In the latest Manufacturing Talks episode, Chris Kuntz joins Jim Vinoski to discuss Augmentir and how the world’s most innovative manufacturers are using Augie, an Industrial Gen AI solution, to revolutionize frontline operations. From real-time insights to enhanced efficiency, Augie is reshaping the shop floor.
The manufacturing industry is embracing AI like never before!
In the latest Manufacturing Talks episode, Chris Kuntz joins Jim Vinoski to discuss Augmentir and how the world’s most innovative manufacturers are using Augie, an Industrial Gen AI solution, to revolutionize frontline operations. From real-time insights to enhanced efficiency, Augie is reshaping the shop floor.
https://www.augmentir.com/wp-content/uploads/2025/02/manufacturing-talks-featured-image.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-02-20 16:41:002025-02-20 18:15:02Manufacturing Talks - Augie, the AI-enabled digital production floor work assistant
Augmentir and UKG are working together to create a digitally connected frontline workforce that is shaping the future of work in manufacturing.
In manufacturing, success isn’t just about machines—it’s about people. But here’s the problem: workforce skills tracking and daily work execution have been handled separately for too long. The result? Misassigned tasks, skills gaps, slower production, and higher error rates.
The solution? Modernizing workforce management by digitally connecting frontline workers with AI-powered skills management and connected worker technology.
Together, Augmentir and UKG are delivering this solution to manufacturing companies around the world. Read on to discover how Augmentir and UKG are working together to create more productive, more engaged workforces in manufacturing.
Workforce Management for Modern Manufacturing Operations
Think of it like peanut butter and jelly: great on their own, but unstoppable together. When manufacturers sync traditional workforce management with AI-powered connected worker technology, they unlock huge benefits:
UKG’s leading workforce management solution, combined with Augmentir’s AI-powered connected worker platform empowers manufacturing companies to optimize labor efficiency, streamline scheduling, reduce mistakes, and ensure compliance, all while boosting productivity on the production floor.
Manufacturing organizations that utilize both Augmentir and UKG Pro Workforce Management™ can benefit from connecting time and attendance, scheduling, and workforce data with Augmentir’s connected worker platform. Through this new integration, manufacturers can gain visibility into real-time, accurate employee information and skills tracking combined with AI-driven insights into work performance. By doing so, manufacturers can improve workforce efficiency and productivity and deliver more impactful training and support for frontline workers.
Right worker, right job – Workers are assigned tasks based on real-time skill assessments.
Training in the flow of work – No need to step away from production; learning happens in real time
Faster onboarding – New hires get up to speed quicker with AI-driven, step-by-step guidance.
Fewer mistakes, higher efficiency – Workers get exactly the information they need, when they need it.
Continuous upskilling – As employees complete tasks, their skills profiles automatically update.
Smarter capacity planning – Give production teams improved capacity planning and a better decision support tool for daily workforce scheduling and management. Proactively look ahead and see coverage gaps based on employee scheduling.
Augmentir’s UKG connector streamlines the flow of employee data into Augmentir, providing operations leaders and plant managers with valuable insights into worker availability, productivity, training effectiveness, and more. This gives production teams improved capacity planning and a better decision support tool for daily workforce scheduling and management.
Gone are the days of outdated skills databases and generic training programs. Today, learning happens on the job, in the moment, and at the worker’s fingertips. Manufacturers can provide personalized on-the-job support to employees through Augmentir’s digital guidance, bringing training in the flow of work and alleviating potential skills gaps.
The Future of Training: Learning in the Flow of Work
Traditional workforce training methods are outdated. Long classroom sessions, dense manuals, and generic training modules don’t cut it anymore—especially in fast-paced manufacturing environments. Workers need real-time, task-specific guidance to build skills and stay productive.
That’s where embedded training comes in. Instead of separating learning from work, Augmentir enables:
Just-in-time training – Employees learn exactly what they need, right when they need it.
Mobile, interactive work instructions – Step-by-step guidance delivered on the shop floor.
Skills-based task assignments – Workers are matched to jobs they’re qualified for, with training baked in.
Continuous learning & upskilling – As workers complete tasks, their skills profiles evolve, keeping pace with job demands.
This approach not only accelerates onboarding but also reduces downtime, improves accuracy, and keeps workers engaged—all while production continues at full speed.
How Augmentir and UKG are Shaping the Future of Work in Manufacturing
Augmentir’s AI-powered connected worker platform makes skills integration effortless. By delivering smart, adaptive digital work instructions, Augmentir ensures that:
Workers receive personalized guidance based on their experience level.
Skills data stays fresh, automatically updating as tasks are completed.
Training gaps are filled in real time, keeping production smooth and efficient.
Supervisors have full visibility into workforce capabilities and gaps.
For manufacturers like Armstrong World Industries (AWI), this has been a game-changer. Facing workforce shortages and declining tenure rates, AWI needed a way to ensure workers had access to the right information at the right time. By adopting Augmentir, AWI empowered its frontline workers to operate equipment, troubleshoot issues, and execute tasks with confidence—all through a single, mobile interface.
The Power of the UKG + Augmentir Partnership
The digital transformation of today’s manufacturing workforce doesn’t stop with Augmentir alone. The partnership between UKG and Augmentir takes workforce optimization to the next level.
By combining UKG’s workforce data (scheduling, time tracking, and HR insights) with Augmentir’s AI-driven skills tracking and adaptive work instructions, companies can:
Schedule workers smarter – Assign shifts based on real-time skill levels.
Close skills gaps faster – Proactively upskill employees before gaps cause production delays.
Improve retention & engagement – Give workers clear paths for career growth and skill development.
Boost operational efficiency – Match the right person to the right job, every time.
This isn’t just about automation—it’s about empowering people. When employees have the skills, training, and resources they need in the flow of work, they stay longer, perform better, and drive business success.
Bottom Line? Augmentir + UKG = The Future of Work in Manufacturing
The manufacturers that integrate digital skills tracking with connected worker technology that supports daily operations will be the ones that thrive in an era of workforce disruption. Augmentir and UKG are making it happen – helping companies close skill gaps, improve efficiency, and build a workforce that’s future-ready.
https://www.augmentir.com/wp-content/uploads/2025/02/future-of-work-in-manufacturing-ukg-augmentir.webp12602400Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-02-18 12:10:032025-02-18 12:10:03The Future of Work in Manufacturing with UKG and Augmentir
Learn how skills tracking enhances work allocation and workforce utilization to improve productivity in manufacturing.
Employee skills tracking is an excellent way to stay ahead of the curve in today’s ever-changing manufacturing landscape. Leaders can use this talent management strategy to close worker competency gaps, increase effective training, and hire qualified prospects.
Putting an emphasis on employee skills can also help manufacturers prioritize work allocation and workforce utilization. But what exactly do these two terms mean and how do they relate to tracking skills in manufacturing?
Work allocation is the process of assigning resources and roles to meet the objectives of a given task or production facility. Workforce utilization, meanwhile, refers to how a company or organization effectively utilizes its workforce to meet its operational goals and objectives.
To keep up with competition, manufacturers should not only try to recruit the best possible hires, but also allocate work in an effective way to retain staff, satisfy customers, and boost profits.
Ultimately, keeping track of skills is a beneficial way to organize a company’s resources to attain sustainable business goals. Implementing a connected worker solution and digitizing skills management processes through smart manufacturing technologies is an effective way for organizations to instantly visualize the skills gaps in teams as well as track workforce skills and quickly assess both team and individual readiness.
Learn more about digital skills tracking and how it improves work allocation and workforce utilization below:
Skills tracking helps ensure that all workers have the necessary expertise to complete tasks to their fullest potential. Basically, it closes the gap between the competencies employees already have and ones they need to further develop.
Every manufacturing firm has a unique set of job requirements and expectations. Tracking worker skills on a regular basis helps a company identify training needs and build workers’ knowledge so that they can meet expected targets. Skills management and tracking software help manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.
In a nutshell, measuring employee proficiencies can boost retention, decrease the amount of time spent on tasks, and improve overall productivity.
Benefits of tracking skills to improve work allocation
Through digitization and effective skills tracking, manufacturing firms can best allocate work to team members based on expertise, credentials, and actual ability. For example, an operator who has more than 10 years of experience using computer-controlled equipment may be a better fit to handle complex machinery than an entry-level worker who lacks that training.
Additionally, with a centralized digital repository managers have a better idea of each employee’s current skills level and potential areas of improvement. Then they can close any skill gaps through training opportunities. In return, workers who receive the necessary training are more likely to thrive in their roles and be productive.
In summary, measuring worker skills can help improve work allocation by:
Hiring or assigning current employees to the correct jobs and tasks
Facilitating worker development through mentorship and training
Retaining high-quality employees
How tracking skills boosts workforce utilization
Workforce utilization refers to how much of an employee’s time is devoted to billable work. Tracking skills can improve this, in turn boosting productivity and profits.
When you measure how efficiently employees are doing their jobs and how well a business manages its resources, you can assure that tasks are done well and see continuous increase in revenue. Think about how many hours of each staff member’s workweek need to be billable to remain profitable and whether they are on track. With a digitized tracking system, manufacturers are able to automate and streamline this process reducing errors, improving productivity, and ensuring success.
Pro Tip
Through the use of smart, connected worker solutions and AI-based workforce insights organizations can deliver continuous, on-the-job learning based on skill tracking and real job performance, promoting reskilling and upskilling efforts enterprise wide.
To summarize, tracking skills can help enhance workforce utilization by:
Setting profitable rates for services based on worker output and time billed
Compensating employees fairly
Gauging whether staff is being overworked or underutilized
By digitizing these tracking processes and implementing AI-driven support, organizations can also visualize, track and offset employee burnout. By taking highly granular connected worker data and using AI to filter out the unnecessary portions, industrial operations are able to not only improve tasks and productivity but better support and empower frontline workers.
Ways to track workforce skills
Tracking employee skills is a great way to improve worker performance and productivity by matching the right person with the right assignment.
One way to track an employee’s skills is through a skills matrix, which is a grid that maps staff credentials and qualifications. A skills matrix helps managers strategize and oversee current and wanted skills for a team, position, department, and more. Similarly, a job cover matrix is used to map employees to tasks, roles, or jobs, ensuring adequate coverage and identifying skill gaps. A skills matrix (as well as a job cover matrix) is usually managed using a spreadsheet, but there are alternatives to skill matrices. For example, cloud-based skills management software can help identify and track employee competence and correlate it with actual job performance. The software can also help managers filter employee databases by skills to assemble teams or assign work based on specific qualifications.
Leadership can also track competencies through a skills taxonomy. Taxonomies help classify and organize skills into groups to better understand which skills employees have and which they should learn. Essentially, these structured lists help management identify and track skills to better allocate resources and worker training opportunities.
Lastly, a skills-tracking application can include AI-based software to identify and measure worker expertise and actual job performance. This is an excellent method for intelligently assigning work through skills mapping, optimizing training programs, and more. With AI-based insights and connected worker technology, organizations can bridge the gap between the training room and the shop floor, integrating training into the flow of work and creating an environment of continuous learning.
Skills management with Augmentir
Augmentir offers top-notch solutions to easily track and manage your frontline’s skillset. Our connected worker solution provides customized dashboards to streamline processes to improve workforce management, skills management, and deliver in-line training and support at the point of work, closing skills gaps at the moment of need.
If you are interested in learning how Augmentir can help improve your skills management, skills tracking, and workforce development – request a live demo.
In conversations with our customers, a recurring theme emerges when discussing their transition to digital processes: the largest cost and burden often lies in the time and effort required to digitize existing paper-based materials.
In conversations we have with manufacturing companies, a recurring theme emerges when discussing their transition to a paperless operation: the largest cost and burden often lies in the time and effort required to digitize existing paper-based materials.
Standard Operating Procedures (SOPs), work instructions, and checklists are typically built over years, representing a significant repository of organizational knowledge. Converting these into digital formats while maintaining accuracy and accessibility can be daunting.
Customers frequently express concerns about the resource-intensive nature of this transformation. It’s not just about scanning documents; it’s about rethinking and structuring them for digital workflows. Many find themselves needing to allocate substantial time to review, update, and adapt content to ensure it aligns with current operational realities and integrates seamlessly into new platforms.
This challenge is real for any industrial company undergoing a transformation to digital manufacturing. It also represents an opportunity … and this is exactly why we created Augie.
The Power of GenAI in Digitizing Content
Generative AI (GenAI) has transformative potential for digitizing content by automating the conversion of paper-based materials into structured, digital formats. It can analyze and extract information from documents like SOPs, work instructions, or checklists, quickly translating them into editable, standardized templates. GenAI also enables content enhancement, such as rewriting for clarity, integrating visuals, language translation, or adapting content for specific workflows. By accelerating the digitization process and reducing manual effort, GenAI empowers organizations to transition to digital systems more efficiently and cost-effectively.
Augie, a suite of Industrial Generative AI tools from Augmentir, revolutionizes industrial digital transformation by combining advanced AI capabilities with practical, human-centric applications. Augie uses generative AI and the power of advanced Large Language Models (LLMs) to transform digital content creation, create adaptive workflows, provide real-time worker guidance, and analyze data to deliver actionable insights.
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Augie has been instrumental in helping us quickly transform our existing paper-based SOPs and training documents into interactive digital work instructions and learning tools. We’ve reduced our digitization effort from months down to days. This has streamlined our processes, reduced errors, and accelerated the upskilling of our workforce.
Digital Transformation Lead Fortune 100 Food & Beverage Manufacturer
Augie for Procedure Creation
Augie is a powerful tool for accelerating the transition from paper-based to digital operations in manufacturing and industrial settings.
Quickly generate standard work procedures from Excel, Word, PDFs, images, or videos. The Augie Content Assistant takes your existing content and generates digital smart forms, checklists, and digital work instructions. Augie can summarize the exchange of tribal knowledge via collaboration and convert these to scalable, curated digital assets that can be shared instantly across your organization.
Augie for Training Content
Augie, Augmentir’s GenAI assistant, makes it easier to convert paper-based information into tailored training content and quizzes for today’s less experienced frontline workforce. Augie automatically analyzes SOPs, work instructions, and other documents to create clear, simplified training modules. It generates interactive quizzes to reinforce key concepts and adapts learning materials to individual skill levels, ensuring workers engage with relevant content.
By streamlining this process, Augie reduces the effort and time required to create effective, hands-on training tools for workforce development.
Augie for Content Localization
Language translation and localization are crucial for ensuring work instructions and training materials are effective and accessible for frontline workers in manufacturing and any industrial setting. Providing materials in a worker’s native language increases comprehension, reduces errors, and enhances safety.
With Augie, content localization is easy. Augie’s content localization tools make work instructions and training materials more relatable and actionable. This investment fosters better workforce performance, inclusivity, and compliance with global standards.
The Next Phase of AI in Manufacturing is Here
Augie redefines the next phase of AI in manufacturing by seamlessly integrating generative AI into frontline operations to accelerate digitization, as well as enhance productivity and worker empowerment. Augie includes a complete suite of AI-powered assistants and AI services that help bridge the skills gap, accelerate onboarding, and ensure frontline workers are equipped with the knowledge they need to succeed.
The Augie Industrial Gen AI Suite transforms every stage of the Connected Worker Journey.
Augie transforms every stage of the connected worker journey by providing a complete suite of AI tools that evolves alongside an organization’s needs. It begins with the digitization of processes and the conversion of static, paper-based content into dynamic, interactive digital workflows, making operations more accessible and efficient for frontline workers. As operations become connected, Augie leverages real-time data to deliver actionable insights, enabling companies to identify inefficiencies, improve workflows, and drive continuous improvement.
Beyond operational enhancements, Augie fosters continuous innovation through its extensibility and seamless integrations with other enterprise systems, creating a unified, scalable ecosystem that adapts to new challenges and opportunities. By addressing every phase of the connected worker journey, Augie empowers organizations to not only modernize their operations but also build a foundation for long-term success and innovation.
Now is the time to embrace the future of manufacturing—don’t miss out on the opportunity to empower your workforce and elevate your operations with Augie. Take the first step toward a smarter, more efficient manufacturing environment today.
https://www.augmentir.com/wp-content/uploads/2024/11/augie-digitizing-frontline-work.webp12602400Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-11-20 16:16:472025-02-07 21:53:20Solving the Single Largest Pain in Digitizing Frontline Work
Learn how Digital Standard Work effectively transforms manufacturing production and enables operational excellence.
Manufacturing organizations are feeling the pressure of increased customer demands, skilled labor shortages, and intense shifts in their frontline workforces, however, they can effectively overcome these obstacles with digital standard work enabled by smart connected worker technology. Digital standard work promotes operational excellence in manufacturing through facilitated knowledge-sharing, enhanced process standardization, increased employee engagement, improved workforce agility, and overall optimization of workforce abilities.
Standardized work in manufacturing (centerlining, machine setup/maintenance, inspection checklists, workforce training, lubrication procedures, etc.) is effective for continuously improving the most efficient and safe methods for performing work to meet customer demand while minimizing waste. Digital Standard Work takes these processes one step further, enhancing them with digital technology to establish a true culture of continuous improvement where frontline workers and shop floor processes benefit from digital workflows, collaboration, AI-powered guidance, generative AI assistants, real-time access to centralized knowledge bases, and more.
By redefining standard work for the digital age, manufacturers can achieve operational excellence through increased efficiency, quality, flexibility, and innovation across their frontline workforces. Read more on Digital Standard Work and how it effectively transforms manufacturing production and enables success:
According to Forbes and McKinsey, through digital tools manufacturers can reduce machine downtime by 30% to 50% and quality-related costs can be reduced by 10% to 20%. Effectively digitizing manufacturing standard work through smart, AI-driven connected worker technology involves:
Interactive Digital Work Instructions Replace paper-based standard operating procedures (SOPs) with interactive digital work instructions that include multimedia elements like videos, images, and animations. These can be accessed by workers on tablets, wearables, and other mobile devices right on the shop floor.
Data Capture and Integration Leverage smart tools and sensors to automatically capture data from the manufacturing process, such as torque values, cycle times, and quality checks. This data can be integrated into the digital work instructions to provide real-time feedback and ensure adherence to standards.
Workflow Automation Automate non-value-added tasks like data entry, approvals, and documentation through connected worker platforms. This streamlines workflows, reduces errors, and frees workers to focus on value-adding activities aligned with standard work.
Knowledge Management Digitize and centralize tribal knowledge and tacit knowledge, best practices, and process documentation in a connected worker platform. This ensures standardized methods are easily accessible and updatable for consistent knowledge sharing across the workforce.
Using smart, connected worker platforms to digitize and optimize standard work in manufacturing drives improved productivity, ensures better and more consistent product quality, and fosters a safer work environment for enhanced operational success. Connected worker platforms that digitize standard work can also be used to support a company’s broader IWS (integrated work systems) strategy, which helps improve operational excellence in manufacturing.
Pro Tip
Using a low-code no-code workflow builder simplifies the creation of complex digital workflows for frontline work processes. Furthermore, integrating remote collaboration tools facilitates real-time guidance, knowledge sharing, and the ability to update standard work procedures based on captured tribal knowledge.
Engaging Frontline Workers with Digital Standard Work
As manufacturing workforces shift due to retirement and tribal knowledge loss, effective workforce training has become critical for continued success. Interactive digital interfaces, augmented and enhanced capabilities, and wearable technologies make standard work practices like workforce training more engaging and accessible, improving workforce adoption and adherence.
Digital tools facilitate information visibility and knowledge sharing among frontline workers, enabling them to learn from each other, share best practices, and contribute to a culture of continuous improvement. By tracking and analyzing performance data from digital systems, manufacturers can identify top performers, provide personalized feedback, and recognize achievements, fostering a sense of engagement and motivation among frontline workers.
Digital Standard Work empowers frontline workers by involving them in process improvements, recognizing their contributions, and providing opportunities for learning and growth, leading to increased job satisfaction and commitment. By leveraging digital technologies and interactive interfaces, manufacturers can transform Standard Work procedures into engaging and empowering experiences for their frontline workforce, driving productivity, quality, and a culture of continuous improvement.
Most importantly it gives manufacturing frontline and factory staff the tools they need to be successful and thus create a more satisfied environment where employees come to work and feel good about what they are doing and how they are doing it.
Driving More Effective Collaboration
Digital standard work also facilitates better collaboration across your frontline teams. Effective communication starts with digital tools, and by implementing digital standard work with connected worker technology, manufacturers can connect frontline team members across shifts, departments, locations, and languages, improving visibility into workforce planning, training, skills tracking, daily management, troubleshooting, and more.
From frontline workers to executives, a digital standard work strategy that leverages connected worker technology allows employees to collaborate seamlessly and easily access information. Connected worker solutions that include industrial collaboration tools allow workers to virtually connect to subject matter experts for remote guidance and assistance. These software tools are becoming commonplace in manufacturing and other industrial settings, where companies are faced with an increasingly distributed and remote workforce, yet still require team collaboration to help troubleshoot and resolve issues. In a nutshell, workers can get more done with greater accuracy in less time.
Interested in learning more?
If you’d like to learn more about how Augmentir and our AI-powered connected worker solution digitizes standard work, streamlines operations, improves communication, and empowers frontline workers with the tools and information they need, schedule a demo with one of our product experts.
https://www.augmentir.com/wp-content/uploads/2024/07/digital-standard-work-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-07-04 11:33:422025-02-07 02:48:29How Digital Standard Work Promotes Operational Excellence in Manufacturing
Today’s dynamic and changing manufacturing workforce needs continuous learning and performance support to effectively sustain and deliver effective on-the-job performance.
Every day we hear about the growing manufacturing “Skills Gap” associated with the industrial frontline workforce. The story is that 30% of workers are retiring in the near future and they are taking their 30+ years of tribal knowledge with them, creating the need to quickly upskill their more junior replacements. In an attempt to solve the knowledge gap issues, an entire generation of companies set out to build “Connected Worker” software applications, however, they all relied on the existing training, guidance, and support processes – the only true difference with this approach has been the creation of technology that takes your paper procedures and puts them on glass.
Along with tribal knowledge and tacit knowledge leaving, today’s workforce is also more dynamic and diverse than previous generations. The 30-year dedicated employees are no longer the norm. The average manufacturing worker tenure is down 17% in the last 5 years and the transient nature of the industrial worker is quickly accelerating. An outgrowth of the COVID pandemic brings forth the Great Resignation, where workers are quitting in record numbers, and worker engagement is down almost 20% in the last 2 years.
This new manufacturing workforce is changing in real-time – who shows up, what their skills are, and what jobs they need to do is a constantly moving target. The traditional “one size fits all” approach to training, guidance, and performance support is fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality and productivity.
Digitizing work instructions is a great start to helping close the manufacturing skills gap, but alone, it won’t help completely solve the problem. We must go a step further to overcome the lack of a skilled and qualified manufacturing workforce.
Enter the 2nd generation of Connected Worker software, one based on a data-driven, AI-supported approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities.
These 2nd generation connected worker solutions are designed to capture highly granular data streaming from connected frontline workers. These platforms are built from the ground up on an artificial intelligence (AI) foundation. AI algorithms are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse data and find correlations and patterns that can be used to identify opportunities for improvement and creates a data-driven environment that supports continuous learning and performance support.
This approach aligns perfectly with the dynamic, changing nature of today’s workforce, and is ideally suited to support their 5 Moments of Need, a framework for gaining and sustaining effective on-the-job performance.
For example, Augmentir’s AI-powered connected worker platform leverages anonymized data from millions of job executions to significantly improve and expand its ability to automatically deliver in-app AI insights in the areas of productivity, safety, and workforce development. These insights are central to Augmentir’s True Proficiency™ scoring, which helps to objectively baseline each of your team members for their level of proficiency at every task so organizations can optimize productivity and throughput, intelligently schedule based on proficiency and skill-levels, and personalize the level of guidance and support to meet the needs of each member of the workforce.
This provides significant benefits to Augmentir customers, who leverage Augmentir’s AI in conjunction with the platform’s digital workflow and remote collaboration capabilities, allowing them to deliver continuous improvement initiatives centered on workforce development. These customers are able to utilize the insights generated from Augmentir’s AI to deliver objective performance reviews, automatically identify where productivity is lagging (or has the potential to lag), increase worker engagement, and deliver highly personalized job instructions based on worker proficiency.
Traditionally, there was a clear separation between training and work execution, requiring onboarding training to encompass everything a worker could possibly do, extending training time and leading to inefficiencies. Today, with the ability to deliver training at the moment of need, onboarding can focus on everything a worker will probably do, identifying and closing skills gap in real-time and significantly reducing manufacturing onboarding times. In one particular case, Bio-Chem Fluidics was able to reduce onboarding time for new employees by up to 80%, while simultaneously achieving a 21% improvement in job productivity across their manufacturing operation.
As workers become more connected, companies have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce.
https://www.augmentir.com/wp-content/uploads/2021/10/this-is-not-your-grandfathers-workforce.jpg6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2021-10-14 16:29:462025-02-07 02:47:12This Is Not Your Grandfather’s Workforce
Learn how manufacturers combat the manufacturing skilled labor shortage and close skills gaps with an Augmented Connected Workforce (ACWF).
Generative AI in manufacturing refers to the application of generative models and artificial intelligence techniques to optimize and enhance various aspects of the manufacturing process. This involves using AI algorithms to generate new product designs, optimize production workflows, predict maintenance needs, and improve production efficiency within frontline operations.
According to McKinsey, nearly 75% of generative AI’s major value lies in use cases across four areas: manufacturing, customer operations, marketing and sales, and supply chain management. Manufacturers are uniquely situated to benefit from generative AI and it is already a transformative force for some. A recent Deloitte study found that 79% of organizations expect generative AI to transform their operations within three years, and 56% of them are already using generative AI solutions to improve efficiency and productivity.
Manufacturing is rapidly evolving and by integrating cutting-edge technologies like Generative AI, manufacturers can better support, augment, and enhance their frontline workforces with improved decision-making, collaboration, and data insights.
Join us below as we dive into generative AI in manufacturing exploring how it works, the benefits and risks, and some of the top use cases that generative AI, specifically generative ai digital assistants, can provide for manufacturing operations:
Generative AI refers to artificial intelligence systems designed to create new content, such as text, images, or music, by learning patterns from existing data. In manufacturing, this involves the use of Large Language Models (LLMs) and Natural Language Processing (NLP) to analyze vast amounts of data, simulate different scenarios, and generate innovative solutions that can impact a wide range of manufacturing processes.
Large Language Models
Large Language Models (LLMs) are a type of generative artificial intelligence model that have been trained on a large volume – sometimes referred to as a corpus – of text data. They are capable of understanding and generating human-like text and have been used in a wide range of applications, including natural language processing, machine translation, and text generation.
In manufacturing, generative AI solutions should leverage proprietary fit-for-purpose, pre-trained LLMs, coupled with robust security and permissions. Industrial LLMs use operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.
Natural Language Processing
Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on the interaction between computers and humans using natural language. It involves the development of algorithms and models that enable computers to understand, interpret, and respond to human language in a way that is both meaningful and useful.
For generative AI, NLP is a key technology that enables the assistants to understand and generate human-like text, providing seamless conversational user experiences and valuable assistance to frontline workers, engineers, and managers in manufacturing and industrial settings.
NLPs allow the AI to process and interpret natural language inputs, enabling it to engage in human-like interactions, understand user queries, and provide relevant and accurate responses. This is essential for common manufacturing tasks such as real-time assistance, documentation review, predictive maintenance, and quality control.
By combining large language models and natural language processing, generative AI can produce coherent and contextually relevant text for tasks like writing, summarization, translation, and conversation, mimicking human language proficiency.
Benefits of Leveraging Generative AI in the Manufacturing Industry
Generative AI and solutions that leverage them offer several benefits for manufacturing operations, including:
Operational/Production Optimization and Forecasting: GenAI technology offers a significant boost to manufacturing processes by monitoring and analyzing in real-time, spotting problems quickly, and providing predictive insights and personalized assistance to boost efficiency for manufacturing workers. Additionally, AI assistants empower manufacturers to explore multiple control strategies within their process, identifying potential bottlenecks and failure points.
Proactive Problem-Solving: Generative AI-powered tools provide real-time monitoring and risk analysis of manufacturing operations, enabling the quick identification and resolution of issues to optimize production and efficiency. They can spot events as they happen, providing valuable insights and recommendations to help operators and engineers rapidly identify and resolve problems before they escalate.
Reduce Unplanned Downtime: Generative AI solutions can analyze vast datasets to predict equipment maintenance needs before issues arise, allowing manufacturers to schedule maintenance proactively, minimizing unplanned disruptions. This not only improves downtime but also contributes to the overall operational resilience of mission-critical equipment.
Personalized Support and On-the-job Guidance: Generative AI tools can be tailored to diverse roles within the manufacturing plant, offering personalized assistance to operators, engineers, and managers. It can provide role-based, personalized assistance, and proactive insights to understand past events, current statuses, and potential future happenings, enabling workers to perform their tasks more effectively and make better, more informed decisions.
These benefits demonstrate the significant impact of generative AI on frontline manufacturing activities, improving overall operational efficiency, adjusting processes where needed, and driving operational excellence.
Pro Tip
Generative AI assistants can take these benefits one step further by incorporating skills and training data to measure training effectiveness, identify skills gaps, and suggest solutions to prevent any skilled labor issues. This guarantees that frontline workers have the essential skills to perform tasks safely and efficiently, while also establishing personalized career development paths for manufacturing employees that continuously enhance their knowledge and abilities.
Risks of Generative AI in Manufacturing
Generative AI in manufacturing presents several risks, including data security, intellectual property concerns, and potential bias in AI models. The reliance on vast amounts of data raises the risk of data breaches and cyberattacks, potentially exposing sensitive information. Intellectual property issues may arise if AI-generated designs or processes inadvertently infringe on existing patents or proprietary technologies. Additionally, biases in training data can lead to suboptimal or unfair outcomes, affecting the quality and equity of AI-driven decisions. There is also the risk of over-reliance on AI, which may reduce human oversight and lead to errors if the AI models make incorrect predictions or generate flawed designs. Ensuring proper validation, transparency, and human intervention is crucial to mitigating these risks.
Top Use Cases for Generative AI Manufacturing Assistants
Generative AI assistants and frontline copilots are AI-powered tools designed to provide valuable assistance and insights in industrial settings, particularly in manufacturing. These assistants are a type of generative AI that are used in manufacturing operations to enhance human-machine collaboration, streamline workflows, and offer proactive insights to optimize performance and productivity for frontline workers.
What makes frontline AI assistants unique among other generative AI copilots is the enhanced human-like interaction beyond standard data analytics and analysis to understand the context around a process or issue; including what happened and why, as well as anticipate future events.
Generative AI assistants work via specialized large language models (LLMs) and generative AI, providing contextual intelligence for superior operations, productivity, and uptime in industrial settings. Additionally, they typically involve natural language processing for understanding human language, pattern recognition to identify trends or behaviors, and decision-making algorithms to offer real-time assistance. This, combined with machine learning techniques, allows them to understand user inputs, provide informed suggestions, and automate tasks.
Troubleshooting:Troubleshooting is such a critical use case in manufacturing. With today’s skilled labor shortage, frontline workers are often times in situations where they don’t have the decades of tribal knowledge required to quickly troubleshoot and resolve issues on the shop floor. AI assistants can help these workers make decisions faster and reduce production downtime by providing instant access to summarized facts relevant to a job or tasks, this could come from procedures, troubleshooting guides, captured tribal knowledge, or OEM manuals.
Personalized Training & Support: With GenAI assistants, manufacturers can instantly close skills and experience gaps with information personalized, context-aware to the individual worker. This could include: on the job training materials, one point lessons (OPLs), or peer/user generated content such as comments and conversations.
Leader Standard Work: With Generative AI assistants, operations leaders can assess and understand the effectiveness of standard work within their manufacturing environment, and identify where there are areas of risk or opportunities for improvement.
Converting Tribal Knowledge: One of the more pressing priorities that many manufacturers face is the task of capturing and converting tribal knowledge into digital corporate assets that can be shared across the organization. With connected worker technology that utilizes Generative AI, manufacturing companies can now summarize the exchange of tribal knowledge via collaboration and convert these to scalable, curated digital assets that can be shared instantly across your organization.
Continuous Improvement: AI and GenAI assistants can help us identify areas for content improvement, and make those improvements, measure training effectiveness, and measure and improve workforce effectiveness.
Operational Analysis: Generative AI assistants can also provide value when it comes to operational improvements. GenAI assistants can use employee attendance data to help shift managers or line leaders determine where the risks are, and potentially offset any resource issues before they become truly problematic. An organization’s skills matrix, presence data, and production schedules all can feed into a fit-for-purpose, pre-trained LLM – giving you information that manufacturing leaders need to keep their operations running.
Future-proofing Manufacturing Operations with Augie™
Generative AI and other AI-powered solutions are leveling up manufacturing operations, analyzing data to predict equipment maintenance needs before issues arise, allowing for proactive maintenance scheduling, and minimizing unplanned disruptions. With these tools manufacturers can empower frontline workers with improved collaboration and provide real-time assistance with contextual information, ensuring relevant and timely support during critical decision-making processes.
Overall, generative AI is transforming a wide array of manufacturing and industrial activities, connecting workers in ways that were previously thought impossible, and making frontline tasks and processes safer and more efficient for workers everywhere.
Augie, Augmentir’s new generative AI assistant for frontline work pulls in skill capabilities, workforce development information, and training data in addition to MES and ERP data. It offers contextual, proactive insights and automated workflows to optimize production and prevent bottlenecks, contributing to manufacturing efficiency, uptime, quality, and decision-making.
Additionally, Augie ties together operational data, training and workforce management data, engineering data, and knowledge/information from various disparate enterprise systems to empower frontline workers, streamline workflows, and increase manufacturing performance.
Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.
https://www.augmentir.com/wp-content/uploads/2024/06/generative-ai-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-06-17 18:43:542025-02-05 15:57:34Generative AI in Manufacturing: Benefits, Risks, and Top Use Cases
Connected frontline operations platforms are helping manufacturers reduce downtime and provide a foundation for a holistic preventive maintenance strategy.
Centerlining in manufacturing is a methodology that uses standardized process settings to assure that all shop floor operations are carried out consistently.
For example, in manufacturing, it pinpoints which machine settings are needed to execute a given process and ensures operators implement those settings to avoid any defects on the shop floor. This works to decrease product and procedure discrepancies by improving machine efficiency.
The type of machine configurations that can be centerlined to create quality goods that meet customer expectations range from temperature, speed, and pressure settings to the proper alignment of guard rails. When applied to a procedure, centerlining can substantially increase the number of sellable items, secure uniform product quality, and decrease production costs.
In a nutshell, employing a successful centerlining process can help optimize plant operations and reduce mistakes in product creation.
Learn more about how centerlining can improve everyday operations, and how to centerline a manufacturing process to yield the best output, in the following sections:
Centerlining works by using specific machine settings per product (pressure, speed, temperature, etc.) to ensure processes are carried out the same way during each assembly line run.
Using the right centerline settings also has a side benefit: it lets operators identify problems as they happen. If workers know which process variables are triggering production delays, they can better control them to boost product quality output.
This can be achieved by creating a statistical process control chart to see which variables are causing interruptions to the assembly line and make any needed changes to the process. Creating a chart can also help workers identify procedures that are affecting the development of goods to ensure continuous improvement.
Centerlining goes hand in hand with total productive maintenance (TPM), a method which utilizes equipment, machine operators, and supporting processes to boost the quality and safety of production protocols.
How manufacturing efficiency can be improved by centerlining
Standardizing the appropriate machine settings can make everyday operations run more smoothly. For example, centerlining the requirements for each product can streamline changeovers, allowing workers to quickly reset their equipment and not lose time when switching to a new product run. This can prevent costly mistakes and reduce waste throughout the shop floor.
It also guarantees that all processes are completed in the same manner. Consistency helps ensure quality, especially when operators are setting up equipment for a production run. Failing to configure the right settings can increase the time for product changeovers and cause product deficiencies.
How to centerline a manufacturing process
Centerlining in manufacturing is a great way to troubleshoot product and procedure variations, oversee operations, and carry out statistical analysis to boost quality assurance and control.
Learn how to centerline a process by following the four steps below.
Step 1: Determine key process variables
It’s crucial to spot process variables that have the greatest effect on product quality to minimize any defects. Potential variables can include pressure, temperature, density, mass, and more.
Step 2: Identify machine settings for each variable
Then, look at which centerline settings can be applied to each process to ensure the creation of quality goods. Again, you’ll want to determine what has worked well in the past and use a statistical process control chart to set variable limits.
Important things to consider are: when the process has worked, which setting was best suited for that procedure, and how the two worked in conjunction with one another.
Step 3: Assess variable impact on production process and product
After you’ve identified the appropriate machine settings, it’s time to monitor how each variable impacts the production process and final product creation. Start by analyzing which assembly line runs yielded the highest production rate, factoring in things like equipment idle time, scrapped parts, rework, etc., to gauge what works and what needs improvement.
It’s vital that you have accurate, clear data to analyze. We recommend digitizing your centerlining process and results to correctly quantify the performance of each variable.
Step 4: Ensure centerline settings are always applied
Lastly, make sure that all operators are aware of and educated on how to best implement a centerlining process so that the right settings are applied each time. Failure to do so can result in mistakes and product deficiencies down the line. It’s best to provide all the necessary resources, steps, and training from the get-go to avoid costly errors. Digital work instructions and connected worker tools are a great way to ensure that operators are properly equipped to perform centerlining procedures.
At this stage, your manufacturing firm should have the proper reporting techniques to evaluate product quality against centerline procedures.
Interested in learning more?
Augmentir is a connected worker solution that allows industrial companies to digitize and optimize all frontline processes that are part of their TPM strategy. The complete suite of tools are built on top of Augmentir’s patented Smart AI foundation, which helps identify patterns and areas for continuous improvement.
