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Industrial Process Optimisation

We help manufacturers solve complex problems such as hidden bottlenecks and unprofitable production lines.

Advanced analytics for industrial process optimisation

By using analytics systematically, manufacturers may greatly unlock savings. Analytics give process engineers greater visibility into every process, which they can therefore steer more effectively. Moreover, analytics support better management by helping operators to spot when a process deviates from defined key performance indicators (KPIs). This visibility allows them to detect movements and take corrective actions much more quickly. Furthermore, analytics aid in uncovering hidden process restrictions that can often be resolved with small capex investments. Besides making employees more efficient, they can help to remove critical human bottlenecks, freeing up time and resources that can be directed to additional improvements in plants.

We offer three applications of advanced analytics that together are powerful tools for maximizing the physical and financial performance of manufacturers’ assets and often-complex supply chains.

 

Predictive Maintenance

Maximize opening time of critical assets, leveraging big data to predict and anticipate failures.

Predictive maintenance analyzes the historical performance data of machines to forecast when one is likely to fail, limit the time it is out of service, and identify the root cause of the problem.

 

Yield & Throughput

Maximize yield/throughput of individual assets, by optimising working parameters based on big data analysis.

Yield-energy-throughput (YET) analytics can be used to ensure that those individual machines are as efficient as possible when they are operating, helping to increase their yields and throughput and reduce the amount of energy they consume.

 

Supply Chain Dynamic Optimisation with Advanced Modeling

Dynamically define optimal setup point (eg, sales mix, value allocation, procurement mix).

Profit-per-hour (PPH) maximization analytics, meanwhile, scrutinizes the thousands of parameters and conditions that have an impact on the total profitability of an integrated supply chain (from raw materials purchasing to final sales), providing intelligence on how best to capitalize on given conditions.

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