Manufacturing

From predictive maintenance to line scheduling – there is unprecedented power in applying Analytics to manufacturing and production, no matter if it is a discrete or by process type of industry.

Industry 4.0 and the use
of Data and Analytics

The manufacturing process has been exceptionally transformed for the past 25 years due to increment use of sensors, IoT and analytics. Operational challenges have only grown deeper and the trade-offs related to productivity vs. costs vs. availability vs. service levels are getting harder and harder to balance.

Production planning can be done in different time horizons (short, mid and long-term), each one having their own requirements and objectives. For short and mid-term planning, prescriptive models can be applied to calculate optimal scenarios and help the decision makers define what is the best production mix for each production line.

Optimization models simultaneously evaluate the production process main attributes, raw material availability, line efficiency in each site, lot sizes, minimal runs, scheduled maintenance stops and all other relevant factors, to create an accurate and feasible recommendation.

Master Production Planning

Production Scheduling

Materials Resource Planning

Inbound Logistics Planning & Execution

Inbound Inventory Mgmt

Production Control & Execution

For the shortest-term plan, heuristics and metaheuristics methods are able to recommend the best production schedule for the optimal mix, focusing on minimizing the total time spent with line setups and cleans.

This productivity goal is intimately related to the new remote control rooms, where detailed real-time visibility and large-scale use of sensors are mitigating risks for plant workers while also isolating the decision makers from the heat of plant floor operational pressures, making space for the decisions to be based on cost and service level.

performance

Performance DHAUZ has the right solutions for Data Driven Manufacturing

DHAUZ has extensive experience in developing and implementing tailored solutions for line scheduling and MPS, an also in designing and leading the governance for cloud command centers and IoT. Here are some of our main offerings for Analytics and Industry 4.0

Process-Mining & Operational Bottlenecks

We have developed process-mining tools to help us identify the actual steps taken during production and operations so that we can map where the real bottlenecks are and which action to take to improve quality and efficiency.

Line Scheduling

With a tailor-made approach for line scheduling, we can accurately model the important characteristics of all production lines. We combine predictive and prescriptive analytics with simulation to deliver better and more comprehensive models of each manufacturing site.

Quality Control & Visual Analytics

AI most advanced methods, NLP and video analytics applied to help build intelligent quality inspections, CO2 emissions reduction, production cost optimization and fostering innovation through kaizen models powered by advanced analytics.

Predictive Asset Maintenance

The use of state of the art prediction models to enable early defect identification and potential maintenance need. We have an exclusive PAM solution that contains a library of deployed predictive and AI models, a data processing layer and an execution interface that gets industrial maintenance to a much more pro-active and efficient level.

Energy Efficiency

Solution development based on energy consumption optimization models that includes plant equipment requirements, energy cost rates, energy acquisition contracts and offers, gas emission reduction interest and incentives, minimized costs and ESG goals.