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End-to-end control system for production KPIs

The platform analyzes the performance of all production chains for each subsidiary, identifies deviations and displays the hierarchical structure of interconnected KPIs

Client

International metallurgical holding

Problem

The main problem

Tasks

Key objectives of the project

01.

Increasing the transparency of processes and dependencies of each production area, transparency of the causes of incidents.

02.

Organization of process continuity, risk minimization, reduction of downtime.

03.

Tracking the product's path from the input of raw materials to the output of finished goods, reducing defects.

04.

Diagnosis of the causes of incidents at the early stages of product production.

05.

Increased speed and efficiency of management decisions.

06.

Improving the quality of finished products.

Technologies

Client

HTML5, CSS3, Angular

Server

.NET 6, WebSockets

Data

PostgresPro, Hadoop, Spark, Parquet

Solution

Functionality

Analysis of KPIs of enterprises

Display of KPIs in the form of a hierarchy, relationships and graphs covering all stages of production, forecasting indicators, calculating the potential of production processes and technological parameters

Analysis of downtime and deviations

Automatic recording of equipment downtime, formation of measures to eliminate them; recording and display of deviations according to configurable indicators and control limits of metallurgical products

Defect control

Recording defects in outgoing products. Allows adding a description of the root causes of defects, generates reports and graphs, and transfers data to other systems.

Quality control

The system forms metal processing routes and transmits data to other analytical reporting systems. Allows you to record data on product quality according to custom parameters.

The system has created a unified platform of consolidated KPIs covering all production processes in each subsidiary.

Effects

by 18%

reduced the number of downtimes and incidents by 18% due to a reduction in the number of production and technological incidents

by 2.5 times

reduced the number of risks and mistakes in production and operational processes by 2.5 times

by 10 times

boosted the speed of KPI analysis and risk prevention by 10 times due to timely response to trends and deviations in indicators

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