Solve chronic product and equipment failures

Use the power of big data analytics and gain full control to identify real root causes of chronic failures in products and foresee machine breakdowns. Reduce time and effort spent on manual analysis with our industry-proven high quality data analytics. Be up and running before you know it.


How can Nexplant Analytics deliver higher quality manufacturing?

  • React quickly

    Be aggressive in resolving quality issues in your manufacturing facility. Quickly understand the problem, from accurately categorizing failure patterns using machine learning, to various algorithms to help you find the root cause of failures, and cross validation that filters the specific effectiveness factor.

  • Get results fast

    Get the most out of your data with high performance parallel computing analytics and solutions. You can even use multi-dimensional search analytics to visualize manufacturing problems and find solutions.

  • Create high quality analytical reports seamlessly

    Create high quality, easy to read analytics reports regardless of an individual engineer’s experience. Field engineers can reduce up to 80% of their time spent on analytics work, letting them work more productively onsite.

"Samsung Nexplant is considered an important future tool for the smart factory strategy in defining the next-generation paradigm."

- IDG Tech Dossier 2018,

Big data analytics provide the answer to quality issues for semiconductors.

Gain insight. Prevent chronic product failures with big data analytics.


Take a closer Look

  • Map pattern analyzer

    Analyzes and classifies failure patterns based on clustering.

  • Root-cause analysis

    Analyzes big data to find the root cause of equipment failures and quality degradation.

  • Unmanned analyzer

    Automatically creates analytics reports in a significantly shorter amount of time using big data.

  • Key sensor classifier

    Classifies critical sensor profiles to detect root causes of quality degradations in real time.

  • Machine diagnosis

    Diagnoses machine anomalies based on the machine’s aging model.

  • Health prognosis

    Analyzes profile clustering and explores unique/similar patterns and motifs.

  • Profile pattern explorer

    Analyzes profile clustering and explores unique or similar patterns.


  • Platforms
    Linux Multi Node
  • Database
    Oracle, MySQL, PostgreSQL, Maria DB
  • Software Requirements
    JVM 1.7 or above, Hadoop 2.0, Scala


Read, download, and share


    IDG Report - Intelligent Factory Platforms are the Driving Force of Industry 4.0



    Nexplant Analytics at a glance



    Enhance manufacturing with unmanned big data analytics


Let's talk

Whether you’re looking for a specific business solution or just need some questions answered, we’re here to help.

Detect failures right away
After coming to office, engineer discovered an abnormal yield drop in the wafer being fabricated the previous day. So engineer analyzed the cause of yield loss by obtaining equipment and quality data amounting to 1 year of the same failure causing product and took appropriate measures.
Analyze problems and take the right course of action
After returning to the office, engineer noticed that the expense increased due to repair under warranty on certain qualified products indicating failures during a particular period. Based on rigorous analysis of the outgoing qualified products, engineer directed a selective delivery of 1st grade products to premium customers asking for high quality and instructed an additional quality inspection on 5th grade products.