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This paper aims to conduct a detailed analysis of the industrial practices currently being used in the geothermal energy industry and to determine whether they are contributing to any limitations. A HAZOP-based upgradation model for improvement in existing industrial practices is proposed to ensure the removal of inefficient conventional practices. The HAZOP-based upgradation model examines the setbacks, identifies its causes and consequences and suggests improvement methods comprising of modern-day technology.

This paper proposed a HAZOP-based upgradation model for improvement in existing industrial practices. The proposed HAZOP model identifies the drawbacks brought on by conventional practices and suggests improvements.

The study reviewed the challenges geothermal power plants currently face due to conventional practices and suggested a total of 22 upgradation recommendations. From those, a total of 11 upgradation modules comprising modern digital technology and Industry 4.0 elements were proposed to improve the existing practices in the geothermal energy industry. Autonomous robots, augmented reality, machine learning and Internet of Things were identified as useful methods for the upgradation of the existing geothermal energy system.

If proposed recommendations are incorporated, the efficiency of geothermal energy generation will increase as cumulating setbacks will no longer degrade the work output.

The proposed recommendation by the study will make way for Industry 4.0 integration with the geothermal energy sector.

The paper uses a proposed HAZOP-based upgradation model to review issues in existing industrial practices of the geothermal energy sector and recommends solutions to overcome operability issues using Industry 4.0 technologies.