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Cut scrap and defects with the data you already have
Since 2017 we have used machine learning to find the process settings that reduce scrap and defects at foundries, tyre makers, wheel plants, and automotive OEMs.
The tier-1 plant also lowered its production energy use and saves about $100k a month. Other results include a 55% sustained defect reduction at an engine-block manufacturer and 29% less scrap at an alloy-wheel manufacturer. A tyre manufacturer also improved six quality metrics by 39% on average. Read the case studies
Prescribe
Prescribe learns how each process setting affects quality from your plant's own process and quality data, and prescribes the settings that reduce scrap and defects. Operators, engineers, and plant managers each see the prescriptions for the parameters that matter most in their part of the process. At the tier-1 foundry, Prescribe models about 1,000 parameters across the plant and updates its prescriptions every five minutes. It runs on DataProphet Connect.
Read the tier-1 case study →What we do for manufacturers
Data readiness assessment
In four to eight weeks, for a fixed fee, we map your data, find the opportunities worth pursuing, and give you a delivery plan.
Process optimisation
Prescribe finds the parameters that drive quality in complex processes and prescribes the settings that improve it.
Process control
A live view of how well each line follows its own control plan, down to the machine and the operator.
Unified production data
We link the process and material conditions behind each unit produced, giving a plant-wide view and the foundation for analytics.
Data quality and governance
Checks that keep the data your decisions rely on complete and correct.
Business analysis and data science
Former manufacturing engineers and data scientists who work with your team to make each improvement measurable and repeatable.
DataProphet Connect
DataProphet Connect is a fully managed industrial data platform, in production since 2020 and now used by hundreds of plants. Connect collects data from PLCs, historians, and databases through secure gateways, and gives operators, engineers, and managers dashboards, alarms, and machine learning models in one place. Connect is also available on its own, and machine builders run it under their own brand: since 2020 it has been the platform behind Norican Group's Monitizer.
Explore the platformBack-office work for manufacturers
Manufacturers also hire our AI engineering team for work outside the production process. For a leading SA brewer we built workflows and machine learning for accounts receivable and accounts payable. We build demand forecasts that set how much to produce and what to order, so that a plant meets demand with less finished product wasted and less cash tied up in stock. We also build systems that read engineering drawings and draft bills of materials, and group data pipelines that replace hand-compiled executive reports with certified, automated ones.
Finance and back office on the AI engineering page →Demand forecasting on the AI engineering page →In our clients' words
“We struggled with unexplained defective products shipped, which impacted our input cost, revenue, and ESG initiatives. DataProphet sustainably improved production performance from initial engine block processing to shot blasting.”
“We know foundries and how they work; DataProphet really knows AI. Together, we can bring practical AI applications into foundries faster, applications that will have a tangible impact for our customers now, not in a distant future. In DataProphet, we have found a partner who shares our pragmatic attitude and our passion for helping foundries work ever more productively and resource-efficiently.”
