Every asset manager, no matter the scale of the corporate, faces similar tasks: optimize maintenance planning, improve the reliability of assets or equipment, and optimize workflows to enhance quality and productivity. In a recent IBM Institute for Business Value study of chief supply chain officers, nearly half of respondents said they’ve adopted latest technologies in response to challenges.
With the ability of generative artificial intelligence (AI) foundation models combined with traditional AI, even greater assistance is on the horizon to exert greater control over complex asset environments. These base models are based on large language models and are trained on large amounts of unstructured and external data. You can generate answers equivalent to text and pictures while interpreting and manipulating existing data.
Let's explore 6 ways generative AI can optimize your organization's asset management operations, including field service, maintenance and compliance. Generative AI can:
1. Create work instructions
Field service technicians, maintenance planners and field service managers make up your frontline team. You need work plans and work instructions for system failures and repairs. Using a hybrid AI or machine learning (ML) model, you’ll be able to train it on corporate and published data, including newly acquired assets and locations.
Through interactive dialogue, it will probably create visual evaluation and deliver content to your team immediately. Access to this information can increase field service uptime by 10-30% and increase first-time repair rates by 20%, leading to cost savings, improved worker productivity and increased customer satisfaction.
2. Increase the efficiency of labor order scheduling
Work orders drive activity and depend on work plans and work schedules to authorize and allocate resources to finish tasks. The process itself, while straightforward, is time-consuming, so it's no surprise that there are sometimes delays in work order scheduling.
Generative AI strengthens base models by training them with all of the essential instructions, parts, tools and skills for a particular facility or class, enabling the creation of labor plans. This improves the talents of your employees and results in a 10-20% increase in planning skills. Additionally, generative AI can facilitate automation and recommend updates to maintenance standards, potentially resulting in a 10-25% increase in compliance.
3. Support reliability engineering
Reliability is a key performance indicator in any asset-based company. Unfortunately, experienced reliability engineers are leaving many locations, leading to limited resources for training alternative employees. By using hybrid AI/ML models, generative AI generates error and impact evaluation from historical data. This permits you to prioritize and reduce serial failures by as much as 25-50% while increasing site reliability by 10-15%.
4. Analyze and apply maintenance standards
Generative AI foundation models can train against asset class standards, including work history, maintenance schedules, work schedules, and spare parts. They discover and recommend compliance with current standards for existing assets. By improving worker skills, generative AI analytics extend asset lifespan by 15-20% and increase uptime by roughly 5-10%.
5. Update maintenance quality
When work orders are accomplished, they often signal the necessity to move on to the following one. However, intelligent evaluation of accomplished work orders can reveal areas where compliance or maintenance processes must be improved. Generative AI can recommend updates to enhance the effectiveness of scheduled maintenance by 15-25% and create latest work plans based on the finished work plan in absence, increasing planning proficiency by 10-20%.
6. Assist in compliance with safety rules and regulations
Generative AI provides real-time support for industry, site or facility security and regulatory compliance, reducing fines by 25% and improving compliance by as much as 50%. Training models that leverage published safety guidelines, regulations, regulatory submissions, decisions and internal data sources significantly improve the speed, accuracy and success rate of regulatory submissions for planners and engineers.
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