SEMANTIC NETWORK AND SEARCH IN VEHICLE ENGINEERING

Transcription

1 Martin Sturm, Sylke Rosenplaenter SEMANTIC NETWORK AND SEARCH IN VEHICLE ENGINEERING From Concept to Deployment Vehicle Design Operations & System Development GM Europe Engineering Adam Opel AG

2 1. Motivation: Issue and Business Impact 2. The Idea: From structures and folders to metadata and semantic network 3. Semantic Network and Search Engine: Best Practices 4. Deployment Strategy: Going fast vs. being perfect 5. Outlook: The Big Picture This presentation focuses on project deployment, reviews the current achievements and roadblocks and reports on project progress and implementation status. AGENDA. 2

3 Engineers spend significant time* searching for data complex IT landscape many isolated tools extracting data file attachments integrated text & tables verifying data duplicated, inconsistent & out of date data converting data various data formats valuable time for core engineering activities is lost *GM & Opel Surveys AGENDA. ISSUE 3

4 Where is the data I need? Is it the latest status? Are changes coming across? Who is the person to talk to? What are the data I need? What changes occurred? The Top 1 problem when talking to our global Engineering workforce* Results in long search time (up to weeks) Various systems with different interfaces and methodologies Links between information are often not obvious (e.g. Work Order to CAD part) Best Practices for Data Mining exist, but who knows them all? Kills productivity and efficiency *GM & Opel Surveys AGENDA. BUSINESS IMPACT 4

5 The speaker does not fit into the Door anymore. Seems the measurements were modified. Why that? What was the reason to do so? To whom do I have to talk? Who is the Design Engineer? What s the release status? AGENDA. BUSINESS IMPACT 5

6 The Idea: From structures and folders to metadata and semantic network As was situation Data Management through isolated IT tools and databases ( Data Silos ), relations between data gets lost, structure defined by application Data Management through hierarchical structures Folders on Shared Drives, Vehicle Assembly structures (CAD) Unmanaged Data attachments, Hard Disks or Flash Drives The Idea: Combining metadata and semantic network provides great improvement in information management and retrieval. AGENDA. QUICK RECAPITULATION 6

7 Imagine you would like to buy a book about business data management! Into which category might such a book fall into? Data Bases? Information Technology? Engineering? Business & Investing? Management & Leadership? AGENDA. FROM STRUCTURE TO CONTEXT 7

8 a) You visit a traditional bookshop b) You use an online bookshop: Search business data management Specialized books Information Technology Engineering Business & Investing You receive search results out of several categories: Why: use of keywords = context information Data Bases Data Management Knowledge Management Physics Management & Leadership Business & Finance Results: 1 4 of 30 Data Management Enterprise Content Management Database Technologies Lost Knowledge: How Companies can govern today s data chaos! And: you receive more context information supporting you in finding the right book: With a little luck & patience, you might find the type of book you were looking for! And: Customer ratings Customer tags Semantic search you can assist others to receive improved search results by adapting these mechanisms. AGENDA. FROM STRUCTURE TO CONTEXT 8

9 Why do we need semantic search & networks on top of context information? We need to transfer context information into knowledge! Source: (search Term prostep ) Semantic search & networks Investigate the data sources using a business specific set of rules Automatically establish relations between information pieces Search result supports Traveling the network Aggregating information AGENDA. TO SEMANTIC RELATIONS. 9

10 Changes Decisions Quality BOM System PDM System FINDING INFORMATION: AGENDA. EXAMPLE No central point of search Engineer has to know where to find data Different systems, different user interfaces Multiple data sources to get full picture No straightforward lookup of data 10

11 Changes Decisions Quality BOM System PDM System AGENDA. SEMANTIC SEARCH: APPROACH 11

12 The Idea: From structures and folders to metadata and semantic network The Challenge Engineers know and love folders Large organizations move slowly: Still unfinished journey to change Engineers' mind set regarding the use of metadata Convincing users to try something new and improve Data Management can be very time consuming AGENDA. AN UNFINISHED JOURNEY 12

13 Semantic Network and Search Engine: Best Practices Finding is not enough Create bridges between source applications and establish connections between search results Investigate the data sources using a business specific set of rules and establish automatic relations between information pieces Semantic Networks can be used to turn search results into knowledge. AGENDA. FINDING IS NOT ENOUGH 13

14 Semantic Network and Search Engine: Best Practices Less is more Target: Google like user interface Flexible and simple interface to support scalability of connected data sources AGENDA. LESS IS MORE 14

15 AGENDA. MODIFIED USER INTERFACE 15

16 Semantic Network and Search Engine: Best Practices Enhance search results through intelligent filters *.ppt is not a good filter => Program, Model Year, VPPS, Region,... Scalability to connect additional Data and Record Types from additional sources AGENDA. CLEVER FILTERS 16

17 Data Source Filter Geometrical Information Part List Information Engineering Work Orders Change Management Problem Resolutions Experts Standards Visual Issues Filter options are only available if search results meet that particular Data Source Filter criteria AGENDA. CLEVER FILTERS 17

18 Model Filter Product Line Division Body Style Model Year Filter options are only available if search results meet that particular Model Filter criteria AGENDA. CLEVER FILTERS 18

19 Semantic Network and Search Engine: Best Practices Balancing Quickness and Details Provide Quick Overview Cover pages as well as Detail Views for each Search Result before opening the actual Data Source Also, link Experts for each particular Search Result AGENDA. COVER PAGES AND DETAIL VIEWS 19

20 Semantic Network and Search Engine: Best Practices Balancing Quickness and Details To see the Relationship among Search Results, all Related Hits will be displayed including their filters, e.g. A Search Hit about a Change Decision will also display its related Work Order, related 3D part as well as all Experts for this context AGENDA. RELATED HITS 20

21 Identification of data sources: Best Practices Performance and Security Challenges Balance search results: Full text index (information overkill?!) vs. selected data / document types Handle the complex and evolving network: Identify, setup and maintain the right connections Meet ILM and security requirements: Check who can see what in which system Integrate new record types on (business) demand: Technical Specifications, Supplier Contractual Information, Test Reports, AGENDA. CONFLICT OF INTERESTS 21

22 Semantic Network and Search Engine: Best Practices Security Concept Suppliers SmartSearch Search results themselves only provide limited level of detail information Data Data Source Data Source Data Source Source Hyperlink Employees Search Index Hyperlinks to the original data source will control information accessibility AGENDA. SECURITY CONCEPT 22

23 Deployment Strategy: Going fast vs. being perfect Iterative approach Going small steps but being quick? Or going big steps but being slow? Data sources will be connected one by another Continuous improvements to create awareness and desires Develop business cases to plan next developments and allocate resources for release management AGENDA. ITERATIVE APPROACH 23

24 Deployment Strategy: Going fast vs. being perfect Implementation Schedule The idea: Smartsearch wins 1 st Global IT Innovation Challenge Global Rollout: Deployed to Enterprise Data Center for engineers SmartSearch 3.0 (Proposed): Integration of further record types and training content Prototype: Focus on usability, search results, 170+ users, most joined voluntarily Productive System: Testing load balancer, bandwidth and usage in productive use SmartSearch 2.0: Powertrain & Manufacturing Integration AGENDA. IMPLEMENTATION SCHEDULE 24

25 Connecting the Dots since 2007 In a heterogeneous IT landscape CONWEAVER provides a Linked Enterprise Data Layer between the different application systems. Visual Dynamic Data Linking is enabled by more than 350 Analytics & Information Access Modules. Our Linksphere Products (Terra & Luna) are in productive use at well known discrete manufacturing enterprises. CONWEAVER Linksphere Terra & Luna > License Seats of Linksphere Terra 20% Turnover p.a. Dr. Thomas Kamps thomas.kamps@conweaver.com CONWEAVER GmbH Friedensplatz Darmstadt CONWEAVER GmbH 2017 All rights reserved

26 SmartSearch Step 1 At the very beginning Sketch of data and system landscape Mockup for preproduction prototype Rapid Prototyping with data analysis and cleansing Created data and system landscape (by customer) Collected system screenshots and/or sample data Explained the business processes Analyzed provided information Created Mockup for preproduction Prototype GMIT Innovation Challenge 2011 Global Winner Detected (and corrected) incomplete and inaccurate records Identified degree of link up between 1% 400% Optimized links in the Graph Implemented Prototype CONWEAVER GmbH 2017 All rights reserved

27 SmartSearch Step 2 From Prototype to Productive System Agile Configuration several iterations GoLive with production system Evolution Further development (in house) Created Data Analysis Layer, Linksphere Terra Graph and Information Access & Visualization Layer UAT Handover to Operations Team Rollout Planning Version (Release) 1&2 configured by CONWEAVER Since the configuration of the 3rd version by GM (in house) CONWEAVER GmbH 2017 All rights reserved

28 If you build it, will they come? From global winner to real benefit Increasing numbers of users User Feedback With SmartSearch, you can got very good result and save your time. Thanks to creator. Amazing Tool First time using it and already smiling. Nicely done! Found a PN in minutes that I would have had to chase down for who knows how long with my old search method :) This system is a great step forward and I see a lot of potential. Thank you. 16 Data Sources Total User Hello, Your search is great! Finally we get something that integrates data from different sources. CONWEAVER GmbH 2017 All rights reserved

29 Linked Enterprise an accelerator of Digital Transformation 1 2 Today Tomorrow Further Use Cases* by extending the Linksphere Graph Linked Data for Smart Search Linked Data for Smart Search & further Use Cases Part Dashboard Weight Monitoring Maturity State Monitoring Support for Systems Engineering Configuration Lifecycle Management Support for Safety Forensic Engineers Mechatronics Fastening Technology Linked Data Layer *Examples of other CONWEAVER customers CONWEAVER GmbH 2017 All rights reserved

30 Deployment Strategy: Going fast vs. being perfect Communication Measures Interactive user feedback through feedback button: Work together with users to realize further enhancements Rollout and implementation through All People Meetings instead of formal communication only Collect feedback and encourage collaboration through internal social media AGENDA. COMMUNICATION 30

31 Deployment Strategy: Going fast vs. being perfect Also think about Which is the Gold Source for data? Who owns it? How does SmartSearch know about future / additional vehicles? Who will decide about adding them to SmartSearch? How does the concept fit into your data storage strategy? What about clean up processes? Stop thinking in Silos, think about context How can this shift in paradigm be communicated? AGENDA. GLOBAL APPROACH 31

32 Outlook: The Big Picture Future Topics Data Mining Role based Results Multilevel Security Confidential Programs SmartSearc h Big Data Machine Learning Modern User Interface User Interface Flexible Framework AGENDA. FUTURE TOPICS 32

33 The amount of data increases daily and we need to treat it very efficiently! Big solutions take time, but we cannot always wait! Please feel invited for a lively discussion! AGENDA. QUESTIONS 33

34 SUMMARY, OUTLOOK, An unfinished journey still AGENDA. QUESTIONS 34

35 Martin Sturm, Sylke Rosenplaenter THANK YOU 35