Robotics in Industry 4.0—5 Major Challenges for Packaging
Since it was first used by the German government in 2011, the Industry 4.0 concept has been a buzz topic for many manufacturing sectors. Broadly, it can be understood as updated methods of production in which machines and products are digitally networked together.
Incorporating diverse concepts—like the Internet of Things (IoT), cloud computing and artificial intelligence (AI)—its goal is to change traditional industrial production plants into the smart factories. However, how to most efficiently adopt these concepts into the packaging industry remains a challenge.
In its new study, The Impact of Industry 4.0 on Packaging to 2023, Smithers Pira pinpoints the nascent technologies that are enabling this fourth industrial revolution and highlights five major changes that will be witnessed in the next five years: Automation and robotics, smart packaging, Big Data and cloud computing, mass customization and E-commerce.
Access PMMI’s 2018 Industrial Robot Opportunities in Food and Beverage Processing Report by visiting: oemgo.to/robots
The packaging industry is responding to increasing brand owner demands for shorter product lifecycles and cost-driving variation—leading to shorter runs, more line changes and more downtime on traditional converting lines. A new generation of robotic systems and, in particular, improvements in data flow mean package production can integrate and connect key processes—design, production, distribution and maintenance—into a single holistic approach. The most significant impacts of new robotic platforms will be felt in converting and distribution.
Bright Dairy, the third largest player in China’s growing dairy foods market, has collaborated with Swiss company Tetra Pak to design a manufacturing facility for yogurt. When it is fully integrated, it will be able to process 500 tons of raw milk daily. All processing and packaging operations in the plant and their enterprise resource planning (ERP) systems will be integrated with the Tetra Pak’s PlantMaster manufacturing execution system (MES). The platform includes equipment, quality and utility management, a warehouse management system, and traceability analysis and reporting from reception of raw milk to warehouse handling using QR codes.
In December 2017, BASF embarked on a digital transformation via partnership with Dutch startup Ahrma to approach the growing market for smart logistic solutions and a more transparent, reliable and efficient supply chain.
Cooperating with robots
Human-robot interaction is today complicated because of the risk of injuries. Pre-Industry 4.0, manufacturers solved this issue by not letting humans and robots share workspaces.
This will change with the evolution of superior AI, allowing for collaborative work between people and a new generation of cooperative robots (cobots). Collaboration is not only about safety; it means that people and robots working close together with flexibility and productivity.
In addition, a different class of cobots are taking shape. Dubbed chatbots, these are designed to aid knowledge workers by assembling information from back-end systems, such as the latest inventory levels or arrival time of the shipment. They are intended to be accessible via a variety of interfaces, such as web, mobile app or augmented reality (AR) glasses.
System-wide machine learning
Historically, automated systems have been limited by the vision system and software installed by the original programmer. This approach is changing as superior machine learning algorithms are installed.
Machine learning algorithms are required with computational methods to improve themselves or the equipment they operate—in effect learning information directly from data without relying on a pre-set and fixed equation or program and without human interaction. For these to optimize production, the more data that can be produced the better, and the greater the refinement of performance. Translated to the packaging industry, this will increasingly be about analyzing information from thousands of remote sensors to reduce product defects, shorten unplanned downtimes, improve transition times and increase production speed.
Robotic systems can already proactively monitor and adapt to changes in a production line. By networking multiple machines, each robot will increasingly be able to adapt dynamically not just to its work, but that of other robot and humans within the smart factory.
Major companies are now making investments in machine learning-powered approaches to improve all aspects of manufacturing. It is projected to grow noticeably; in the coming five years, this will spread for specialized industries into mainstream sectors, including packaging. To realize machine learning’s full potential, however, companies must break down data silos. Pooling data for advanced synthesis across companies is key to creating new, performance-based business models.
A common machine language
Industry 4.0 cannot operate without standardized interfaces between machines. Packaging equipment producers are a step ahead of the rest of the industry in this with the Packaging Machine Language (PackML). First developed more than a decade ago, this digital communication standard allows a common interface and operational consistency across a packing line.
The robot producers have agreed to use PackML moving forward. By 2023, the language is likely to become a global industry standard. For example, Euromap—the umbrella organization of the European plastics and rubber machinery industry—recently accepted PackML for Industry 4.0 work.
A changing labor force
With a higher degree of automation in a smart factory, fewer workers will be needed. Lower-skilled workers, like drivers and cleaners, will face redundancy. But there will be a premium on employing more skilled workers—especially software engineers and programmers.
The introduction of more robots in production plants will change strategic geographical considerations. Relocating facilities in search of cheap labor will be less of a priority—hence packaging manufacturers can relocate plants closer to their customers and realize new time and logistics savings.
This will allow some rebasing of factories to North America and Western Europe. Meanwhile, the importance of software means large firms will be able to control multiple sites from a centralized hub, giving greater control and uniformity in production and printing.
Stuxnet—malware used to disrupt Iran’s uranium enrichment operations—has shown how vulnerable an integrated plant can be to computer viruses. As more and more systems are connected to smart devices, enterprise systems and the Internet, pack manufacturing operations will be increasingly exposed to cyber attacks.
It’s easy for a determined hacker to break into a network and download control logic to an industrial controller or change its configuration. Thus, there is a growing onus to adopt integrated cybersecurity solutions and implement monitoring software to protect equipment.
The impact of increased automation and other key components of Industry 4.0 are ranked and assessed critically in the new Smithers Pira study. Access the report at awgo.to/smithers.