manufacturingtechnologyinsights

Connecting Product Development and Manufacturing - A Necessary Foundation for Industry 4.0

By Peter Schroer, Founder and CEO, Aras Corporation

Peter Schroer, Founder and CEO, Aras Corporation

In an ideal world, the design of the manufacturing process would run concurrently with the development of the product.

“Change management, collaboration, and even algorithmic design checking are all simplified by co-existence of EBOM and MBOM”

The benefits of better collaboration between the disciplines are well understood. Design changes that result in manufacturing optimization including cost, quality or schedule could be implemented earlier in the product development cycle where the cost of change and risk is much lower. Manufacturing would gain better visibility, and more lead-time to innovate new processes to achieve cost, quality and schedule goals while allowing product developers the freedom to innovate.

These concepts are decades in the making – including Design for Manufacturability and 6-Sigma initiatives. Yet challenges remain, especially with dramatically increasing product complexity in the age of Industry 4.0 and the Industrial Internet of Things.

New Challenges Outpace Old Methods

A significant limitation comes into play when organizations are burdened by separate enterprise systems.

Typically, this involves a standalone Product Data Management (PDM) solution for the product development teams and ERP for the manufacturing engineer. IT interfaces between the systems are complex, and while a one-way push of new Bill of Materials (BOM) data from Design to Manufacturing is a commonly achieved scenario, propagation of daily BOM updates and iterative feedback of recommended changes back to the design system are complex, and rarely implemented.

Poor handling of change transactions between systems is the root cause of most problems. Consider that Work Instructions are usually authored in a standalone system, separate from PDM and ERP. Often the work instruction authoring is not even a “system” at all, often authored in MS-Word or MS-PowerPoint. Most companies do not have the internal knowledge, discipline and/or tools to implement perfect closed loop change systems, especially in the context of data spread across three or more separate enterprise IT systems, and it’s common for some changes to be missed.

And in many cases, teams use Excel spreadsheets to communicate BOM changes. This is a “homegrown” approach often force-fit to reconcile differences between the Engineering Bill of Materials (EBOM) and the Manufacturing Bill of Materials (MBOM) to verify product integrity.

A Platform Approach

What’s needed here is a fresh look at the approach and at the organization’s IT boundaries. We have seen great success in moving the Manufacturing Engineering processes of MBOM creation and Work Instruction authoring back into a shared platform database with Engineering EBOM management. This tightens the closed loop change process, and simplifies the IT challenge of maintaining real-time synchronization between PDM, ERP and MS-Office data.

By creating a common platform environment, call it a Business of Engineering Platform, both the EBOM and its multiple MBOM companions exist within a single database and application context. This dramatically simplifies the mapping of the EBOM to MBOM, and ensures that subsequent changes that need to propagate from EBOM to MBOM are handled efficiently. Reconciliation methods are also simplified by running within a single database context.

Change management, collaboration, and even algorithmic design checking are all simplified by co-existence of EBOM and MBOM. A less obvious benefit of the co-existence, but with significant long term advantage is the use of machine learning and integrated digital thread traceability within the PLM to remember how and why the EBOM to MBOM mapping was made. The next change, or even the next new product, can leverage the knowledge base and rules to automatically propagate ECO changes from EBOM to MBOM based on previous decisions. The payoff ? Reduced trial-and-error data manipulations, improved traceability and accelerated time to high yield production.