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Predictive Engineering Analytics Series - Part 3

Track: Business Process Connection

Session Number: 170119
Date: Thu, May 11th, 2017
Time: 10:45 AM - 11:15 AM
Room: 111-112

Description:

Be sure to add Predictive Engineering Analytics Series Parts 1-6 to your agenda to make the most of the full day series.

Leveraging PLM Analytics for Product Performance
Product quality and reliability being one of the most critical considerations towards establishing product brand, no wonder companies invest significant spend towards ensuring the new product development imbibes a rigorous quality assurance program. Product performance needs to be closely monitored not just during the First Article Inspection or the initial batch, but quite a few ongoing production runs to infer failure modes from the early symptoms of product performance. Quality executives struggle with control charts, FMEA, six sigma analyses, while the design function strives to strike a fine balance on product cost with product specifications following tight tolerances on form, fit or function. It becomes imperative to analyze the data more closely – during manufacturing, service & support to strike this optimal balance.

How does one improve the predictability of product failures so timely corrective actions can arrest the catastrophic failure of the product, warranting total replacement? How can the periodic servicing operations be accurately tuned, to become timely and effective so as to avoid costly routines uncalled for in a seemingly healthy operating environment? What critical parameters need to be monitored closely to provide the early indications of an impending failure amongst several contributing factors?

How may one leverage PLM to manage the data along the complete lifecycle to provide the hints and pin point trouble candidates for early resolution and corrective action? The paper takes into account a few industry examples of early product failures encountered and delineates an approach linking several enterprise systems including PLM with effective product analytics devised as part of an effective NPD process

Sub-Categorization: Predictive Engineering Analytics
Session Type: Interactive Lecture

Related Industry: Aerospace & Defense, Automotive & Transportation, Consumer Products and Retail, Electronics and Semiconductor, Energy and Utilities, Industrial Machinery & Heavy Equipment, Life Sciences, Marine, Medical Devices & Pharmaceuticals, Other, All Industries
Learning Objectives: 1. How may one leverage PLM to manage the data along the complete lifecycle to provide the hints and pin point trouble candidates for early resolution and corrective action?
2. How does one improve the predictability of product failures so timely corrective actions can arrest the catastrophic failure of the product, warranting total replacement?
3. What are the Industry examples
Applicable Software: Teamcenter Quality Issue Management with CAPA, Teamcenter Reporting & Analytics, Teamcenter Service Lifecycle Management
Pre-requisites: General awareness of NPD capabilities offered by PLM
Sub-Categorization: Predictive Engineering Analytics
Session Type: Interactive Lecture

Related Industry: Aerospace & Defense, Automotive & Transportation, Consumer Products and Retail, Electronics and Semiconductor, Energy and Utilities, Industrial Machinery & Heavy Equipment, Life Sciences, Marine, Medical Devices & Pharmaceuticals, Other, All Industries
Learning Objectives: 1. How may one leverage PLM to manage the data along the complete lifecycle to provide the hints and pin point trouble candidates for early resolution and corrective action?
2. How does one improve the predictability of product failures so timely corrective actions can arrest the catastrophic failure of the product, warranting total replacement?
3. What are the Industry examples
Applicable Software: Teamcenter Quality Issue Management with CAPA, Teamcenter Reporting & Analytics, Teamcenter Service Lifecycle Management
Pre-requisites: General awareness of NPD capabilities offered by PLM