The Covid-19 pandemic has changed the industrial management system, including the regulation of labor. Most of the work in the industry cannot be done through work from home, but must still be in production units. In a number of cases, clusters of COVD 19 were found in the industry, forcing the industry to have to lock down. The problem of the lack of a model for controlling the spread of COVID 19 in the manufacturing industry is the basis for this research. The model designed in this study is also expected to be relevant in the new normal era for the manufacturing industry. The modeling and application of COVID-19 control research in the manufacturing industry is carried out through four stages, namely identification and characterization of work patterns, model design and validation, model implementation and verification, and model comparison testing. At the stage of identification and characterization of work patterns using the methods as guided by the International Labor Organization. The design phase and model validation used the Epidemic Mathematics approach and the Shewhart Control Chart. The application of the model in the industry is in accordance with the guidelines for working in a factory during the COVID-19 Pandemic according to the World Health Organization. The comparative test of the model will be processed using the diversity test. The data used is collected from the company in the form of simple tracing monitoring data for workers before entering the work area and shortly before leaving the work area, COVID 19 test data if any, employee health data, and other data if relevant to support this research. The data obtained is used for model design, both the employee health control model and the COVID-19 distribution model in the work area. The model is made with a scope that is limited only to the industrial work environment, not including outside facilities. Contamination to employees may occur when employees return home or are outside the factory. The model also does not adopt the presence of employees who are being treated for COVID-19 healing in a healing facility. In the Shewhart Control Chart model, it is hoped that a control limit can be obtained that can be used to monitor fluctuations in employee health, the diagram will be designed for daily monitoring of workers. Out-of-control data becomes a warning to carry out a reliability test (Capability) and to trace sources of contamination obtained by employees.
Copyrights © 2023