Harnessing your systems, data and supply chain information to review, plan and predict.
Time series data has limited potential. Cimlogic work with clients to add context and subject matter expertise and analysis in the digital world. Through operational excellence, based on contextualised data and information, we deliver value right back to the physical world, throughout the supply chain. That’s where the real business value is unearthed.
So, what does this mean to manufacturers? In short, contextualised data on which to base current decisions and future forecasts. Answering questions such as ‘What do customers want, when do they want it and where do they want it delivered?’
Today, leading manufacturers are reaping the benefits of AI, machine learning and other technologies to gain greater insight across the supply chain, contextualising their data to support rapid, accurate decision-making and forecasting. It’s the logical next step from manufacturing analytics; collect and manipulate large amounts of data and then use those insights to take specific actions or set up automatic business processes to respond to in real time.
Cimlogic can support you in implementing technologies such as machine learning and AI to achieve predictive manufacturing across your supply chain:
- Predictive operative/non-operative time to improve planning and demand accuracy
- ‘Time to target’ prediction to optimise operations
- Root cause analysis of process losses
- Optimal process setting by batch/run to reduce losses
- Predictive alerting to prevent loss
- Real-time process corrections
- Reduced variability, rework and rejects
- Giveaway and weight reject management
- Predictive and optimised yield
- Positive pre-release prior to quality inspection
Predictive Inventory and Demand
- WIP optimisation
- Material movement optimisation
- Material availability
- Zero touch performance monitoring
- Insight acceleration
- Process anomaly insight
- Navigation assistant
- ‘Next batch’ performance outlook
- Failure prediction
- Predictive maintenance planning
- Optimised energy consumption
What does AI and machine learning mean for manufacturers?
AI is not magic, it’s maths!
AI can transform areas such as maintenance, performance, inventory, quality, and sustainability, by offering real-time predictions across processes, empowering timely corrective actions. In short, the insight that an army of intelligent humans could provide, in a fraction of the time! Machines are ‘trained’ to respond to events both internally and externally (even anticipating events), autonomously. They can detect unexpected (and expected) events, such as machine outage, supply shortfall, delivery issues, and react and work around the problem. The more data available (and over time), the more the machine can learn, make decisions, and start to prescribe.
- Predictive Maintenance
- Predictive Performance
- Predictive Inventory and Demand
- Predictive Worker
- Predictive Quality
- Predictive Sustainability
What business goals can predictive manufacturing help achieve?
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