes low-cost infrastructure a complement to primary MRFs that operate at high volumes. AMP’s secondary facilities introduce market certainty and new revenue streams for established MRFs by creating a demand for residue that would otherwise cost businesses to dispose,” says Marrs. Data collection and AI-driven software create the ability to know in near real-time what materials are coming through a facility. This knowledge can be used to optimize the process, so it works more efficiently. “Software can alert facility staff to unexpected levels of contaminants, triggering robot assignment configurations [and] verifying robots are performing as expected,” says Marrs. Brooks sees data coming from AI being used to drive business decisions. “If you know what is in a bale of material, you can better determine its worth. The fidelity of the data—does it match reality—is key,” says Brooks. Design for Recycling As automated sorting takes hold in plastics recycling, materials suppliers and package designers can facilitate sortability by working with sorting equipment and sensor suppliers to ensure that sensors “see” the product. For example, colorant suppliers have identified a solution to the problem of plastics colored with conventional carbon black pigments that couldn’t be sorted using NIR sensors. New black pigments don’t mask the material signal. Plastics are thus visible to NIR sensors. AI may solve some challenges of recycling certain packages, but it is still important for package makers to design for recyclability, says Marrs. She recommends using the Association of Plastic Recyclers design guidelines. “These guidelines are built in collaboration with industry and help to ensure plastics packaging recovery,” says Marrs. Collaboration and broader adoption of new technologies such as AI-driven sorting can make a difference in plastics recycling. AI software guides robotic arms to pick and place material for recovery. Courtesy of Amp Robotics Tomra’s Innosort AI-based sorting system reduces contamination in recycled polymer flake. Courtesy of Tomra Recycling 12 | PLASTICS ENGINEERING | NOV/DEC 2022 | www.plasticsengineering.orgSPONSORSHIP OPPORTUNITIES ANTEC ® 2023 Live is a 2.5 day in-person event with a cross-section of the plastics value chain topics on the latest advances in industrial, national laboratory and academic work. AS AN ANTEC ® 2023 SPONSOR, YOU WILL REACH A GLOBAL AUDIENCE OF PLASTICS DECISION-MAKERS AT ONE OF THE LEADING PLASTICS TECHNOLOGY EVENTS. IF INTERESTED IN IN ANY OF THESE SPONSORSHIP OPPORTUNITIES PLEASE CONTACT: Let’s create a program that’s right for you! Desiray Young, SPE Sales, +1 203.740.5428, dyoung@4spe.org Michael Greskiewicz, SPE Sales, +1 203-740-5411, mgreskiewicz@4spe.org Conference Sponsor - $10,000 Help us kick off our ANTEC ® LIVE event by being our “Exclusive” Conference Sponsor! Benefits include the opportunity to provide opening remarks and to address attendees on day 1 (up to 5-minutes), one full page ad or two- 1/2 page ads in Plastics Engineering Magazine, 5 complimentary registrations, on-site event signage, your logo on SPE event website, and recognition in Plastics Engineering Magazine & in SPE News as our sponsor. Off-Site Networking Sponsor - $7,000 Participate in our popular off-site event (details to be announced) on Tuesday, March 28, and get ready for fun! Exclusive benefits include personal welcome to attendees at the venue, signage at the event, presentation slides and announcements during technical sessions, logo napkins, and logo cups. Commercial Sponsor - $5,000 Feature your company’s 3-minute message on stage or recorded prior to each of the four Keynote Sessions on Tuesday, March 28. Other benefits include one-1/2 page ad in Plastics Engineering Magazine, 3 complimentary registrations, your logo on SPE event website, and recognition in Plastics Engineering Magazine & in SPE News as our sponsor. Welcome Reception Sponsor - $5,000 Welcome attendees to ANTEC ® during our Welcome Reception on Monday, March 27. Benefits for this exclusive sponsorship include personal welcome to attendees at the door, signage at the reception, presentation slides and an- nouncements during technical sessions, logo napkins, and sponsor provided table drops. and many more packages available at 4spe.org/ANTECSponsor!BY GEOFF GIORDANO I ndustry 4.0 promises never-before-seen manufacturing efficiencies driven by digital connectivity and data-collecting innovations that let producers measure everything from mold and material behavior to optimal energy use by one machine or many. For processors wondering how much return on investment big data can really deliver, the answer is plenty, as it turns out. From devices that simply attach to a machine’s power cord to measure power use to the most elaborate, versatile automation packages manufacturers conceive, digitally driven plastics manufacturing equipment is indeed delivering on its ROI promise. Take, for instance, the wealth of time-, material- and energy-saving innovations unveiled at two major expos in October: K 2022 in Düsseldorf, Germany, and PackExpo in Chicago. Advances ran the gamut of bottom-line boosters, from efficient, connected equipment to materials geared to reducing carbon footprint and bolstering brand owners’ sustainability stories. Exhibitors of Industry 4.0 and related equipment at K included: » Netzsch Process Intelligence, whose sensXPERT smart process system combines real-time mold data with machine-learning software to increase manufacturing efficiency as much as 30 percent using in-mold sensors that react to material deviations. The technology assesses hardware and software to produce algorithms that simulate, predict and analyze material behavior on individual machines. The system supports processes including injection molding, reactive injection molding, resin transfer molding, hot pressing and vacuum infusion with an emphasis on thermoset materials. » Wittmann Battenfeld, which demonstrated its expertise in automation and digitalization while illustrating how careful selection of equipment options can offer an excellent price-to-performance ratio. In its demonstration, one of WB’s SmartPlus 90/350 injection machines equipped with an automation cell designed and manufactured by the company produced a bubble level made of ABS using a 1+1-cavity mold from Austria’s SOLA. Top and bottom parts of the level housing were injection molded; those parts were passed to automation stations by the company’s WX138 robot. While the top part was printed at a laser station, the bottom part was placed on a tray and fitted with vials before the top part was pressed onto the bottom part. Finished parts were sent to a testing station, where a vision system checked the vials’ positioning. After quality inspection, finished levels were deposited on a conveyor belt. “ROI is often the reason companies don’t automate straight away,” stated the PMMI (Packaging Machinery Manufacturers Institute) 2022 report on the future of automation in Developers say there’s no IOU for ROI with Industry 4.0 connectivity and digitalization systems Companies across the manufacturing spectrum achieve rapid ROI from digitalized workplaces. One major area is automation. At the Universal Robots display at PackExpo, a cobot quickly and accurately palletizes shipping boxes. Courtesy of Universal Robots 14 | PLASTICS ENGINEERING | NOV/DEC 2022 | www.plasticsengineering.orgpackaging and processing, which was released at PackExpo. That said, the report noted, “The use of 3D printers to produce spare parts for automated equipment has rapidly become a reality, and use of this new but fast-developing technology is particularly attractive because it has a positive impact on the ROI for machinery, as parts can be produced more cheaply. Perhaps more importantly, it circumvents supply chain disruptions and cuts lead times.” Notably, while labor costs have increased, automation costs have decreased, the report advised. “These two factors have worked in tandem to ensure a much healthier ROI for automated solutions.” As one manufacturer of consumer packaged goods commented in the report: “[F]ive years ago, an autonomous robot might have cost … $100,000. Today, I can [automate] that same job for about $35,000. Also, the cost of labor five years ago might have been $8 an hour, and now it’s $16 to $18 just for the people on the line. So again, that makes the ROI more achievable.” Despite 65 percent of respondents indicating reluctance to automate a range of highly manual processes because they feel the cost is too high and ROI would take too long, the PMMI survey found respondents ready to use a variety of automation technologies in the next three years, including: » Remote access: 32 percent » Predictive maintenance: 45 percent » Cobots: 48 percent » Cloud/edge computing: 29 percent » Big data analysis: 34 percent » 3D printing: 31 percent » 5G networks: 25 percent » Digital twins: 26 percent » Wearable devices: 36 percent » Artificial intelligence (AI): 38 percent Seeking Answers While it’s been difficult to get specific metrics for ROI tied to digital investments, explained Justin Garski, Americas OEM segment manager for packaging and converting at Rockwell Automation, Milwaukee, “things that make an impact are being able to understand why your [connected equipment] stopped and being able to help troubleshoot remotely when there is an issue. Between these two things, we’ve seen [reductions] in machine-down-event quantity and faster time to resolution when something doesn’t work as expected.” At PackExpo, Rockwell Automation unveiled an end-to-end connected enterprise solution encompassing 3D emulation software, a robot cell, data collection and cybersecurity threat detection and repulsion. Emulate 3D creates a digital representation and simulation of an entire line; all engineering and debugging of a line’s operation can be performed offline. The company then enables flexible manufacturing with its iTRAK intelligent conveyance system and unified robotics control. Rockwell also offers Plex and Fiix software: Plex collects machine data and feeds it to Fiix, a cloud- based, AI-powered computerized maintenance management system. Protecting the data is cybersecurity technology created in partnership with Claroty, which is based in New York City. “ROI when looking at these emerging technologies is a bit of an exploratory task,” Garski continued. “We like to host workshops, which are typically a half-day to one-day long, where we really dig into the problem statement to uncover where the value truly is for each customer. They are all different, and all have unique outcome goals, so being able to break down the walls and talk in depth is an important Wittmann Battenfeld demonstrated Industry 4.0 capabilities at K 2022 by producing an ABS bubble level in an automated cell that featured its molding machine, control and robot. Courtesy of Wittmann Battenfeld www.plasticsengineering.org | NOV/DEC 2022 | PLASTICS ENGINEERING | 15step to getting a ROI.” Sourcing Molds and Parts Fictiv, which bills itself as “the operating system for custom manufacturing,” recently broadened its injection molding toolbox with new 3D visualization technology that offers design for manufacturability (DFM) feedback before customers approve and order parts. Fictiv’s platform simplifies ordering and sourcing for injection molding tools and parts through a transparent quoting process. “There is an enormous ROI when it comes to automating workflows,” a Fictiv representative said at PackExpo when queried about the company’s capabilities. When it comes to Industry 4.0, “physical equipment and advanced manufacturing machines come to a lot of peoples’ minds. But for many engineering teams, manual workflows create drag in product development and limit productivity. “Digital technology can remove massive amounts of inefficiencies, significantly reducing operating costs and increasing time to market for new products,” the representative added. “In our 2022 State of Manufacturing Report, which shows the results of a third-party survey of over 230 senior manufacturing decision makers in the U.S., we found that 93 percent of companies look to cloud-based technology solutions to increase operational efficiency for product development.” Fictiv’s ROI successes for customers include: » TransMed7: Design and development time was reduced from weeks to days, production time from months to weeks and accelerated product development from 10 years to two years for five breakthrough medical devices. TransMed7 saved millions of dollars in infrastructure and overhead costs, according to Fictiv. » Honeywell: Fictiv reduced production lead time for a critical component in the RE100 APU (auxiliary power unit) from 22 weeks to three weeks. “To calculate ROI, we encourage customers to think about the manual tasks people typically perform, and how much more productive employees could be if they had better tools to do their work faster and more efficiently,” the representative explained. “When you simplify and streamline manufacturing processes, that accelerates product development time, reduces quality issues and increases customers’ ROI. “Additionally, our 2022 State of Manufacturing Report found that 72 percent of senior manufacturing decision makers estimated that engineers are spending at least 10 percent of their time on parts procurement—this in a year when the U.S. Department of Labor released a report showing the largest first-quarter decline in worker productivity in 75 years. Our platform manages all that work for engineers, so they get that time back to innovate and develop products.” The representative added that Fictiv’s global manufacturing partner network “benefits greatly by leveraging our digital platform, which automates the manual workflow tasks involved in reviewing, quoting and producing custom parts. This results in increased operator efficiency, productivity and business revenue. For example, one of our manufacturing partners, Goose Manufacturing, was able to increase its annual revenue by over $250,000 in 12 months.” Bring on the Robots Showing off its new 20-kilogram-payload UR20 cobot at PackExpo, Universal Robots (UR), of Odense, Denmark, said many customers achieve ROI within a year of purchase, and soon buy more cobots. Companies across the manufacturing spectrum have realized ROI in as little as two months with UR cobots, according to the company, and their productivity has increased by up to 500 percent. EVCO Plastics, a custom molder with plants in the U.S., Mexico and China, spreads its cobot cost across numerous short-run production jobs and agrees with UR that ROI can come within six to nine months. UR robots are flexible and able to be oriented through the controller no matter how they are used—on the floor, installed on walls or ceilings or mounted on carts and moved from job to job. UR, which is owned by Teradyne, of Boston, offers an ROI calculator for purchasing a cobot. The company stated in a 2021 white paper titled “Building the case for robotic automation,” that while ROI is “the most common and easiest method to understand … it does not factor long-term cash flows or the cost of the capital, and thus is not an absolute measure of profitability.” Direct labor savings and employee retention savings figure heavily into the digital ROI equation, thanks to allowing employees to be redeployed into more satisfying roles, making the work environment safer and giving workers a clear signal that the company is investing in the latest equipment, the paper stated. Then there is RaaS, or robotics as a service. One presenter at PackExpo was Formic Technologies of Chicago, which rents factory robots to end-users. Co-founder and sales vice president Misa Ilkhechi explained the company’s RaaS model, in which it assesses a manufacturer’s need, determines the right brand and type of robot, then deploys it in a facility, billing an hourly rate with no upfront cost; the manufacturer pays only for the time the robot is in use. Users calculate ROI simply by subtracting hourly labor cost for an operator from Formic’s rate. Lease contracts vary from one to six years. Most of the company’s customers work in consumer packaged goods; injection molding is the second- largest segment. Ilkhechi said the majority of customers save about 40 percent in operating costs with the systems they deploy. Real-Time Data According to Datanomix, of Bridgewater Township, N.J., which provides manufacturing production data and also offers an ROI calculator, the digital investments that return Next-gen monitoring systems from Datanomix generate real-time machine data, which are converted into information broadcast in work cells on large-screen TVs. Jesse Bunnell reviews production data at molder EPTAM Precision in New Hampshire. Courtesy of Datanomix 16 | PLASTICS ENGINEERING | NOV/DEC 2022 | www.plasticsengineering.orgthe best outcomes for manufacturers are those delivering live production data. The company’s next-generation production monitoring systems connect directly to machines and pull data from control systems in real time. Data are then converted into contextualized information visually presented in the Datanomix Automated Production Intelligence platform and broadcast to a work cell simultaneously through large-screen TVs on the shop floor. “Lean manufacturing is just that: It shortens the time between notification and resolution by removing unnecessary steps that don’t add value,” explained Datanomix co-founder and CEO John Joseph. “When humans are solicited for subjective data entry, the data lose integrity and value. Delivering technology capabilities without requiring assembly, input, export, crunch or data customization is essential. “Technology providers to Industry 4.0 initiatives must take the extra steps to truly understand the workflows and subsequent information that flows from the factory floor to the business office,” he remarked. “If the analytics tools don’t match how people think about and run their businesses, the likelihood of adoption drops precipitously. Days and weeks of modeling this behavior are required to home in on the correct information feed, user experience, data latency and historical statistics pertinent to the … worker who relies on these data to produce the desired outcome for a business. It’s one part art and several parts science.” ROI for an Industry 4.0 solution can be divided and analyzed into three primary segments, Joseph advised: Time required to collect, assemble and build data models weekly by every employee in the chain of command: finding the data, correlating them and loading them into spreadsheets for analysis. Impact of the technology solution on automating data-processing tasks and the subsequent impact on time and task compression. Simply put, how much time is returned to the business to support more productive activities? What can be done with that newly discovered time made available by a technology investment? Answers include: produce more significant results for the company; generate new layers of revenue; achieve higher productivity; and more efficient decision- making, to name a few. The rule of thumb, he observed, is that a reasonable payback period is six to eight weeks. Key to remember, too, is that today’s digitally savvy workforce uses data all day long and needs that capability at work. According to Joseph: “People expect to have answers in a few seconds rather than … days or even weeks. Delaying that process because of manual data collection and translation creates frustration and stress for employees. Thanks to Industry 4.0 technology, manual data collection is replaced by real-time sensing information. The manufacturing workforce is looking for information from the production floor to take immediate action.” CNC Software/Mastercam, of Tolland, Conn., has seen large manufacturers transition to smart manufacturing and Industry 4.0 in the past several years by expanding existing ERP/ MES systems with cloud-based technologies, data mining and analysis, as well as other enterprise-wide systems, said Ben Mund, manager of channel marketing. “We’ve spoken to many shops that revisited their practices, evaluated their internal and external processes, and made changes out of necessity, in many cases driven by the pandemic. More efficient and effective use of data between machines and systems has been one of the elements that created the biggest benefits.” The CAD/CAM supplier supports customers with “a fully functional R&D machine shop at our main office, where we can bring in different elements—both software and hardware—to test how they will best benefit our customers,” Mund said. “We can also see firsthand if we need to make modifications to ensure their best use. “We focus on where Mastercam can accept and output information and how that information can be used and coordinated elsewhere in a shop’s process as needed. Mastercam powers the machine tools, but that is just one part of what a shop needs to do,” Mund said. “Mastercam also provides a platform for the shop to do various things like metrology, robotics or digital tool management, which add to the growing connectivity of Industry 4.0.” With some estimates placing unfilled manufacturing jobs at around 2 million by 2030, he added that any increase in productivity from these techniques will help in two big ways: “First, those who enter the field will immediately be more efficient and able to focus on the elements of manufacturing that rely heavily on a machinist or CNC programmer’s skill, creativity and passion. Second, as shops become more digitalized, connected and high-tech, more people will be driven to the field. Industry advancements attract those looking for new challenges, students deciding on a career and even help parents realize that manufacturing has evolved far beyond the image they may have of it.” Datanomix’s Joseph added: “Employees embrace digital information and prefer to work at companies that adopt new technology solutions that support their work and make their careers more exciting and engaging. Employees feel valued, recognized and unified with their co-workers when they have a sense of empowerment, develop skills around using data to drive production and have confident decision-making. Being part of something bigger and feeling a sense of teamwork and accomplishment is the new path for Industry 4.0 solutions.” Rockwell Automation unveiled an end-to-end connected enterprise system at PackExpo, with 3D software, robot cell, data collection and cybersecurity threat detection. Courtesy of Rockwell Automation www.plasticsengineering.org | NOV/DEC 2022 | PLASTICS ENGINEERING | 17Next >