AI at work
Production
Reduce downtime?
Improve production planning?
Identify performance losses?
Eliminate quality defects?
Artificial intelligence has the potential to completely transform the manufacturing industry.
Large manufacturing companies can benefit from this technology, but many small businesses also have the opportunity to create new value.
Discover Sapiens Analytics' on-demand artificial intelligence solutions.
Quality
Control
New AI-powered Sapiens Analytics solutions can detect quality issues that might elude traditional checks and improve the quality process by identifying anomalies in operating conditions. Quality control engineers can thus predict potential quality issues and correct underlying production conditions before serious problems arise.
Production Planning
Manufacturing companies capable of accurately forecasting and planning production are in a much better position to optimise their resources, leading to higher profits and greater customer satisfaction. When AI/ML is applied to production process data, forecasting is no longer merely a matter of guesswork; manufacturers can rely on more precise and reliable models.
Potential benefits include increased productivity, reduced costs, improved quality, and minimised downtime.
Monitoring
Systems
Through predictive maintenance, you can anticipate potential failures in industrial systems that could compromise the entire production process.
By determining the likelihood of future machinery breakdowns, manufacturers can schedule preventive maintenance and repairs in advance. AI-enabled predictive maintenance allows factories to boost productivity while simultaneously reducing repair costs.
Improving production
Monitoring the production process and the facilities.
Creative Design
In generative design, machine learning algorithms are used to mimic the design process employed by engineers. Using this technique, manufacturers can rapidly produce hundreds of design options for a single product.
With artificial intelligence, software can generate multiple iterations of a product design that improve upon the original. Sapiens Analytics software requires inputs from designers, such as:
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Basic components
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Dimensions and mass
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Manufacturing techniques
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Financial and other resource constraints
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The algorithm can generate a matrix of potential layouts based on these inputs.
Process Improvement
Organisations can achieve sustainable production levels by optimising processes using AI-based software.
Track key KPIs such as OEE, production rate, or scrap rate.
Predict accurate delivery dates and meet deadlines.
Resolve production bottlenecks.
Robotic Automation
Factory operators rely on their knowledge and intuition to manually adjust equipment settings while monitoring various indicators across multiple screens.
Sapiens Analytics' AI solutions automate repetitive tasks, eliminate or drastically reduce human error, and refocus human workers on more profitable areas of the business.
Commonly known as "industrial robots," robotics in manufacturing enables the automation of repetitive tasks, the elimination or reduction of human error, and the reallocation of human labour to higher-value activities.
Robots have a wide range of potential applications in manufacturing plants. Computer vision is integrated into various industrial robots, enabling them to navigate chaotic environments with precision.
Performance improvement
A digital twin can be used to track and examine the production cycle, identifying potential quality issues or areas where product performance falls short of expectations.
Process analysis
Edge analytics utilises datasets collected from machine sensors to provide rapid, decentralised insights.
Predictive maintenance
Maintenance operations are improved through proactive monitoring of machinery efficiency, real-time performance analysis, and the anticipation of critical issues such as time-to-failure.
Go to the Predictive Maintenance page >>
Quality control
Maintaining a desired level of quality in a service or product is known as quality assurance. Using computer vision technology, AI systems can detect deviations from the norm, as most defects are immediately apparent.
Raw material and component procurement management
AI-based software can forecast raw material prices and predict potential supply chain disruptions more accurately than humans.
Predictive capabilities improve over time thanks to machine learning.
Insights
