Our Digital Transformation Vision

The Roadmap to Operationalize Digital Transformation

The convergence of physical and cyber worlds impacts every aspect of society. Packaging is no different. With voice of customer in mind, we built a 4-stage, multi-year roadmap to operationalize digital transformation across a customers’ packaging operation. Our four-stage strategic plan is founded on a premier partnership with Rockwell Automation, with a focus on building every customer solution based on the Allen Bradley® Integrated Architecture™ controls platform.

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Allen-Bradley Controls

Phase 1: Establish Smart, Connected Automation Foundation

Migrating our machines onto a single, standardized controls platform to establish a smart, connected “foundation” for our customers. This phase is almost complete.
Customers benefit from a unified, commercial off the shelf controls platform because it better adheres to common corporate standards, leverages a very common skills set (Allen Bradly is widely known), and gives customers easy, global access to competitively priced commercial of the shelf parts and support services.

Phase 2: Augmented Reality Tools for Training and Maintenance Workflows

Layer in augmented reality workflows and integration to deliver new capabilities in staff training and machine maintenance efforts.
Software-based Augmented Reality tools, such as PTC’s Vuforia or Chalk improve maintenance and training workflows. Vuforia™ enables common mobile devices to display virtual overlays on physical equipment that visually simulates maintenance or troubleshooting procedures. Chalk™ facilitates real-time, interactive visual collaboration with remote expert resources.
From a customer impact standpoint, the ability to deliver instantly understandable visual training/guidance or collaborate with expert resources is a game changer. It enables new remote maintenance techniques and leverages existing widely employed smart phones and tablets.
AR Work Instructions
AR Digital Twin

Phase 3: Incorporate Internet of Things (IoT) Devices

Expand to incorporate more IoT touchpoints, essentially blending the machine with its digital twin to offer an enhanced operating experience and information integration. Expanding the breadth and depth of embedded IoT enables us to integrate with advanced IoT applications that expose detailed machine operations in real-time to production staff.
This stage represents an exponential leap in data acquisition and exposure, and sets the stage for the coming cloud-based, big data environment. More data means that more in context production information is available in real-time both to staff and to on-board diagnostics.

Phase 4: Predictive Analytics and Performance Benchmarking

In the final stage of our plan we will start to offer unique insight by applying machine learning and AI to the vast amounts of as-produced data collected during production.
This final stage represents an evolutionary step for customers in terms of their OEM relationship. Big data Solutions that leverage machine learning and artificial intelligence (AI) will make the holy grail of predicative maintenance analytics in our markets attainable.
This will be disruptive – first because predicting failures before they occur enables customers to restructure legacy maintenance and cost models to eliminate a huge percentage of unplanned downtime, and 2nd because industry-wide performance benchmarking draws back the curtain and exposes things for how they really are.
AR Analytics

Augmented Reality for Your Packaging Operation

AR is making it possible to more quickly train or provide expert guidance to a workforce, and provide them the information they need at the right time and with the correct context.


Staff can be guided through how to get a machine back up and running, perform a product line changeover, or be alerted to a performance issue using AR technologies.


We see the AR value proposition as delivering significant productivity gains in human labor; improvements on the order of 30-60% depending on the specific application.

AR Work Instructions