PDM --- How the Technology has envoled.------GOOD Material

How the Technology has Evolved
A Short Review
Taken from the Hewlett-Packard's document entitled "Understanding the Fundamental Technology and Business Concepts - Product Data Management The Environment for Today's Product DevelOPMent."  
  
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PDM systems were originally of the 'home-grown' variety. Many large corporations that were leaders in the application of computers to engineering, found their progress being seriously hampered by paper-based systems in the early 1980s. With no commercial systems available they were forced to develop solutions internally. Some were successful, others not.  
  
In the late 1980s several software companies, realizing the need and the associated business opportunity, introduced the first generation commercial PDM systems. Some of the newer vendors tended to offer PDM independently of other engineering software applications. However, most were already in the business of selling CAD/CAM/CAE software. They had seen their customers' data management problems and were well positioned to add PDM to their product line. Typically, they focused on selling their PDM systems to their existing customers and often used them to leverage sales of CAD/CAM/CAE.  
  
The basis for these PDM systems is the database engine - typically a commercially available Relational Database Management System (RDBMS). The database is used to keep records of parts and related files. The PDM system then provides the security, file storage, revision control, classification, notification and application integration in addition to facilitating the engineering process. The latter capability is rapidly evolving.  
  
A common theme amongst early PDM systems was a focus on the 'downstream' engineering process, namely capturing and managing the engineering product data from the point of initial release, to manufacturing and then through to product obsolescence. There were several reasons for this.  
  
Manufacturing departments had already been targeted for cost reductions and overall process improvements. Companies were actively employing JIT (Just-in-Time), TQC (total Quality Control) and ABC (Activity-Based-Costing). As far as engineering product data was involved, there were two key areas of concern: managing the initial release of the data to manufacturing and managing the engineering change order process initiated by manufacturing.  
  
So the early PDM systems were developed with a manufacturing focus. Key engineering process capabilities of these systems were Release Management and Change Management.  
  
Since the release and change processes could be fairly well defined (in terms of the steps the designs had to go through) the PDM systems were developed to enforce very strict engineering procedures. This worked for the manufacturing focus.  
  
In recent years, however, the other areas of the product life cycle have been targeted for improvement. Time-to-market is a major issue for most companies. Time-to-market can be reduced by shortening the time from initial concept to the first shipments of a product. Concurrent engineering is a related issue. It involves executing several engineering tasks in parallel instead of serially. Most engineering tasks are executed between initial concept and release to manufacturing.  
  
In response to these new areas of focus, second-generation PDM systems support the entire product life cycle - from initial concept to product obsolescence. They can support concurrent engineering practices in both a flexible, conceptual design phase as well as in the better defined engineering change process. They can also manage several levels of release of a design - not only the final release to manufacturing but the intermediate releases that take place at company-defined checkpoints such as breadboard, lab prototype, production prototype, etc.  
  
Some systems go beyond managing engineering procedures and manage the engineering process (or workflow) as well. Now users can share up-to-date, pre-released engineering data and the flow of that data can be intelligently, yet flexibly, controlled according to a set of rules.