March 2008 eNews

Design for Manufacturability reviews bring rewards

By Sameer Kondejkar

Today’s mechanical product designers are in a very unique position where the product lifecycle has broken the barrier of manufacturing factory walls and entered into the business process of enterprises. This was possible because of the integration between the product lifecycle management (PLM) and enterprise resource planning (ERP) systems. The process that was restricted earlier to the product data management (PDM) and PLM now needs to take various parameters according to the automation requirements for the cost effective manufacturing. Various tools developed in the automotive domain based on concepts such as design for manufacturing, design for engineering are helping the designers to optimize the design process by upstream validation techniques to find manufacturability issues.

Yet the companies applying these techniques haven’t been able to realize the true value of their investment in implementing Design for Manufacturability (DFM) in their design process.

The reasons for the apparent performance gap can be many. Yet it can be safely stated that DFM technologies and applications designers have not been consciously looking to enhance their value through process automation and knowledge capture. What this implies is while the PLM as a concept is getting extended over the complete enterprise and generating benefits through integration of PLM with ERP systems and automation, the design process is still largely manual and knowledge-driven. These two parameters lead to the performance shortfall of DFM-based applications when measured against the benefits one gets through automation of various industrial processes.

Reviewing design for manufacturability – avoiding sharp internal corners

Overdependence on manual intervention

Most companies implement DFM reviews in the form of checklists for manual review process and/or cover DFM in periodic training programs for their design engineers conducted by manufacturing experts. Another commonly followed practice is calling manufacturing experts for design review from the manufacturability point of view.

These methods are manual-intervention-based and need close interaction between design engineer and manufacturing experts. As “Design Anywhere and Manufacture Anywhere” is becoming a norm in industry, geographical distance between design engineer and manufacturing engineer is increasing. In these changed scenarios, iterations of design have higher cost and time implications.

The following examples will highlight the issues faced in existing DFM implementation practices:

DFM guidelines recommend avoiding sharp internal corners inside pockets when it is to be manufactured using milling process. As milling cutters are typically circular, achieving sharp corners would need multi-step milling process with gradually reducing the size of mill cutters and special machining at the end to finish as sharp corners. All this makes machining time consuming and an expensive process.

To apply this DFM guideline, traditional methods would focus on following:

  1. Educating design engineers about reasons for having such rule and imparting regular training on similar issues.
  2. Manual verification of design to find sharp internal corners within pockets of the design. However, this may be a time-consuming task for complex geometries, and the reviewer may miss a few violations if only visual inspection is relied upon.
  3. When a design with missed issues reaches the manufacturing shop, manufacturing proceeds with extra processes to achieve sharp internal corners, or sends back the design with comments to the design engineer for modification.

The examples highlight key issues faced in existing DFM implementation practices, which can be summarized as

  • Inconsistent design quality
  • Time-consuming processes
  • Need of proximity between design and manufacturing engineers
Automation of DFM knowledge repository

Effective implementation of DFM would greatly facilitate the process, if a review of design against an organization’s set of DFM guidelines is automated, and interactive feedback for design engineers is generated to take immediate corrective actions – all this within design process itself.

Key technologies which can facilitate automation in DFM implementation:

  1. Knowledge of Capture System or Rule Engine: As DFM primarily deals with manufacturing process knowledge to review the design for manufacturability, a good knowledge management system is mandatory which can help capture this knowledge in a suitable format for digital usage independent of those who contributed to such knowledge.
  2. Automatic Recognition of Manufacturing Feature-Operations: The ability to analyze design geometry, and automatically extract various manufacturing features/operations from it, is the first step to facilitate any kind of automation in DFM implementation. This recognition needs to be independent of the way the geometry may have been modeled.
  3. Validation and Feedback Mechanism: This stage brings together DFM knowledge repository and recognized manufacturing feature parameters to automatically verify the design for any DFM related violations. It can also offer interactive feedback to the design engineer on the reason and exact locations of violations and possible steps for corrections.

Applying these technologies and framework, automation of DFM knowledge repository and the ability to provide interactive feedback to design engineers within their design system can be achieved.

Conclusion: more effectiveness

By bringing in automation in DFM implementation, effectiveness of the process would greatly increase by achieving consistency, reliability and predictability independent of those involved. The need for location proximity and iterations of design between design and manufacturing engineers is minimized. DFM related knowledge gets captured in a reusable systematic format, and it also establishes mechanism for its scalable expansion.

Benefits of automated DFM reviews can be summarized as:

Improved design quality

  • Early prediction and prevention of manufacturing problems

Better productivity

  • Automation of review process
  • Decreases lead-time by reducing backtracking and design iterations

Knowledge capture and reuse

  • Scalable method for capturing of DFM experience in knowledge base

Automated DFM validation will not only improve the quality of designs and reduce issues in manufacturing for organizations; it will also result in big savings in terms of manufacturing costs and shorter design and manufacturing cycles.

Sameer Kondejkar is product manager for DFMPro at Geometric Ltd.

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Geometric Ltd.