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The New Age Physical

Engineering Experiences, Not Just Products

  1. Home
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  3. Engineering Analytics

Engineering Analytics

LTTS' engineering analytics team takes a systematic approach to unlocking value:

  •  What data to collect
  •  How much data to collect and at what intervals
  •  How to transmit the data
  •  Where to analyze it and when
  •  Building the right analytical models to derive insights,
  •  And finally, delivering the right insights to the right people at the right time

 

We have helped global conglomerates make new product design decisions, dramatically reduce or even eliminate machine downtime, revolutionize service support, enhance workforce productivity and engineer new revenue models.

What We Do

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Consulting Services_90x90_color-01.pngConsulting Services

  • Study of existing systems, processes, and infrastructure
  • Identification of data sources and storage means
  • Definition of engineering problems along with business implications
  • IoT and connectivity consultancy
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Data Engineering_90x90_color-02.pngData Engineering

  • Data preparation
  • Data mining – cleaning, structuring & storing
  • Definition of KPI
  • Detailed approach to application of statistical/analytical modelling
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Analytics Modelling_90x90_color-03.pngAnalytics Modelling

  • Creating an analytical model
  • Refining the model using live data sets to improve accuracy
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Validation & Testing_90x90_color-04.pngValidation & Testing

  • Deployment of model on live system to verify model accuracy
  • Evaluate, monitor and fine-tune model to align with expected outcomes
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Deployment & Business Operations  _90x90_color-05.pngDeployment & Business Operations

  • Productize data model
  • Derive business insights for product R&D, operations, service support and new revenue models

What Stands Us Apart

  • Strong ecosystem of academia and partners. Technology partnership with companies such as Splunk, Tableau, SAS, IBM, Microsoft, and Amazon.
  • Vendor neutral system integrator with experience in multiple platforms:
    • Big data platforms such as Hadoop, Spark, Kafka, Splunk, and non-Hadoop systems
    • NoSQL data stores such as Mongo DB and Hbase
    • Analytics tools like R, SAS, Python, and SPSS
    • Visualization tools such as Tableau, QlikView, and Spotfire
  • Readily deployable data models that can enable deep insights in areas such as demand forecasting, condition-based maintenance and warranty analytics.

 

Success Stories – Turning Data to Gold

Turning Data to Gold_inforgraphic_0.png

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  • Engineering the change
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    • Semiconductors
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    • Oil & Gas
    • Software Products
  • Services
    • Products
      • CAE & CFD
      • CAx Automation
      • Cloud Engineering
      • DevOps
      • Embedded Systems
      • Engineering Analytics
      • Immersive Experiences
      • Integrated Design, Validation & Testing
      • Security Monitoring
      • Security Solutions
      • Security Services
      • Sustenance
      • Testing
      • Wearables Engineering
      • Voice Innovations
      • VLSI
      • Testing & Validation
    • Manufacturing
      • PLM on Cloud
      • aspenONE on Cloud
      • Plant Design & Engineering
      • Digital Factory & Simulations
      • Line Expansion & Transfer
      • Frugal Product Design
      • Asset Care
      • Accelerated Operations
      • Manufacturing Automation
      • Agile Supply Chain
      • Content Engineering
    • Operations
      • Connected Service Support
      • Integrated Content Management
      • Intelligent Building Management
      • Sourcing & Procurement
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      • Industry 4.0
      • Product Strategy
      • Security
      • Smart Factory
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