Industries > Manufacturing

Artificial Intelligence in Manufacturing

Go beyond industry 4.0 with total visibility, predictive insights, and prescriptive actions

SparkCognition accelerates digital transformation for the world’s leading manufacturers in process, discrete, and batch operations. Our proven solutions for AI in manufacturing provide predictive maintenance, process optimization, and prescriptive actions that enable you to increase throughput, reduce costs, and save energy.

Read our eBook
demo

Proven Value

“SparkCognition’s ability to deliver reliable, AI-based predictive analytics helps the people working with and on the equipment to not only know what is happening, but more importantly, what is going to happen, and when. This is a game changer. Not only does this improve plant safety, but it increases productivity by reducing unplanned downtime.”

Doug Smith, CEO, Texmark Chemicals, Inc.

    Accelerate your digital transformation with AI in manufacturing

    Manufacturing requires you to adapt effectively to evolving conditions in your plant as low margins make the importance of production continuity more critical than ever. But much of the current factory tech stack is fragmented, dated, proprietary, siloed, or even all of the above.
    At the same time, the pandemic has only made it harder for legacy frontline systems to keep pace with widespread industry challenges like skilled labor shortages, regulatory compliance, supply-chain issues, and surging demand.
    Here’s the good news: no matter where you are on your digital journey today, you will become an industry 4.0 leader faster with SparkCognition’s easily operationalized, scalable, and high ROI products for AI in manufacturing.
    Our proven solutions provide end-to-end visibility and capture real-time insights to enable predictive maintenance and prescriptive actions that optimize throughput and reduce unnecessary strain on your resources. Realize the transformative power of artificial intelligence in manufacturing—by simply using the data you already have.

    Relieve the painful cost of downtime using artificial intelligence in manufacturing

    Downtime cost averages $532,000 per hour for large manufacturing companies, and human error causes 23% of unplanned downtime in manufacturing—more than twice the rate of other sectors.

    With real-time insights and predictive alerts on your machine health, SparkCognition’s patented solutions for AI in manufacturing help you avert costly micro-stoppages, slowdowns, and unscheduled downtime events before they happen. Adopting a data-driven, predictive maintenance approach enables cost-optimized equipment service when continually learning models determine an imminent failure is most likely: in time to avoid expensive downtime.

    Discover next-best-action recommendations with AI in manufacturing

    By the end of the decade, the growing skill-shortage problem could put nearly $500B of manufacturing GDP at risk. With experienced workers leaving the workforce and hiring markets getting more competitive every day, it’s time to rethink the way people and technology can work together optimally. 

    Prescriptive insights remove the guesswork for your staff by providing root cause analysis to prevent unnecessary repairs. SparkCognition allows you to codify SME manufacturing knowledge in various formats into one central source of truth, with next-best-action recommendations that become even more accurate and precise over time.

    Achieve sustainability goals through AI in manufacturing insights

    Manufacturers account for more than 30% of the nation’s total energy consumption. Yet, only 1 in 10 manufacturers are on track to achieve their sustainability goals.

    SparkCognition’s predictive analytics monitor energy, water, and other resource usages in real-time using AI-powered anomaly detection so you can reduce waste, save money, and scale your ability to improve sustainability across your operations. 

    Our AI in manufacturing solutions alert you to wasteful electricity, water, or other resource usages, allowing you to analyze past anomalies and alerts to find root causes and patterns in resource usage, correlate usage practices with production and/or quality issues, and extend your asset’s usable life while maximizing throughput through optimization actions.

    Case studies: AI in manufacturing companies improving operational efficiency and sustainability

    How to become an industry 4.0 leader using AI-enabled predictive maintenance

    Gain end-to-end visibility, increase operational efficiency and throughput, and use AI-powered predictive maintenance and process optimization to achieve sustainability and cost savings. Read our industry sheet

    Driving sustainability for a Top 50 beverage manufacturer

    See how our AI solutions delivered deep visibility and predictive insights to reduce costs for a top 50 beverage manufacturer’s most significant resources: water and energy. Read our use case

    Optimizing production via AI-powered transparency

    Learn how we improved plant efficiency for a global beverage company by delivering quantified, granular insight into current and future performance issues. Read our case study

      Unlock the power of AI in manufacturing

      Leveraging deep manufacturing industry knowledge, SparkCognition unlocks the power of AI in manufacturing at scale so you can leap ahead of your competitors held back by fragmented and dated legacy systems.

      A fortune 50 beverage manufacturer saw production efficiency increase by up to 5%, averting nearly $1M in maintenance costs through a single plant deployment.

      Our AI-native tech stack supports rapid deployment with a fit-for-purpose modular approach that enables you to select a product configuration that delivers superior ROI vs. existing MES, APM, and PdM offerings in today’s industrial automation ecosystem. With proven solutions for AI in manufacturing, SparkCognition helps data-rich, but insight-poor operators find actionable insights to accelerate their digital transformation.
      Schedule an exploratory call
      demo