Where Search & Discover Solutions Fit in Product Development
Dick Bourke posted on September 10, 2014 |

Many vendors offer software that helps product development teams find CAD models and related product documents within their corporate IT environments.  These "Search & Discover Solutions (SDS)" come in various shapes and sizes.  In this post I'll introduce a framework to help product development teams evaluate which systems to consider based on their needs.

 

Search and Discovery Solutions are used for 4 Primary Purposes
Different vendor search solutions target different stages of the product lifecycle:

  • Research on materials, technology and processes
  • Development of both new and on-going products
  • Operations including internal manufacturing and the enterprise global supply chain
  • Service addresses improving ways to maintain customer satisfaction

 

 

We can also categorize the vendor solutions based on how broad or focused a solution they offer and whether they cover geometry or just text:

  • General Purpose
  • Point Solution – text
  • Point Solution – geometric
  • Special Purpose

A vendor's products can fall into one or more classifications. Let's explore each in more detail.

 

General Purpose Search Tools
This classification encompasses a host of search engines that may have some or all of these characteristics: proprietary search engines, advanced semantic processing, predictive capabilities, Big Data tools and, in certain cases, steps toward Internet of Things (IoT) applications.  

Here are a few previously recognized "representative" vendors and their software tools in this classification.

  • Attivio – Active Intelligence Engine
  • BA Insight Agile Information Integration
  • Coveo – Advance Enterprise Search
  • Sinequa – Real-Time Big Data Search & Analytics Platform

 Add to this list:

  • Emcien –  cites IoT applications
  • Exalead's CloudView – if used for R&D, it also should be considered in the Special Purpose classification
  • IBM InfoSphere products – including Master Data Management

The role of ERP systems in the Operations and Service stages has been continually usurped by the CAE/PLM community for applications like BoM management. More encroachment is likely. Dassault's recent acquisition of Quintiq, a provider of supply chain planning and optimization software, is a case in point.

Another prime example is PTC's Service Lifecycle Management (with related applications) – a major component in PTC's highly visible Internet of Things strategy.   

 

Point Solutions – Text and Geometric
These tools address the data needs of engineering design departments and many downstream functions, such as manufacturing engineering, purchasing and the global supply chain.

The text-oriented solutions employ a range of semantic capabilities using inquiry input of key words and phrases with Boolean logic to discover needed data. The software may be open source, proprietary, or combinations. These tool sets usually include software connectors to extract information from related systems or files.  The ability to crack open CAD files is critical and some may be embedded in PLM systems.

I grouped text-oriented and geometric search together here. Several SDS tool vendors were identified earlier in "Getting the Benefits from an SDS - without a PLM system." They are 3DSemantix, Actify, Alcove9, Exalead, NorthRidge, Perception Software, ShapeSpace Ltd and Siemens.

Add to this list:

  • BCT – aClass, a classification system for use with Teamcenter
  • Convergence Data Services – Design for Retrieval  
  • Enfinio – Bingo!
  • iSeek – CADseek
  • PTC – PDMLink and PartsLink

The justification for these tools is commonly Design Reuse for departmental product development, perhaps boosted by procurement's yearnings for improved supply chain management.

Extending the initial efforts to achieve Design Reuse can then lead to gaining value with applications for the global supply chain, such as service applications – retrieving technical data for service technicians.

 

Special Purpose
Special purpose SDS tools can support all four stages of a product's lifecycle, but focus primarily on R&D based on advanced search capabilities. Two vendors in this space are:

  • IBM: Rational Engineering Lifecycle Manager (RELM) – based on a Linked Data approach for structured data, it is used for analysis of relationships discovered during design activities, such as among specifications. RELM is directed primarily for R&D in complex industries, with extensive hardware and software relationships. Though its prime value is in its use prior to product release, it can be applied in later Operations and Service stages.
  • IHS: IHS Goldfire – the Design Tool platform that combines semantic search capabilities with ideation tools, such as Root Cause Analysis and others to support R&D activity. This capability is provided with access to the broad IHS portfolio of product design services, with industry focus and on-line libraries (internal and external) to support development processes.

Significantly, some IHS offerings also fall into the Point Solution classification in the Operations and Services stages, for instance, MRO services.

Add to this list:

  • Conweaver – software and services to support R&D searching needs – with a focus on automotive and aerospace companies. The technology is a Linked Data approach.  Some applications have been implemented in the Operations and Service stages, e.g., BoM change management.
  • Exalead's CloudView – though presented as a general purpose tool, it is spotted in this Special Purpose classification when it's implemented for R&D.

 

Proper implementation is key, regardless of the software chosen
A key theme throughout my columns has been the relentless quest for high-quality data for timely decision-making.

While an SDS provides the framework for searching and discovering data, the quality of the retrieved data may be suspect – a common situation. So potential users need to critically assess the completeness and accuracy of the company's metadata, classification and attribute identification.

What's more, to gain the maximum benefit from an SDS, achieving high-quality data must be addressed when planning software evaluation, selection and implementation.

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