@rgemas MES is a Manufacturing Execution System developed by Arge Bilişim, providing data collection, traceability, measurement, analysis, and action cycle facilitation. It includes data collection hardware, MES software modules, and consulting services provided by Arge Bilişim.
It is a Lean Manufacturing tool that measures the effective utilization rate of machines. It is a module developed to improve the effective use of machines
It is a module capable of automatically measuring both planned and unplanned downtimes of machines along with their reasons.
Real-time Data Sharing Module for Collaboration Between Supply Chain Focused Company, Suppliers, and Customers.
A module that provides traceability for each product in terms of materials, labor, quality, and energy.
A planning module that includes pricing, scheduling, OEE measurement, efficiency measurement, and operations bank required for performance measurement, along with work sheet (routing) and target calculations.
The Time & Action module is used to schedule the timing of the order project, record the status of the plan's execution, and report it
The Time & Action module is used to schedule the timing of the order project, record the status of the plan's execution, and report it
@rgeSchedule has been developed to easily plan even the most complex production processes. With this module from @rgemas, you can create as many scheduling scenarios as you want and turn them into real schedules. It is the module where scheduling is performed.
Efficiency in assembly lines is a metric that measures the ratio of converted labor to expended labor, either for intermediate or final products. To improve efficiency, @rgemas measures efficiency in real-time
Lost time refers to the time wasted on the assembly line due to reasons originating from the factory rather than the operator. It is measured with the aim of improving efficiency and minimizing it.
Performance in assembly lines is a metric that provides the measure of labor that could have been converted into work if there were no lost times, relative to the labor expended. Performance is measured in real-time with @rgemas for the purpose of improvement
It is the module used for accurately measuring standard operation times.
It is the module used for universally accurate measurement, optimization, and standardization of standard operation times. With the MTM module, not only time analysis but also method analysis can be performed.
It is a sophisticated planning tool developed using data science with the aim of improving efficiency and quality. It establishes the best lines and is a module that prevents a dramatic decrease in line efficiency in case of disruptions.
The Quality Control module allows data entry during in-process and/or final quality inspections and initiates Nonconformance Reports (NCR) entry if there are any discrepancies.
It is the module where regulatory preventive activities are entered (also where Kaizens are entered), tracked, and managed.
This is the module where material quality control is performed, especially before entering bottleneck processes to prevent them from causing waste by occupying the process.
It is a type of quality control performed through randomly selected samples to prevent the continuation of systematic errors within the process. This is the module where this quality control is conducted
This is the module where 100% quality control is conducted at the end of the process. The aim is to prevent defective products from proceeding to the next process
It is the 100% quality control conducted at the end of production. It aims to prevent defective products from entering packaging. This is the module where this quality control is conducted
It is the quality control conducted after production and after the products are packaged and boxed, performed by opening the boxes through directed probabilistic sampling. It aims to prevent defective products from reaching the customer. This is the module where this quality control is conducted. Additionally, this module can also be used for raw material quality control.
These are modules used for activities such as reaching the source of inefficiency and/or quality issues, collecting data from the source, conducting analysis, and improvement for the purpose of improving efficiency and quality.
The machine breakdown tracking module aims to minimize downtime due to machine failures. Machine maintenance is the module where machine maintenance is planned and its implementation is monitored
It is the automatic sending of maintenance needs to technical service personnel by machines even before their scheduled maintenance time arrives. The purpose of predictive maintenance is to prevent a decrease in quality and minimize machine downtime to prevent a decrease in efficiency. It consists of software in which predictive maintenance is applied and IOT hardware modules used for data collection.
Giving a bonus' refers to sharing a portion of the profit above the target profit with employees if the target profit has been exceeded. Bonuses are used to incentivize and improve efficiency and quality. This is the module where bonuses are calculated and implemented.
It can be defined as a module that classifies each operator according to their abilities and provides equal wages for equal skill and work. The aim is to ensure fairness in employee wages. This is the module where wages are calculated and applied.
It is a module that allows for the quick creation of worksheet(routes) for rapid price calculation
It is a module used for personnel attendance control and payroll processing
Reports such as OEE, production quantity, efficiency, performance, quality, bonuses, etc. are obtained using web and mobile devices
It is a software service performed for integrating other software used by the company with @rgemas. Integration has been achieved with over 30 other ERP and/or Accounting software.