Introducing the AI-readiness assessment for manufacturers

Historically, manufacturers have struggled to fully utilize, analyze, and understand the vast amounts of complex data generated during lengthy production runs. When teams can’t understand the relationship between inputs and outputs, they can’t continuously improve production. Plus, given the 24/7 pace of industrial manufacturing, operators and engineers don’t have time to improve processes. 

The good news is that you likely have untapped improvement opportunities, meaning there is potential for operational and financial gains. The challenge lies in having the right infrastructure, tools, and expertise to effectively identify, evaluate, and implement those improvements.

The most promising way to predict quality in real-time, identify optimal process settings, and reduce input costs is through the use of Artificial Intelligence (AI).

About the AI-readiness assessment

During the assessment, you’ll be asked 12 questions related to your organization’s data infrastructure, overall business strategy, operational processes, talent capabilities, and existing technologies. These questions are designed to gauge your organization’s level of AI readiness. 

Once you complete the assessment, you’ll receive a detailed framework outlining your organization’s rank and how to advance to the next stage in your AI journey. This framework includes key recommendations to build or solidify a foundation for AI at your manufacturing company. 

Implementing and using AI is no simple feat. Without the right foundation, your organization’s AI initiatives are likely to stall or fail to meet expectations. To maximize the chances of a successful AI roll-out, each of these steps should be addressed sequentially:

1. Establish a scalable, unified data architecture that reduces lag time to quality information 

Your production data must be accessible, clean, and globally structured to be used by AI and ML algorithms. Access to high-quality and accurate data empowers your talented teams to make quick, impactful wins that strengthen a data-driven culture. 

2. Increase operators’ access to quality information for proactive improvements

Once data is available to teams, it’s all about distilling the most valuable insights from your data and shortening the time it takes to implement these insights. Visualization dashboards, automated alerting and monitoring tools, and real-time centerlining solutions synchronize autonomous solutions with your human workforce.

3. Apply machine learning and Artificial Intelligence technologies to identify and implement optimal process settings

At this stage, your autonomous use cases begin to scale and snowball for amplified impact. You can use advanced analytics tools to obtain exact setpoints for critical production steps, get real-time recommendations for addressing anomalies, and implement predictive or prescriptive maintenance strategies.  

With our 5-minute AI-readiness assessment, you can understand which steps you need to take to move up the ladder and advance your AI strategy. 

Are you ready for your 5-minute assessment?

Countless manufacturers are already leveraging autonomous tools to decrease their margins, gain market share, and improve sustainability efforts. Taking our AI-readiness assessment is a critical step in ensuring your company keeps pace with competitors without roadblocks. 

Our AI-readiness assessment helps manufacturers gauge where they stand on their AI journey and what steps they need to take to adopt and scale AI solutions effectively. 

In just a few minutes, you can benchmark your capabilities, identify gaps, and get an expert viewpoint on priorities to maximize value from AI investments.