Building Your Smart Factory

The Factors of a Smart Factory

Smart factories are connected, forward-thinking, and efficient but all have specific things in common: Data-driven organizations that are farther down the path of smart manufacturing distinguish their operations by how they leverage the data that is available to them.

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What makes a factory a “smart” factory

Recent studies show a growing trend towards a wider range of use cases in operational efficiency. Looking beyond uptime and asset performance, companies that are farther down the path of digitalization empower plant personnel with analytics that deliver real-time insights allowing them to make decisions based on the output of those analytics.

1. Everyone makes analytics-driven decisions from relevant operational use cases

To take the next step towards optimizing process and asset performance, many data-driven organizations are already performing data analytics to some extent. This data typically ends up in several business applications serving specific operational purposes.

Data-driven organizations have a different approach towards their analytics. They define operational efficiency use cases based on desired business outcomes, rather than implementing a library of tools first. In doing so, they are putting data in the hands of many. This democratization of data helps manufacturing teams consistently work on operational efficiency and achieve goals:

  • Build

    actionable dashboards to monitor operational performance in real time.

  • Solve

    previously unresolved process performance issues.

  • Test

    and verify the validity of a hypothesis, so it can be addressed or ruled out.

  • Gain

    new insights from contextual information contained within 3rd party business applications.

  • Find

    new ways to improve plant performance using the insights that data provides.

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2. There is continuous improvement on operational performance with analytics-driven insights

Smart factories are led by visionary management teams. Process engineers have successfully overcome the well-known Double S curve of innovation. Best practices are being shared, and everyone is steering in the right direction. However, a smart factory is not the status quo; it is a continuous process! Smart manufacturers have a “start small, scale fast” mindset and enable vertical integration of analytics throughout the entire organization.

3. Employees use and share operational data across data silos

Instead of juggling spreadsheets and limiting themselves to the trend client of historians, data-driven organizations empower individual departments or teams with specific expertise to utilize analytics directly, without depending on data scientists. This “self-service” approach to industrial analytics enables smart factories to avoid the delays and costs of data science projects, achieve higher ROI and accelerate time-to-value and time-to-impact of projects.

FROM… centralized approaches to data analytics

TO… a federated approach where analytics are widely available

FROM… endless repeating of steps for data modeling

TO… constant enrichment of knowledge with useful insights

FROM… language gap between data scientists and subject matter experts

TO… utilizing full potential of subject matter experts


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