PCB production optimization with Siemens Valor Process Preparation VPP

Timeboxed innovation for Endress+Hauser flow to implement a Industry 4.0 solution

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Internationally active, leading provider of measuring instruments, services and solutions for industrial process engineering based in Reinach near Basel (Switzerland). 

More about the Endress+Hauser Group.

Customer Satisfaction, Feedback

"Thanks to the efforts of R. T., the project was successfully completed as planned."

(R.T. = Rainer Tolksdorf)

Initial situation

Each production system uses its own tools, which leads to isolated solutions, data silos, a lack of transparency and problems with know-how transfer and employee deployment. A shared, self-developed information tool is no longer maintainable and urgently needs to be replaced. In accordance with the internal Lean Innovation Standard, the replacement of the information tool with Siemens Valor VPP was planned in four clear sections with milestones in order to achieve the formulated goal.

Solution with Valor VPP and ODB++ data format

Group-wide use of a standardized Industry 4.0 solution (Siemens Valor VPP was selected) to manage as many work preparation processes as possible in electronics production using parts lists and design data in a standard format accepted by the industry.

Preliminary phase

Setup of a test server with Siemens Valor VPP and successful proof of function in milestone 1 and readiness for use in operation in milestone 2.

Success criteria preliminary phase

Successful import of ODB++ design data and extended Bill of Materials (BOM), component validation using an online database, programming of a 3D AOI (optical inspection) system for quality assurance.

Tools and technologies used

Microsoft Server, PostgreSQL, Sharepoint, Siemens Valor VPP, MS Office, MS Teams.

Methods used

Endress+Hauser internal lean innovation methods with ISO9001:2015 compliant project management, Microsoft Azure DevOps (SCRUM) and  Digital Innovation Engineering from Tolksdorf.digital

Project contribution and role

Timeboxed Innovation  Digital Engineering Siemens Valor Process Preparation VPP / NPI: 

Final result

The project was divided into sprints in parallel to the lean innovation approach with Azure DevOps and successfully implemented according to initial planning. It fully meets the expectations and plans formulated in the initial situation and creates new scope for further optimization and internal collaboration. The transfer of know-how enables the specialist department and the product owner to continue to maintain and develop the solution independently.

Contact to the reference

Frequently asked Questions (FAQ)

How was the balance between the drive for innovation and production stability maintained?

Through an agile approach based on DevOps principles. This made it possible to introduce new software iterations (Siemens Valor VPP) into production without compromising Endress+Hauser's high quality standards. The focus was on evidence-based testing to address reservations with facts.

What role did change management play in the implementation of Siemens Valor?

Implementing the technical solution took up an average of 20% of the time. The rest was needed to record and harmonize the understandably different perspectives and interests of development and manufacturing. Change management was an integral part of the project thanks to the ongoing support process. This ensured that the new way of working was accepted in the long term and that process reliability was increased in the long run.

What role does artificial intelligence (AI) play in the project?

At that time, software manufacturers usually provided generic documentation that said little about specific system settings. Surprisingly, AI had already been trained on Valor VPP and was able to provide valuable information about the setup, which was successfully validated on the test system.

How was the system and user documentation designed?

Since multilingualism is important at Endress+Hauser and the system settings of Valor VPP offer many options that are difficult to describe, creating a video with explanatory text (similar to YouTube explainer videos) proved to be the most efficient and effective method.

Author: Rainer Tolksdorf @ Tolksdorf.digital

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