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PACK EXPO Las Vegas 2019 Innovations Report

The trade show featured cutting-edge technologies and solutions to help processors take their operations to the next level.

PACK EXPO Las Vegas Entrance
PACK EXPO Las Vegas and Healthcare Packaging EXPO welcomed more than 31,000 attendees—an 8% increase from the 2017 show.
Photo courtesy of PMMI.

What better place than PACK EXPO Las Vegas and Healthcare Packaging EXPO to take the pulse of the packaging technology scene? And in 2019 this was truer than ever, as the show broke records for number of exhibitors, total exhibit space, and total attendees. By the show’s close, more than 2,000 exhibitors covering nearly 900,000 sq ft of the Las Vegas Convention Center convened with more than 31,000 attendees—an 8% increase from the 2017 show.

“With the incredible role it now plays for the packaging industry, PACK EXPO Las Vegas and Healthcare Packaging EXPO was the international packaging event of 2019,” says Jim Pittas, president and CEO of PMMI. “The sheer size and scope of PACK EXPO Las Vegas and Healthcare Packaging EXPO indicates that as our industry continues to prosper, it turns to PMMI shows for the solutions and tools to improve business.”

As in years past, the editors at PMMI Media Group fanned out across the aisles of the show looking for innovations. We then unpacked our notebooks, emptied our tape recorders, and uploaded our photos and videos so that we could bring you this PACK EXPO Las Vegas 2019 Innovations Report. Considering the size and breadth of the show, we’ve no doubt missed a number of things, and for this we apologize. If there’s something you saw that is not covered in the pages that follow, please let us know.




Automation and Controls

Two PACK EXPO Las Vegas exhibitors a few aisles apart in the Lower South Hall featured analytics platforms that provide better real-time visibility into the manufacturing process.

01 OdenFrom Oden Technologies comes The Oden Platform (1). It’s a comprehensive Industrial Internet of Things (IIoT) analytics platform that provides employees at each level of a manufacturing plant with clear visibility into multiple data sets pertaining to the manufacturing process. Oden helps manufacturers monitor their production process and improve operational efficiency in real time by diagnosing problems that otherwise would have been missed. Oden helps users track performance metrics of multiple assets and accurately predicts downtime based on historical data. In addition, by utilizing the platform, manufacturers can reduce bottlenecks.

This platform is designed to help manufacturing units attain the best performance out of their manufacturing assets and leverage artificial intelligence (AI) and machine learning algorithms to empower prescriptive analytics. This allows employees on the floor to diagnose and mitigate issues as soon as they arise or offer alerts to avoid issues.

Notably, The Oden Platform is designed to integrate seamlessly into both modern and legacy production equipment. In addition, most analytics solutions face issues in retrieving data from legacy devices, which creates visibility gaps. The Oden Platform addresses this issue because the firm’s principals have developed a knowledge base of expected device behaviors based on its deployments across a wide range of environments.

The ability of The Oden Platform to serve everyone in the manufacturing enterprise, including machine operators as well as line managers, allows customers to carry out connected deployments on a holistic level. In addition, employees with limited data science knowledge can leverage the solution, helping customers to include more employees in their digitization efforts while maintaining a shorter learning curve.

One more note on a specific component in The Oden Platform, is an AI-powered recommendation engine called Golden Run that uses data to find the optimal conditions for production. As the Golden Run looks at how a manufacturer previously made a product, it identifies the best sections of each run and uses those insights to create perfect run settings. With the Golden Run, there is no need for human analysis or input—the calculation is all done through the algorithm.

For example, if an operator ran a stable production for two days and the process ran at optimum efficiency for just 15 minutes, the Golden Run engine would define the perimeters of that time. Using these new settings, operators could replicate the same optimal conditions for the full duration of their next run. 

More machine analytics

02 WintrissOther exhibitors were keenly interested in offering analytics that pave the way to predictive maintenance. Among them was Wintriss Controls, which demonstrated its new ShopFloorConnect Version 6.0 (2) at PACK EXPO. ShopFloorConnect OEE and Shop Floor Data Collection Software collects downtime and production efficiency data from every machine in the manufacturing operation, displays it in real-time, and produces indispensable manufacturing reports, including detailed overall equipment effectiveness (OEE) reports in a variety of formats. The software can significantly increase manufacturing capacity and profitability by identifying and quantifying excessive production losses and bottlenecks.

For even better production analysis, users can now improve the OEE of their machines by tracking the reasons for scrap. Version 6.0 also allows users to manually enter good and bad part count data, vital for OEE calculation, when machines with batch processes make it impossible or impractical to automatically count the parts as they are being produced. And to better serve customers in North America and across the globe, this latest program version can handle multiple languages and time zones.

Also highlighting analytics was Schneider Electric, which featured its EcoStruxure Augmented Operator Advisor (AOA). An IIoT solution for machine and/or line-based maintenance solutions, it makes real-time information available whenever and wherever it is needed. The custom application improves operational efficiency with augmented reality, enabling operators to superimpose the current data and virtual objects onto a cabinet, machine, or plant. New at PACK EXPO was news that AOA has been expanded so that OEMs can now see considerably more content, such as more videos or more pages on how to set up their machines or conduct a changeover.

Also new at the Schneider booth was an IIoT product called EcoStruxure Machine Advisor, a cloud-based services platform for machine builders that makes it possible to track machines in operation worldwide, monitor performance data, and fix exceptional events, while reducing support costs by up to 50%. It lets the OEM create a machine profile online and store into that file documentation as well as additional analytics that gauge the health of the machine. “We can monitor up to 10 variables that are used to define the mathematical model of the application and what is considered its ‘normal’ behavior,” said John Partin, packaging BDM at Schneider. “Then the cloud-based AI will be able to identify anomalies and inform the appropriate people of any deterioration in the machine’s performance.”

Adding artificial intelligence to control logic

What if a robot could automatically adjust its grip based on the size and shape of the object? In other words, a robot that could fine-tune how it is holding an object so as not to drop it, much in the same way humans do. According to Siemens, it’s quite possible, and it all comes down to AI based on neural networks. Neural networking is a technology that mimics the human brain in that it is able to recognize complex patterns. With that in mind, Siemens says that by adding AI via neural networks to traditional control programs that were designed to execute a set task, the capabilities of the system can be extended to change based on the parameters of the product or process. Bottom line: Machines become naturally flexible. 

In 2018, at the SPS/IPC/Drives show in Nuremberg, Germany, Siemens announced a module that will integrate AI capabilities into the company’s Simatic S7-1500 controller and the company’s ET 200MP I/O system. This past year at PACK EXPO Las Vegas, Siemens introduced the offering in the U.S., setting the foundation for a future portfolio that will enable AI across all levels of Siemens’ Totally Integrated Automation (TIA) architecture, which is a combination of hardware and software that links everything together seamlessly. The goal with TIA is to apply AI within applications ranging from Siemens’ MindSphere, a cloud-based Internet of Things (IoT) operating platform, out to the industrial edge and even to the controller and field devices.

03 Siemens“With artificial intelligence, we are able to train, recognize, and adjust to allow more flexible machinery,” said Colm Gavin, factory automation digitalization specialist at Siemens during a press conference at PACK EXPO (3). “Because, do we want 10 machines to package 10 different types of products, or a tool that accommodates different packages and different sizes and automatically adjusts to the new format?”

In packaging, for example, bottles are coming down a conveyor belt quickly. If the system is trained for pass/fail, the moment something goes out of tolerance, it will fail. But by using AI to train neural networks to recognize a billion pictures of every possible combination, a vision system will be able to figure out the rules on its own.

Applications in the areas of robotics, quality assurance, and condition monitoring are especially suitable for the TM NPU module. But applications are limited only by the user’s imagination. At PACK EXPO, Siemens demonstrated a robot with “flexible grasping” using AI, which looks at a shape and calculates the optimal point, then the gripper can pick it up (see video at pwgo.to/5364). Once it understands the best grasping point, the AI tells it where to go. “You don’t need to program the robot as AI makes it possible to grasp arbitrarily shaped and positioned objects,” Gavin said, adding that the ability to mimic the human hand in manufacturing has the potential to be a very big business.

Predictive maintenance

During PACK EXPO, Mitsubishi Electric debuted its Melservo-J5 total drive solution. The version of the system that will debut in the Americas will have added features and functions that consumer packaged goods (CPG) companies and machine builders in this region have requested, such as predictive maintenance capabilities.

“After the machine has been used for two or three years, it starts to get fatigued,” said Sloan Zupan, Mistubishi Electric’s senior marketing manager. “Through our motors, we are measuring the conveyor belts and how much tension is in the machine. Through predictive maintenance algorithms built into this motor, we make changes through the motor to compensate for the wear and tear and we notify the control system that we made that change and to the maintenance engineering staff.”

The system also has Time-Sensitive Networking (TSN) capabilities built into it, which according to Mitsubishi, is first of its kind for servomotors.

Emerson Automation Solutions has been working with Busse/SJI, an OEM of palletizing equipment, to test out new predictive maintenance technology, which it showcased at PACK EXPO Las Vegas. 

Specifically, the Emerson technology is able to monitor pneumatics and vibration to predict the health of the system, alerting operators when there is an issue, as well as providing direction on how to resolve it.

“This is very important for the next generation of workers as they may not be as used to the equipment as the seasoned operators are,” said Marcus Parsons, Emerson’s director for food and beverage. “It lets them know right away if there’s a problem that needs to be solved.” 

In a demonstration (see video: https://bit.ly/2Rw6kQz), Emerson provided an overview of a Busse/SJI machine, indicating the location of wireless sensors that are used to monitor the overall health of all the assets inside of the machine. 

The goal of the predictive maintenance application is to improve the machine throughput. A dashboard provides detailed information to the operator, from the main control area to all of the components, each labeled with independent viewpoints to that part of the machine. If there’s an issue, an operator can go to the specific area to attack the problem. 

For example, on a gauge, the system will provide a status—green, yellow, or red. If the status changes from green to yellow, an operator can click on the information in the dashboard to drill down into specifications, and if there’s an immediate component replacement need, they can see the number of days to delivery and the price on the component, a feature that allows the application to tie into the enterprise resource planning system. There is also a historian that keeps track of how the system is running on an hourly basis, looking for any changes over time to provide information that helps operators decide if they need to correct something before it goes out of control, or if the overall health status is good.

According to Emerson, the work with Busse proves to its customer base that Emerson has a simple system—basically based on three sensors—that can pick up more than 100 points of information from a very large machine. 

Introducing MaaS

Pearson Packaging Systems announced a new purchasing method, known as machine as a service (MaaS) that will allow manufacturers to use Pearson case erectors, sealers, and compact palletizers as part of their operation, but without the upfront equipment investment. Instead, Pearson retains ownership of the machines, while customers pay for output.

Senske says MaaS is an ideal option for companies who prefer to pay for automation incrementally, or who have an immediate need for end-of-line machinery, but don’t have approved funding. 

Pearson will ship MaaS equipment to customer facilities, offer installation and start-up support, and train operation and maintenance personnel as part of the package. Machine users pay an established price per case, with the option to purchase the machines outright at any point during the contract term.

MaaS users can access data beyond basic case counts, including information relating to fault types and counts, and uptime and downtime durations. This data is useful in identifying month-over-month trends, proactively spotting potential issues before unexpected downtime occurs, or highlighting the need for additional operator training. In addition, troubleshooting efforts will be facilitated and response times can be executed more swiftly with MaaS as automatic notifications are sent to Pearson’s service department, alerting them when excess faults, network outages, or other performance issues occur.

Integrated image processing

PC-based control specialist Beckhoff has expanded its established, highly successful TwinCAT product range to include TwinCAT Vision, an 04 Beckhoffintegrated image-processing solution (4).

TwinCAT Vision follows the Beckhoff philosophy of open control technology. First, it is hardware-neutral: TwinCAT Vision works both with line-scan and area-scan cameras with GigE Vision Interface. (GigE Vision is an interface standard introduced in 2006 for high-performance industrial cameras. It provides a framework for transmitting high-speed video and related control data over Ethernet networks.) Second, TwinCAT Vision supports software extensions, allowing users to access raw camera data and incorporate their own image processing algorithms easily.

Because TwinCAT Vision is integrated into the TwinCAT control platform, it can connect directly to TwinCAT IoT and TwinCAT Analytics. This ensures easy communication with the cloud, enables access to cloud-based services, and streamlines Industry 4.0 applications.

Integrating the programmable logic controller (PLC), motion control, robotics, high-end measurement technology, and machine vision capabilities on a single platform enables superior real-time application performance and significant gains in machine efficiency. It also avoids unnecessary delays in motion and robotics.

TwinCAT Vision is directly integrated into the TwinCAT Engineering environment. Cameras can be added and configured easily under the new Vision node, and they can be calibrated there as well. It is also possible to capture a camera image stream and to feed in the recording instead of live camera images. Alternatively, images in a range of formats can be loaded. This means that, even without camera access, users can still develop and implement image processing procedures.

Also pushing the boundaries in the area of remote diagnostics and machine monitoring is Nordson, which used PACK EXPO Las Vegas as an opportunity to incroduce its ProBlue Flex hot glue melter with BBconn controls. The ProBlue Flex incorporates intelligent technology that the company says enables ultra-precise dispensing accuracy. It is complemented by Nordson’s new BBconn controls, which allows for remote operation, more visibility, real-time oversight, and the data and analytics needed for continuous improvement.

INTRODUCING! The Latest Trends for Food Products at PACK EXPO Southeast
The exciting new PACK EXPO Southeast 2025 unites all vertical markets in one dynamic hub, generating more innovative answers to food packaging and processing challenges. Don’t miss this extraordinary opportunity for your business!
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INTRODUCING! The Latest Trends for Food Products at PACK EXPO Southeast