This module organizes planned maintenance activities while also detecting failure possibilities in advance with predictive maintenance algorithms.
This module analyzes the performance of devices on the production line and their past failure records to predict maintenance needs, minimizing operational interruptions and increasing production efficiency. It plays a critical role in minimizing unplanned downtime, especially in complex and costly production lines.
It measures efficiency, evaluates resource usage and offers improvement strategies by analyzing performance data on the production line. The aim is to reduce costs and increase productivity by optimizing production processes.
Features
Production Data Collection
Data received from machines and systems in the production line are recorded instantly in the system. Parameters such as working time, production output, fault and pause times are collected for detailed analysis.
Productivity Analysis
Machine operation rate, labor usage, cycle time and material consumption are analyzed through the collected data. Bottlenecks are identified by measuring the effective use of production capacity.
Resource Usage Reports
The usage rates of resources such as energy, water, air and gas are reported in detail. Waste is detected and which production units are inefficient in resource consumption are determined.
Performance Improvement Suggestions
In line with the analysis results obtained, process improvement, automation and resource management strategies are developed and presented to management to increase operational efficiency.
It enables the analysis of data obtained during quality control processes and detailed reporting of nonconformities. The aim is to ensure continuous improvement by detecting quality problems early.
Features
Recording of Quality Control Results
The results of all quality tests performed during the production process are securely recorded in the system. This creates a consistent data infrastructure for retrospective monitoring and auditing processes.
Non-Conformity Detection and Reporting
Defective products or non-parameter results identified in quality tests are analyzed by the system and non-conformity reports are created. Error sources are detected with root cause analysis.
Trend and Deviation Analysis
Deviations that occur in quality tests over time are analyzed graphically. Quality assurance strategies are planned by determining fluctuations in quality performance.
Quality Improvement Suggestions
Corrective and preventive action suggestions to increase product quality are developed and presented to management in line with the analyzed quality data.
It enables monitoring of energy, water and other resources consumed in production processes, performing cost analyses and developing savings strategies. The aim is to support sustainable production and minimize costs.
Features
Energy Consumption Data Collection
Energy consumption data from machines on the production line are automatically recorded in the system. This data forms the basis for detailed analysis on an hourly or shift basis.
Resource Consumption Reports
The amounts of energy, water and other auxiliary resources used at each stage of the production process are analyzed and consumption trends are reported. In this way, processes that cause high resource usage are identified.
Cost and Savings Analysis
Costs related to energy and resource usage are analyzed in detail. Losses due to excessive consumption are determined and areas where savings can be made are clarified.
Efficiency Improvement Reports
In line with the data collected, process improvement and automation suggestions are developed to increase energy and resource efficiency. These reports provide strategic decision support to management.
It aims to optimize workforce management by analyzing in detail the performance, duty times and shift-based productivity of operators working on the production line.
Features
Workforce Data Collection
Operators' duty hours, time spent on duty, production target achievement rates and absenteeism information are recorded in the system. This data forms the basis of individual performance monitoring.
Performance Reports
Based on the data collected, each employee's level of contribution to production and their success in completing their tasks are analyzed. The output they provide to production units is reported along with on-time delivery rates.
Training and Development Needs
For low-performing operators, the system identifies personalized development plans and training needs. This allows competency-based task assignment.
Shift Efficiency Analysis
The productivity rates of shifts are analyzed by comparing the production performance in different shifts. This analysis allows for more efficient workforce distribution and shift planning.
It ensures that data obtained from processes such as production, quality and energy are automatically reported according to certain criteria and that relevant people are notified on time.
Features
Periodic Report Planning
The system automatically generates reports according to user-defined periods (daily, weekly, monthly). These reports include data such as production volume, quality control results or resource usage.
Critical Threshold Notifications
If defined limit values (e.g. production capacity exceedances, energy consumption limits) are exceeded, the system automatically sends a warning to the relevant manager and responsible persons, enabling rapid intervention.
Customized Reports
Users can create reports specific to their needs using various filtering criteria such as date range, product group, equipment type, etc. This flexibility allows different departments to perform analysis according to their own dynamics.
Report Archiving
All generated reports are stored in the system, allowing for historical data analysis. Archived reports allow for easy tracking of performance trends and improvement opportunities.
Türkçe
English