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QLECTOR LEAP
QLECTOR LEAP is a high-performance AI data-driven SaaS platform used to monitor and optimize manufacturing and business processes. Product is based on AI data driven methodology that was developed in cooperation with Josef Stefan Institute and Bloomberg. It uses an automated machine learning approach to build a digital twin of manufacturing processes, including all production lines and sites with dependencies between them incorporating Knowledge graph (data from ERP, MES) and forecast models on the level of each line, material and workers. It enables automated prediction updates based on real time data. It suggests the most optimal production plan and predicts a shortage of material, competencies, and late finalization of production orders with notification of responsible employees to address the cause of predicted events before they happen.
QLECTOR LEAP is addressing the following areas: Planning (AI&ML enhanced planning), Manufacturing (digital twin visualization) and Logistic (internal logistic - Labor/workforce planning & optimization). It brings transparency of shop floor reality to planners and empowers team coordinators to prepare for future events with maintaining and realization of production plans, schedules and KPIs leveraging AI enhanced planning approach. It offers innovative approach to common manufacturing challenges like master data consolidation in SAP and MES, change management introducing digital solutions, and lack of production transparency & flexibility to deal with supply chain volatility.
QLECTOR LEAP automatically builds and maintains a data-driven digital twin of the production facility using AI. It incorporates knowledge graphs and uses historical data from IT systems (SAP, MES, IIoT). Automatic optimization enables adjustment of parameters (e.g. cleaning/setup matrices, delivery dates, material availability...) and criteria that have a key impact on increasing productivity, capacity utilization, stock reductions, workforce optimization and customer satisfaction.
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