Recently, Augmentir completed a rigorous qualification audit as part of a Tier 1 Pharmaceutical Manufacturing company’s Good Manufacturing Practice (GMP), and we are pleased to announce that our product successfully passed the audit.
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A recent article published by The Washington Post shows some shocking numbers on the amount of Americans leaving their jobs over the past year. It’s no surprise that hotel and restaurant workers are resigning in high numbers due to the pandemic, but what is surprising is the fact that the manufacturing industry has been hit the hardest with “a nearly 60 percent jump” compared to pre-pandemic numbers. This “Great Resignation in Manufacturing” is the most of any industry, including hospitality, retail, and restaurants, which have seen about a 30% jump in resignations.
However, if you dig deeper, this trend isn’t new. This recent increase in job quitting in manufacturing has simply magnified a problem that had already been brewing for years, even prior to the start of the pandemic. In fact, in the four years prior to the pandemic (2015-2019), the average tenure rate in manufacture had decreased by 20% (US Bureau of Labor Statistics).
This accelerating workforce crisis is placing increased pressure on manufacturers and creating significant operational problems. The sector that was already stressed with a tight labor market, rapidly retiring baby-boomer generation, and the growing skills gap is now facing an increasingly unpredictable and diverse workforce. The variability in the workforce is making it difficult, if not impossible to meet safety and quality standards, or productivity goals.
Manufacturing leaders’ new normal consists of shorter tenures, an unpredictable workforce, and the struggle to fill an unprecedented number of jobs. These leaders in the manufacturing sector are facing this reality and looking for ways to adjust to their new normal of building a flexible, safe and appealing workforce. As a result, managers are being forced to rethink traditional onboarding and training processes. In fact, the entire “Hire to Retire” process needs to be re-imagined. It’s not the same workforce that our grandfather’s experienced, and it’s time for a change.
The Augmented, Flexible Workforce of the Future
The reality is that this problem is not going away. The Great Resignation in manufacturing has created a permanent shift, and manufacturers must begin to think about adapting their hiring, onboarding, and training processes to support the future workforce in manufacturing – an Augmented, Flexible Workforce.
What does this mean?
It means adopting new software tools to support a more efficient “hire to retire” process to enable companies to operate in a more flexible and resilient manner.
It means starting to understand your workforce at an individual level and using data to intelligently closes skills gaps at the moment of need and enables autonomous work.
And it means taking advantage of data. More specifically, real-time workforce intelligence that can provide insights into training, guidance, and support needs.
Investing in AI-powered connected worker technology is one way to boost this operational resiliency. Many manufacturing companies are using digital Connected Worker technology and AI to transform how they hire, onboard, train, and deliver on-the-job guidance and support. AI-based connected worker software provides a data-driven 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.
As workers become more connected, manufacturers 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. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.
https://www.augmentir.com/wp-content/uploads/2022/02/great-resignation-in-manufacturing.jpg6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2022-02-17 02:31:322025-07-04 11:22:47The Great Resignation in Manufacturing
After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.
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After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:
The use of AI to Improve Quality, Reduce Defects, and Increase Profits
Developing a Digital Twin to Optimize Plant Operations
Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
Designing Products Enabled by Additive and Hybrid Manufacturing Techniques
Exploring the Use of AI in Industrial Attacks and Defense
Using AI to Unlock the True Potential of Today’s Modern, Connected Workforce
Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning.
The Misunderstood Fear of AI
Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.
As we’ve seen with our customers, this couldn’t be farther from the truth. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth.
Understanding Today’s Struggles Within Manufacturing
The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance.
Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations.
Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.
Leveraging AI to Help Build and Grow a Top Performing Workforce
AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time.
The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow.
With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.
AI in Manufacturing will solve many of the challenges that we are seeing.
Learning & Development and the 5 Moments of Need
The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.
According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of:
When people are learning how to do something for the first time (New).
When people are expanding the breadth and depth of what they have learned (More).
When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
When problems arise, or things break or don’t work the way they were intended (Solve).
When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).
The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.
Looking Ahead
We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.
Learn how to reduce changeover time in manufacturing and the benefits of doing so to maximize production processes.
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Providing quality products consistently and on time is at the forefront of customer satisfaction. In today’s competitive market, manufacturers must execute production runs quickly and efficiently to meet customer demand. But equipment and workers can’t operate 24/7. Machines must be properly maintained, workstations require cleaning and employees need rest. This is where optimizing changeover time comes in.
Changeover time is the period that it takes for workers to adjust machines or for assembly lines to start the next product run. A changeover usually includes swapping parts, sanitizing equipment, and preparing it for the next cycle. A good rule of thumb is to keep the changeover period down to less than 10 minutes. You can keep track of your organization’s changeover time by capturing how long it takes to produce each product.
Keeping an eye on your changeover time can help you maximize production and improve processes. Learn more about how you can reduce changeover time in manufacturing by exploring the following topics:
Minimizing changeover time is a key component of lean manufacturing, a production method aimed at minimizing waste while increasing worker productivity. Implementation of this process of quick changeover can help manufacturers maximize uptime and cut down on waste caused by downtime.
Although there are various steps you can take to reduce it, here are some essential steps to help you get started:
Step 1: Assess your present changeover method.
It’s crucial to look at your existing changeover protocol before taking action to modify it. Try to identify which processes need optimization in order to cut down on the time between inventory runs.
Step 2: Implement single-minute exchange of dies (SMED).
Single-minute exchange of dies is a tool used in lean manufacturing to reduce changeover time to single digits. This means that a successful assembly run should be less than 10 minutes.
It’s helpful if workers have some idea of how long each task (such as switching parts, cleaning, etc.) takes during the production process. This awareness can be cultivated the more they familiarize themselves with procedures and day-to-day routines.
Step 3: Create standard changeover procedures.
Creating standard operating procedures (SOPs) and standardizing work can help with the changeover process. If there aren’t centralized procedures, changeover times will vary based on the employee, how long it takes them to clean up, set up and begin a new production run.
It’s important for procedures to contain explicit directions on how to perform successful changeovers. This can include highlighting which equipment needs to be calibrated and other machinery-related tasks.
Pro Tip
Digitizing changeover procedures can offer several benefits that enhance the overall efficiency, safety, and effectiveness of the changeover process. Digital procedures can be accessed by frontline workers through a mobile device or wearable technology, and help improve accessibility, accountability, standardization, as well as provide visual aids to less-experienced workers performing the task.
In a nutshell, having clear instructions makes it easier for workers to know what to expect when it’s time for a changeover.
Benefits of reducing changeover time
Reducing changeover time can yield a number of benefits, especially for companies producing a large number of products on a day-to-day basis.
Some of the advantages include:
Makes it easier to transition between production processes
Creates a more productive work environment
Helps to reduce equipment downtime
Gets products to customers faster
How digitization can help
Implementing connected worker solutions that digitize and optimize changeover processes can help reduce the time each changeover takes by providing explicit digital instructions customized to any given task, machine, or worker.
Digital work instructions are electronic versions of work instructions, quality manuals, or SOPs that provide necessary visual aids and real-time contextual information to help guide workers through complex tasks. These digital work instructions intelligently deliver guidance and streamline changeover processes with images, videos, augmented reality experiences, and live support from colleagues or subject matter experts.
Augmentir is the world’s first AI-powered connected worker platform that helps industrial frontline workers reduce changeover time in manufacturing using smart technology. Learn how world class manufacturers are using Augmentir to drive improvements across their industrial operations – contact us for a demo today!
https://www.augmentir.com/wp-content/uploads/2023/09/reduce-changeover-time-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-09-03 03:11:502025-06-19 12:35:32How to Reduce Changeover Time in Manufacturing
Daily Management helps track today — but it’s not enough. Discover why top manufacturers are turning to Integrated Work Systems to drive continuous improvement.
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Walk into any modern manufacturing facility and you’ll likely see some form of Daily Management in action — shift handovers taking place, whiteboards filled with KPIs, supervisors tracking downtime or productivity issues. For many factories, this is the heartbeat of frontline operations. And rightly so — Daily Management plays a critical role in keeping teams aligned and performance on track.
But here’s the thing: Daily Management is not enough.
More and more manufacturers are realizing that simply tracking what happened today — and reacting to it — doesn’t drive long-term improvement. It doesn’t prevent breakdowns. It doesn’t fix the root cause of recurring quality issues. And it certainly doesn’t help build a digitally enabled, agile, and resilient operation.
If you’re searching for a Daily Management System or software tool to better manage frontline tasks, that’s a great first step. But don’t stop there. Because the real value lies in thinking bigger — in building an Integrated Work System (IWS) that brings all the moving parts of your frontline operations together.
Let’s unpack why.
The Daily Management Trap
At its core, Daily Management helps answer the question: “How are we doing today?”
It gives your team structure — a cadence of check-ins, dashboards, and updates. But the more you rely on it as your primary tool, the more you risk getting stuck in a reactive loop:
Downtime occurred? Log it and move on.
A defect showed up again? Note it and check the box.
A shift fell short of the target? Talk about it and try again tomorrow.
The result? Problems keep resurfacing. Equipment ages faster than it should. Tribal knowledge stays in workers’ heads. And improvement efforts feel like a game of whack-a-mole.
Daily Management shines a light on the symptoms — but an Integrated Work System tackles the root causes.
The Bigger Picture: What’s Missing?
What separates top-performing factories from the rest isn’t just how well they manage today — it’s how they build systems to improve tomorrow.
As highlighted by Ernst & Young, in collaboration with Procter & Gamble, leading manufacturers are moving beyond reactive daily routines and embracing integrated digital systems that connect operations, empower frontline teams, and enable continuous improvement across all use cases that are critical to frontline operations.
Here are just a few critical areas that often extend beyond traditional daily management:
Issue Management: Logging problems is easy. Solving them — through root cause analysis, countermeasures, and tracking — requires structure.
Autonomous Maintenance: Operators should be empowered to care for their equipment, not just report when it fails.
Changeovers: Transitioning between products or shifts introduces variability. Standardizing this is key to minimizing downtime.
Centerline Management: Decrease product and procedure inconsistencies by optimizing machine effectiveness.
Breakdown Elimination: Recurring failures don’t go away by chance. They go away when someone owns them — and has the tools to eliminate them.
Manufacturing Collaboration: Improvements aren’t made in isolation. Visibility, communication, and shared accountability are critical.
5S Audits and Layered Process Audits: Safety and quality audits should be woven into the flow of work — not tacked on as separate compliance exercises.
Individually, these areas may seem like “extra” layers. But together, they form the foundation of an Integrated Work System.
From Managing the Day to Managing the Work
An Integrated Work System doesn’t just organize tasks — it connects the work, the people, and the insights needed to operate at a higher level.
Instead of fragmented tools and outdated spreadsheets, IWS brings everything into one unified approach — so your team can:
Identify issues in real-time
Standardize best practices
Eliminate variability and waste
Collaborate across shifts and functions
Improve continuously — not just reactively
It’s a shift from firefighting to problem-solving. From knowing what happened to knowing why it happened — and preventing it from happening again.
Technology That Supports the Shift
Of course, none of this is possible with whiteboards and paper checklists. Manufacturers need modern tools that support the reality of the factory floor — and help bring Integrated Work Systems to life.
That’s where connected worker technology comes in.
Platforms like Augmentir give manufacturers the digital foundation they need to:
Turn SOPs, audits, and maintenance routines into smart digital workflows
Capture real-time data from the frontline without adding admin overhead
Personalize guidance and support for each worker based on skill level and performance
Analyze trends and surface insights using AI — so you can focus improvement where it matters most
Augmentir helps you go beyond daily visibility. It helps you build a connected, data-driven, and continuously improving frontline operation.
Think Bigger Than Daily
Yes, you need a system to manage the day — but you also need a system to manage improvement.
A Daily Management System may be the entry point, but don’t let it be the end goal. Start thinking holistically about your operations. Ask the hard questions. Look at the gaps between your teams. Audit the processes that break down too often. And most importantly, give your workers the tools they need to contribute — not just comply.
The future of manufacturing isn’t just about managing tasks. It’s about connecting work, people, and performance.
That’s the promise of an Integrated Work System.
That’s where real transformation begins.
And with solutions like Augmentir, it’s never been more achievable.
https://www.augmentir.com/wp-content/uploads/2025/06/thinking-beyond-daily-management-iws.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-06-10 12:21:182025-06-10 12:21:18Thinking Beyond Daily Management: Why You Need an Integrated Work System for Your Factory
Supercharge your IWS strategy with Augmentir’s AI-powered platform. Digitize work, upskill workers, and drive continuous improvement in manufacturing.
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An Integrated Work System (IWS) strategy is essential for driving continuous improvement and achieving world-class manufacturing performance. Originally developed by Procter & Gamble (P&G), IWS is a comprehensive approach to optimizing operations by aligning people, processes, technology, and culture. It focuses on improving manufacturing reliability, reducing costs, and increasing productivity through standardization, capability building, and a relentless focus on continuous improvement.
But even the best-designed IWS strategies can fall short without the right tools to support execution and sustain momentum. That’s where Augmentir comes in.
Augmentir is an AI-powered connected worker platform that supercharges your IWS strategy by digitizing, guiding, and optimizing frontline operations. From standard work execution and skills development to real-time performance insights, Augmentir enhances every IWS pillar — making your system smarter, more agile, and more effective.
Digitize and Standardize Work Processes
At the heart of IWS is a commitment to standardized work — clearly defined, repeatable processes that reduce variation and waste. Augmentir makes it easy to digitize and deploy standardized work instructions across your organization. With intuitive, no-code tools, you can rapidly create digital workflows that are accessible on any device, ensuring consistency and adherence to best practices.
Digitize Total Productive Maintenance and Asset Management with Augmentir
But Augmentir goes a step further. It doesn’t just digitize your SOPs — it continuously improves them. Through built-in AI, Augmentir identifies where processes break down, which steps cause the most errors, and how top performers complete tasks more efficiently. This gives you a data-driven foundation for refining your standards and driving continuous improvement.
Empower and Upskill Frontline Workers
A successful IWS strategy empowers every employee to contribute to performance gains. Augmentir’s connected worker platform personalizes the work experience for each operator. Whether it’s delivering real-time guidance based on current skill level or surfacing just-in-time training content, Augmentir helps close skill gaps and build workforce capability on the job.
With Augmentir’s integrated skills management system, you get a live view of workforce readiness across your lines, shifts, and sites. You can align training investments with actual performance needs, monitor certification status, and track progress against capability-building goals — all within the same platform.
Enhance Autonomous Maintenance and Problem Solving
Autonomous maintenance is a key component of IWS, empowering operators to identify and resolve issues at the source. Augmentir supports these initiatives by guiding workers through inspection, lubrication, and minor maintenance tasks with step-by-step digital instructions. Workers can capture and report issues on the spot, while supervisors gain visibility into completion rates and problem trends.
What’s more, Augmentir facilitates structured problem solving by giving teams the tools to document root causes, track countermeasures, and share lessons learned — all within the context of day-to-day operations.
Streamlined Daily Management and Shift Handovers
Augmentir supports a company’s Integrated Work System (IWS) strategy by enhancing key elements of frontline operations such as daily management, direction setting, and shift handovers. By digitizing and standardizing these workflows, Augmentir ensures that critical information is captured, shared, and acted upon consistently across teams and shifts. This not only drives operational discipline but also aligns frontline activity with strategic objectives.
Daily direction setting becomes significantly more effective with Augmentir’s digital tools. Supervisors can rapidly communicate goals, identify production variances, and prioritize actions using real-time data from the shop floor. Augmentir’s connected worker platform ensures that frontline teams are equipped with clear, up-to-date instructions that reflect current conditions, reducing downtime and enabling more agile responses to issues.
Additionally, Augmentir streamlines shift handovers by providing a structured, digital record of shift activities, issues, and resolutions. This eliminates the information gaps and miscommunications that often occur during manual handovers, ensuring continuity and faster problem resolution.
By integrating seamlessly into IWS frameworks, Augmentir empowers companies to build a more proactive, data-driven, and aligned frontline workforce.
Unlock Continuous Improvement with Data and AI
IWS relies on data to drive informed decision-making and continuous improvement. Augmentir captures rich, real-time data from every task completed by your frontline teams. Its AI engine then analyzes this data to uncover hidden inefficiencies, suggest targeted improvements, and recommend actions that directly impact OEE and operational KPIs.
Instead of relying on assumptions or static audits, Augmentir enables a dynamic, data-driven improvement loop — where insights are generated in real time, and decisions are based on actual shop floor behavior.
A Foundation for Sustainable Operational Excellence
An IWS strategy is not a one-time project — it’s a long-term commitment to operational excellence. Augmentir helps sustain that journey by aligning your people, processes, and technology through a single, AI-driven platform. By providing data visibility, enabling a culture of ownership, and continuously optimizing workflows, Augmentir ensures that your IWS system doesn’t just run — it evolves.
Start Building a Smarter IWS with Augmentir
Whether you’re just beginning your IWS journey or looking to accelerate existing initiatives, Augmentir gives you the digital backbone you need. From standard work and skills development to continuous improvement and performance tracking, Augmentir is purpose-built to support and scale IWS strategies in modern manufacturing environments.
Augmentir supports your IWS strategy by acting as a single pane of glass for your frontline operations. With Augmentir, you can digitize, manage, and optimize all aspects of your frontline operation:
Daily Direction Setting (DDS)
Daily Management System (DMS)
Centerline Management
Clean, Inspect, Lubricate processes
Defect Management
Breakdown Elimination
Changeover Management
Shift Handover
5S and Layered Process Audits
Quality Management on the Shop Floor
Safety
Maintenance
Let Augmentir be your partner in transforming how work gets done — and in unlocking the full potential of your IWS strategy.
https://www.augmentir.com/wp-content/uploads/2025/06/iws-strategy-with-augmentir.webp12602400Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-06-04 13:13:512025-06-10 12:14:10Support Your IWS Strategy with Augmentir: The Smartest Path to Operational Excellence
Explore top use cases for generative AI in manufacturing, how GenAI copilots and digital assistants work, and benefits for frontline workers.
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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.
While traditional AI focuses on data analysis, pattern recognition, and decision-making, generative AI creates new content and synthetic data, enabling innovative solutions. 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. Generative AI is driving innovation and efficiency across the manufacturing sector, enabling advanced digital solutions and competitive advantages. 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. Gen AI is being adopted as a modern alternative to traditional methods, surpassing manual inspections and basic automation to deliver greater operational improvements.
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 includes the ability to generate new product designs and create synthetic data, such as realistic images, videos, or text, to support manufacturing innovation and AI training. The use of Large Language Models (LLMs) and Natural Language Processing (NLP) enables these systems to analyze vast amounts of data, leveraging advanced algorithms and machine learning algorithms to improve prediction accuracy and operational efficiency, 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. LLMs can also enhance document search by efficiently finding, extracting, and summarizing information from technical manuals, reports, and operational records.
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. NLP also enables interactive learning experiences, allowing employees to engage with training content, receive immediate feedback, and clarify doubts in real time.
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. Through process optimization and enhancing efficiency with real-time data analysis and automation, manufacturers can streamline operations, reduce downtime, and improve productivity. 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. Predictive analytics and improved quality control help reduce waste and support continuous improvement in manufacturing processes.
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. Generative AI can also optimize maintenance schedules and delivery schedules to further reduce downtime and improve supply chain reliability. 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. GenAI solutions and applications involved implementing generative AI provide optimized parameters for operators and help manage inventory more effectively.
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.
The use of any genAI tool in manufacturing requires careful consideration of ethical, data privacy, and security risks, as well as potential impacts on employment.
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. The manufacturing sector is being transformed by these advanced AI applications, which are driving efficiency, innovation, and better decision-making across the industry.
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. AI and machine learning are used together in manufacturing to automate defect detection and optimize supply chains, further enhancing operational efficiency.
Here are 6 of the top use cases for generative AI in manufacturing:
1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
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.
Future-proofing Manufacturing Operations with Augie™
Augie™, Augmentir’s generative AI assistant for frontline work, represents the next generation of generative AI solutions, purpose-built to help manufacturing companies future-proof their operations. By harnessing the power of artificial intelligence and machine learning, Augie enables manufacturers to optimize production processes, improve quality control, and reduce maintenance costs—all while adapting to rapidly changing market demands.
With Augie, manufacturers can analyze vast amounts of data from diverse sources, including machine data, sensor data, and historical data, to identify patterns and make predictive, data-driven decisions. This advanced platform delivers real-time insights into production processes, allowing manufacturers to quickly respond to shifts in demand, supply chain disruptions, or operational anomalies. Augie also features sophisticated algorithms for demand forecasting, inventory management, and supply chain optimization, helping companies minimize environmental impact and maximize operational efficiency.
Augie 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.
By integrating Augie into their operations, manufacturers can boost productivity, reduce unplanned downtime, and achieve significant cost savings. The platform’s AI-driven quality control ensures improved product quality, while its customer service automation capabilities enhance responsiveness and satisfaction. Ultimately, Augie empowers manufacturing companies to stay ahead of the competition, adapt to evolving industry trends, and secure a sustainable, competitive advantage in the global marketplace.
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 18:43:542025-06-09 15:26:36Generative AI in Manufacturing: Benefits, Risks, and Top Use Cases
Learn how to digitize your operations and build a paperless factory in this paperless manufacturing guide from Augmentir.
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Manually managing and tracking production in manufacturing has become a thing of the past. That’s because manufacturers are adopting a new digital approach: paperless manufacturing.
Paperless manufacturing uses software to manage shop floor execution, digitize work instructions, execute workflows, automate record-keeping and scheduling, and communicate with shop floor employees. More recently, this approach also digitizes skills tracking and performance assessments for shop floor workers to help optimize workforce onboarding, training, and ongoing management. This technology is made up of cloud-based software, mobile and wearable technology, artificial intelligence, machine learning algorithms, and advanced analytics.
More recently, your journey to paperless manufacturing is being accelerated through the availability of generative AI assistants and supporting import tools that can streamline the conversion of existing content into interactive, mobile-ready content for your frontline teams.
Paperless manufacturing software uses interactive screens, dashboards, data collection, sensors, and reporting filters to show real-time insights into your factory operations. If you want to learn more about paperless manufacturing processes, explore this guide to learn about the following:
A paperless factory uses AI-powered software to manage production, keep track of records, and optimize jobs being executed on the shop floor. Paperless manufacturing is intended to replace written record-keeping as well as paper-based work instructions, checklists, and SOPs, and keep track of records digitally.
For example, in most manufacturing operations, everything from quality inspections to operator rounds and planned and autonomous maintenance is done on a regular basis to make sure factory equipment is operating properly and quality and safety standards are met. In most manufacturing plants, these activities are done manually with paper-based instructions, checklists, or forms.
Operators and shop floor workers in paperless factories use software to execute work procedures and see production tasks in ordered sequences, which enables them to implement tasks accordingly. Workers are able to view operating procedures, or digital work instructions, using mobile devices (wearables, tablets, etc.) in real-time.
Furthermore, paperless manufacturing incorporates the digitization of shop floor training, skills tracking, certifications, and assessments. This digital approach uses skills management software helps optimize HR-based processes that were previously managed via paper or spreadsheets, and includes the ability to:
Create, track, and manage employee skills
Instantly visualize the skills gaps in your team
Schedule or assign jobs based on worker skill level and proficiency
Close skill gaps with continuous learning
Make data-driven drive operational decisions
What are the benefits of going paperless in manufacturing?
There are a number of reasons for factories to go paperless, from cost-effectiveness to increased productivity and sustainability. A paperless system can revolutionize production processes, workforce management, and business operations.
Here are the top benefits of going paperless:
Accelerate employee onboarding: By digitizing onboarding and moving training into the flow of work, manufacturers can reduce new hire onboarding time by 82%.
Increase productivity: Digitizing manufacturing operations means no more manual, paper-based data collection or record-keeping. Workers have more time to run their equipment, execute shop floor tasks, and find solutions to problems.
Boost data accuracy: People are prone to making mistakes, but shop floor data capture and validation can help offset human error and improve accuracy.
Improved workforce management: Digital skills tracking and AI-based workforce analytics can help optimize production operations and maximize worker output.
Manage real-time operations: Human-machine interface systems eliminate the need for paper, files, and job tickets. This means that workers can analyze inventory and other data in real-time.
Save money: Although going paperless means that the cost of paper is eliminated, the savings extend beyond that. With greater productivity, operations in real-time, and improved production optimization, costs can be reduced in many areas.
How do you go paperless in manufacturing?
Going paperless starts with digitizing activities across the factory floor to increase productivity, and extending that value through a digital connection between the shop floor and enterprise manufacturing systems. We lay out below the four basic steps for how to go paperless in manufacturing:
Step 1: Digitize your existing content with Gen AI and Connected Worker technology.
Paperless manufacturing starts with the use of modern, digital tools that can quickly and easily digitize and convert your existing paper-based content. Tools like Augmentir’s Augie™, a generative AI suite of technologies, helps you import and convert existing content regardless of format. Once converted, Connected Worker solutions that incorporate enhanced mobile capabilities and combine training and skills tracking with connected worker technology and on-the-job digital guidance can deliver significant additional value. A key requirement to start is to identify high-value use cases that can benefit from digitization, such as quality control or inspection procedures, lockout tagout procedures, safety reporting, layered process audits, or autonomous maintenance procedures.
Pro Tip
You can now import existing PDF, Word, or Excel documents (just like the PDF above) directly into Augmentir to create digital, interactive work procedures and checklists using Augie™, a Generative AI content creation tool from Augmentir. Learn more about Augie – your industrial Generative AI Assistant.
Step 2: Augment your workers with AI and Connected Worker technology.
AI-based connected worker solutions can help both digitize work instructions and deliver that guidance in a way that is personalized to the individual worker and their performance. AI Bots that leverage generative AI and GPT-like AI models can assist workers with language translation, feedback, on-demand answers, access to knowledge through natural language, and provide a comprehensive digital performance support tool.
As workers become more connected, companies have access to a rich source of job activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist.
Step 3: Set up IoT sensors for machine health monitoring.
The industrial Internet of Things (IoT) uses sensors to boost manufacturing processes. IoT sensors are connected through the web using wireless or 4G/5G networks to transmit data right from the shop floor. The use of machine health monitoring tools along with connected worker technology can provide a comprehensive shop floor solution.
Step 4: Connect your frontline to your enterprise.
Digitally connected frontline operations solutions not only enable industrial companies to digitize work instructions, checklists, and SOPs, but also allow them to create digital workflows and integrations that fully incorporate the frontline workers into the digital thread of their business.
The digital thread represents a connected data flow across a manufacturing enterprise – including people, systems, and machines. By incorporating the activities and data from these previously disconnected workers, business processes are accelerated, and this new source of data provides newfound opportunities for innovation and improvement.
Augmentir provides a unique Connected Worker solution that uses AI to help manufacturing companies intelligently onboard, train, guide, and support frontline workers so each worker can contribute at their individual best, helping achieve production goals in today’s era of workforce disruption.
Our solution is a SaaS-based suite of software tools that helps customers digitize and optimize all frontline processes including Autonomous and Preventive Maintenance, Quality, Safety, and Assembly.
Transform how your company runs its frontline operations. Request a live demo today!
https://www.augmentir.com/wp-content/uploads/2023/09/paperless-manufacturing-augmentir.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-09-20 14:12:392025-06-04 13:02:43Paperless Manufacturing: Your Guide to Transitioning to a Paperless Factory
The benefits of digital work instructions go far beyond simply standardizing work. The real benefit is in personalized guidance and support for today’s workers.
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Digital work instructions are step-by-step directions on the best way to complete any task, from basic maintenance to fixing equipment. These digitized instructions are electronic versions of work procedures that are kept in a centralized system so workers can easily access them to work on tasks or to make timely decisions on projects. While the benefits of digital work instructions are numerous, the real benefit in manufacturing comes when digital work instructions can be personalized to the unique needs and skills of each worker.
So say goodbye to static documentation and hello to a new era of personalized digitization. If you’re interested in learning the real benefits of digital work instructions, read on about the following:
How digital work instructions are transforming manufacturing processes
Traditional instructions on paper can slow down a manufacturing operation. They can be lengthy, become quickly outdated, and are often full of mistakes. With paper-based reporting, for example, workers may forget to note the condition of equipment or update a faulty procedure.
Fortunately, digital instructions are an ideal solution. They offer visual demonstrations, how-to videos, and other resources for completing tasks. Most importantly, when digital work instructions are managed and delivered through a connected worker solution, they can be kept up-to-date to ensure compliance and product quality. According to Quality Magazine, not only do digital work instructions support overall enterprise productivity, but they also provide workers with an improved level of control over their work through enterprise data and automated insights.
When you digitize your procedures, they can be accessed and kept up to date from wherever employees work. They can be enhanced with visual aids, contextual information, and augmented reality experiences to guide workers through complex jobs. Best of all, workers are less likely to make mistakes or miss steps when they can easily refer to clear and visually engaging information.
Digital work instructions are maintained via a connected worker solution, and delivered through mobile or wearable devices on the shop floor. These solutions can be coupled with AI-powered software to further help companies digitize production procedures.
This leads to greater worker productivity and output.
The real benefits of digital work instructions
Digital work instructions provide countless advantages when implemented throughout your entire organization, including improved production processes, decreased downtime, greater operational competence and safety, as well as support for a centralized database of knowledge. On their own, they deliver standard work guidelines but fail to consider the unique skills of each worker, which is increasingly important in today’s evolving and labor-constrained workforce. The typical one-size-fits-all approach to managing, guiding, and supporting employees won’t cut it in today’s market.
Businesses need a solution that helps them improve manufacturing processes and meet their workers where they are.
This is where AI-based solutions come in.
Using AI-based connected worker solutions, organizations can digitize and easily manage skills tracking and training programs and connect them with frontline operations. Embedded AI can dynamically optimize work processes to deliver training in the flow of work, tailored support, and more. Solutions that combine skills tracking capabilities with connected worker technology and on-the-job digital guidance can deliver significant additional value. Data from actual work performance can inform workforce development initiatives allowing you to target your training, reskilling, and upskilling efforts where they have the largest impact.
It can generate an abundance of valuable data to provide tailored training support and skills endorsements and identify workforce opportunities. These benefits extend beyond simply standardizing work to include:
1. A more motivated, more engaged workforce
An organization’s commitment to cultivating its team’s skills can influence their attitudes toward the job. A worker is likelier to perform better when valued and appreciated. Digitized skills tracking also ensures that workers are qualified to perform their job.
2. Mitigate risk and ensure safety
Solutions that include personalized work instructions that incorporate worker skills allow organizations to validate at the time of work assignment who has the skill level to safely perform a specific task. This helps to mitigate risk and ensure safety.
3. Intelligently assigning work
Ensure the right person is assigned to the right job. Manage work assignments based on skill level, endorsements, and actual job performance.
4. Closes the skills gap
Tracking skills is a great way to identify gaps between the skills employees already have and the skills they need. With this information, the company can arrange for additional training or other ways to invest in their employees. Keep in mind that as your manufacturing organization evolves and grows, so should your employee skillset.
6. Identify upskilling or reskilling opportunities
Use data from actual work performance, combined with an employee’s current skills and endorsements to inform your reskilling and upskilling decisions. Knowing where improvements need to be made can close any learning gaps and boost the overall success of a company. Optimizing your workforce can help improve productivity in every department, giving your company a competitive edge in today’s market.
Connected worker solutions that combine skills management with digital work instructions, collaboration, and knowledge management are uniquely suited to optimize today’s variable workforce. AI-generated insights are pulled from patterns identified across all work activity in real-time. These insights identify where new and experienced workers may benefit from either reskilling or upskilling.
This combination of smart digital technology can also leverage your training resources, such as instructional videos, written instructions, or access to remote experts, to deliver personalized guidance for the worker to perform their best. These tools intelligently work together to help you assign workers to procedures based on required skill levels.
FAQs about digital work instructions
What is the purpose of digital work instructions?
Digitized work instructions provide clear, step-by-step directions on how each manufacturing task should be performed. They are kept in a centralized database for real-time view of procedures, how-to videos, training opportunities, and more. Companies implement them in order to improve workers’ procedural knowledge, ensure standard work compliance, reduce mistakes, and raise production quality overall.
How can digital work instructions help manufacturers?
Digital work instructions help manufacturers create a more productive workforce that values detail, quality, and learning. Work instructions can be updated to fit best practices, reduce human error, and provide learning opportunities with visual cues like videos, pictures, augmented reality experiences, and more.
Which work instruction software is right for me?
Although there are different software programs out there, Augmentir is the world’s leading connected worker solution, and the only solution that uses AI to personalize instructions based on individual worker proficiency and skill levels.
How Augmentir’s digital solutions can help
Digitizing work instructions is a great start to address manufacturing issues, however, alone, it won’t help completely solve some of the biggest workforce challenges. It’s not enough to simply move from paper-based to digital work instructions.
We must go a step further, for example, Augmentir’s platform provides complete digital workflow authoring tools that allow you to not only quickly convert your paper-based processes to digital work instructions, but also use AI to dynamically personalize them to the needs of your individual workers.
Digital work instructions, augmented with visual aids, contextual information, and industrial collaboration tools, help intelligently guide workers through complex jobs
Complete workflows allow you to digitize complex business processes
Embedded AI dynamically optimizes work procedures and workflows to deliver in-situ training and support
https://www.augmentir.com/wp-content/uploads/2023/09/benefits-of-digital-work-instructions-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-09-14 17:03:262025-06-04 13:01:35The Real Benefits of Digital Work Instructions in Manufacturing
