Process Automation and Next Generation PLM

It’s no longer about simply making improvements to treat the product lifecycle.  It’s getting more ambitious. It’s about establishing a “digital twin” and “digital thread.”  It’s about a holistic paradigm shift that will indeed transform how manufacturers will manage their products.  And it’s long overdue!

For the last couple of decades, technologies in the product lifecycle space have been point- solutions oriented.  Think configurators, CAD systems, PDM, document management like SharePoint, FEA, ERP, etc.  In reality, these point solutions have simply reinforced existing information silos that make the “digital twin” concept a fantasyland. 

Interestingly enough, even when PLM is in place as just an engineering and design tool, other tools hopelessly attempt to glue the data together such as emails, spreadsheets, Word documents, Access databases, etc.  And collectively, various verbal, manual, cultural, water-cooler, processes have been concocted to try and bring some order to the chaos.

Many organizations will admit that this evolution of point-solutions, manual interventions, data silos, and cobbled processes have eroded profits, impaired morale and impacted customer reputation. But what to do?

The Promise of the Next Generation PLM

We’ve used the diagram below as one way to characterize the promise of next generation PLM.   Simply put, it’s about data cohesion and repeatable processes.  More specifically, it’s about tying data together, at a granular level, so that processes can reference the actual data items that are being acted on. 

For example, in the case of a quality control process, a certain task in the process can reference and link directly to the most recent part in question, a current version of the part’s requirements, and the correct quality control template that needs to be completed for that task.

With this approach, it’s finally possible to establish a digital thread of activities.  Literally, from the time of a quote (in the case of BTO/ETO businesses) all the way thru delivery and feedback.

PLM Data Process Matrix.png

Picking a place to start in this journey will likely vary depending on the nature of the business and challenges an organization faces.  Do you start shoring up your data or automate processes?  Or both?  It can be argued that starting with processes helps to envelop organizational policies and standards while solidifying stake holders and data requirements.

However, it’s not just about documenting processes.  What good are documented processes if no one follows them?

Automating Processes with Next Generation PLM

There are countless process automation tools.  However, the demands of managing the product lifecycle in particular will require a seamless link to varied array of product data.  Effectively, think of these processes as collectors of data that help to build the digital thread and eventually the digital twin. 

Aras Innovator has put itself on the map as the next generation PLM platform that has been built from the ground up with a vision for maintaining the digital twin.  Processes are integrally woven in with product data and visa-versa. It is a platform that empowers users to instantiate processes that drive adherence, consistency and repeatability. 

Make the Process Smart

Imagine building out an automated process to support the quoting cycle for BTO/ETO/Supplier manufacturers.  By leveraging “smart” process capabilities, routings and tasks are dynamically adjusted as a function of the customer, product line, new versus, resubmitted quote, and so on.  As these tasks get underway, only users that need to contribute are alerted. And once they get their tasks, they’re prompted for only the data required. No more email alerts burying everyone regardless of the role they play in developing a quote.

Anticipate Change

Automated processes inherently have a way of illuminating improvement opportunities. You don’t know what you don’t know.  But by simply establishing a process, users will invariably suggest improvements and refinements (complaints). 

Ultimately, the pursuit of user adoption will drive change.  Hence, having a workflow engine that is flexible enough to support the iterative nature of changes will be critical.  This includes having logical user roles and rights, integrated analytics and integration extensions to other repositories of data.

Rethink the Data Model

As the various processes are being instantiated, exercised and improved, insights are developed as to what data is needed and when.  For example, as part of the digital twin concept, operational requirements precede the functional and even physical details of a product.  So based on the nature of the product and its data components, a model can evolve and likewise be created. 

 Courtesy of Aras Corporation

Courtesy of Aras Corporation

Conclusion

Product data is developed and accumulated throughout its lifecycle from initial concept to obsolescence.  By establishing repeatable and smart processes to collect, manage and secure this data, organizations have the opportunity to achieve the promise of next generation PLM. This journey is not a big-bang event.  Rather it is an intentional and deliberate initiative marked by a “crawl, walk, run” approach.  Process automation is the cornerstone to this approach that will support continuous process improvement, boost profit margins, and enhance customer relations.