Learn how to write manufacturing SOPs and the benefits of having standard operating procedures in a manufacturing operation.

Standard operating procedures, or SOPs, will change the way you run your manufacturing operations.

SOPs are imperative to a properly organized management structure. They are step-by-step guidelines workers must follow when carrying out tasks to standardize work and are designed to meet industry regulations.

Essentially, they provide general info about assignments, including the tools, methods, or machinery needed to complete projects. SOPs indicate what the task is, who will perform it, how it should be completed, and when it should be completed.

manufacturing sop

For example, manufacturers may write SOPs for employee training to reduce risk and injury. Leadership may also use procedures to assign goals and measure employee performance.

Read on to find out more about the benefits of manufacturing SOPs and how to write them by exploring the following topics:

Advantages of Implementing Standard Operating Procedures

According to Forbes, a comprehensive SOP keeps workers on the same page and improves efficiency and accuracy. Without documented procedures, there is no way to set proper standardized processes and workers might try to complete jobs in non-standard methods, which leads to disruptions in the production processes and causes all sorts of quality issues in a manufacturing environment. Thankfully, SOPs work to prevent that from happening.

Some of the advantages of using SOPs include:

  • Meets regulatory compliance: Product inspectors constantly ask to review SOPs when conducting audits. These serve as the point of reference for whether specific measures followed meet industry guidelines.
  • Standardizes tasks: The point of written procedures is to establish a standard way of completing tasks. They enable tasks to be performed in the same way across the company.
  • Improves accountability and tracking: SOPs define who is responsible for a work order, maintenance check or inspection. This reporting can improve accountability across departments. If a task wasn’t completed accordingly or a procedure was missed, management can take necessary steps to prevent it from happening again.
Pro Tip

Digitized SOPs can further improve tracking and traceability features, helping manufacturers comply with regulations and quality standards. With digital SOPs it becomes easier to maintain records of every step in the production process, including who performed each task and when.


How to write a manufacturing SOP

Writing a comprehensive set of SOPs can help workers perform tasks in the safest and most efficient way possible. Although there isn’t an official way to write procedures, you can follow certain steps to make them more effective:

Step 1: Establish a goal.

It’s important to think about what you want your SOP to accomplish. Regardless if you’re starting a new process or improving an existing one, figuring out the end goal will make it easier to complete the document.

Step 2: Pick a format.

There are different formats you can use to write your document: step-by-step, hierarchical, narrative, etc. We recommend the sequential step-by-step format for its straightforwardness.

Step 3: Write the procedures.

Make sure your procedures are clear, concise, current, consistent, and complete.

Step 4: Review and update.

It’s important to review your SOP for any discrepancies and update them if necessary. Consider asking fellow leaders knowledgeable in procedure creation to read them over.

Why SOPs are Important in Manufacturing

Compliance with manufacturing SOPs is crucial for a number of reasons, including:

  • Prevents accidents and ensures worker safety
  • Promotes worker consistency
  • Improves product quality
  • Protects your business’s reputation

SOPs are a critical component of manufacturing operations because they provide a structured framework for achieving consistent quality, safety, and efficiency in the production process. They help manufacturers meet regulatory requirements, reduce errors, and ensure that employees are trained to perform tasks consistently and safely.

Digitizing Manufacturing SOPs with Connected Worker Solutions

Using connected worker technologies to create digital SOPs can significantly improve their impact on manufacturing by enhancing accessibility, effectiveness, and overall utility.

Through digitization and smart, connected worker technology manufacturers can improve SOPs with features like real-time access, remote collaboration and guidance, data-driven insights, workflow automation, enhanced training, traceability and compliance, and more. Essentially, with these advanced technologies, manufacturing organizations can augment and support their workers with optimized processes and SOPs creating an environment of continuous improvement.

Augmentir offers customized AI-powered connected worker solutions that transform how you write and create manufacturing standard operating procedures. Request a live demo today to learn more about why leading manufacturers are choosing our solutions to improve their manufacturing processes.



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Learn how continuous and workflow learning can help modernize employee training in the manufacturing industry.

Staying ahead of the curve in today’s manufacturing marketplace means that businesses need to innovate and adapt. To accomplish this, organizations must have a skilled workforce and ongoing training and workforce management processes to support continuous learning and development.

Modernizing training cultivates employee skillsets by implementing continuous learning in the flow of work.

modernize manufacturing training with continuous learning

Continuous learning is the process of attaining new skills on a constant basis. Workflow learning involves educating yourself on the job using resources and self-directed learning materials. Done together, this modern training approach can help streamline productivity.

If you want to learn how to improve manufacturing training with continuous learning and workflow learning, explore this article that answers the following:

What is continuous learning?

Continuous learning in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation. According to Forbes, embracing a culture of continuous learning can help organizations adapt to market demands, foster innovation, as well as attract and retain top talent.

Learning can come in different forms, from formal course training to hands-on experience. Employees are encouraged to be self-starters who want to evolve their skills on an on-going basis. A good example of a continuous learning model is everboarding; everboarding is a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

How can continuous learning be used in manufacturing?

When businesses don’t support continuous learning, manufacturing processes stagnate. This contributes to a lack of innovation and hinders potential opportunities for success that a company may experience.

In a nutshell, the more workers know and the more they can accomplish, the more they can contribute to business growth. This may consist of employees taking an online course or learning a new technique hands-on, no matter what department they’re in.

For example, assembly line workers may learn new manufacturing processes to ensure everything is functioning properly. Meanwhile, operators may study the latest machinery to learn new tricks of the trade.

What is workflow learning?

Workflow training in manufacturing involves learning while doing. This means that workers pick up new skills while on the job through hands-on experience.

The key to workflow learning is that it happens while employees perform their everyday tasks.

Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions. With workflow learning, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially bridging the gap between knowing and doing. This “active learning” aligns with the Pyramid of Learning visual model that illustrates the different stages of learning and their relative effectiveness.

pyramid of learning

Active learning involves the learner actively engaging with the material, often through problem-solving, discussion, or application of the knowledge while they are on the job.

In general, active learning is considered more effective than passive learning in promoting deep understanding and retention of information. Therefore, learning leaders often strive to design learning experiences that involve higher levels of active learning, moving beyond the lower levels of the pyramid and promoting critical thinking, creativity, and problem-solving skills.

How can workflow learning be used in manufacturing?

Workflow learning consists of using resources at your disposal to complete tasks. This strategy is sometimes referred to as performance support.

For example, workers can look up answers to questions, steps of a process, or new services while performing their jobs instead of interrupting their workflow to go to a class or training session.

Pro Tip

Active, or workflow learning can be implemented with mobile learning solutions that leverage connected worker technology and AI to provide workers with bite-sized, on-demand training modules that they can access on smartphones or tablets. These modules can be developed with customized learning paths that are focused on the type of tasks and work employees are doing on the factory floor.


How can technology improve manufacturing training?

The nature of manufacturing training is changing in the age of artificial intelligence. Today, many training processes can be streamlined and optimized using digital and smart, connected worker technologies.

For instance, data collected from everyday manufacturing processes can polish training programs online. Experienced workers can share best practices on customized dashboards for other employees to access. These can be updated in real-time and show changes highlighted to better optimize manufacturing processes.

Digital training tools can also help improve learning speed and retention. For example, workers who need visuals or real-world scenarios can assess them using AI-powered software to maximize their training.


Augmentir is the world’s leading AI-powered connected worker solution that helps industrial companies optimize the safety, quality, and productivity of the industrial frontline workforce. Contact us for a live demo, and learn why leading manufacturers are choosing us to elevate their manufacturing operations to the next level.


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Learn about performance management in manufacturing, best practices and implementation methods, and key examples and use cases.

Manufacturing performance management is the process of setting, monitoring, and optimizing key performance indicators (KPIs) related to production processes and workforce performance in manufacturing environments. It includes real-time monitoring and evaluation of employees’ work, as well as the continuous improvement of operational workflows to ensure optimal efficiency, product quality, and adherence to both safety requirements and organizational goals.

performance management in manufacturing best practices

Through data-driven insights, performance management software, and regular assessments, performance management aims to enhance employee productivity, reduce downtime, and maintain a competitive edge in the industry. Read our blog post below to learn more about performance management in manufacturing including:

5 Best Practices for Performance Management in Manufacturing

To get the best value from your performance management system here are five best practices for performance management in manufacturing:

1. Clear Goal Alignment:

Organizations must ensure that performance management processes align with overall organizational goals. They must clearly communicate objectives to employees at all levels, linking individual and team performance metrics to broader manufacturing and business objectives. This fosters a sense of purpose in frontline teams, engages workers, and helps employees understand how their efforts contribute to the company’s success.

2. Real-time Monitoring and Data Analytics:

Implement real-time monitoring of production and shop floor processes and equipment performance through the use of AI and connected worker technology. Utilize data analytics and AI-driven processing to gain insights into worker performance trends, identify bottlenecks, and facilitate data-driven decision-making. The ability to monitor operations in real-time not only enables proactive interventions to maintain efficiency, it also ensures fairness, accuracy, and transparency in performance measurement.

Pro Tip

Performance management software in manufacturing is crucial for optimizing production efficiency, and should integrate with other manufacturing systems, such as Learning Management Systems (LMS), Enterprise Resource Planning (ERP), and Manufacturing Execution Systems (MES), to provide a holistic view of the entire manufacturing operation.


3. Employee Training and Development Programs:

Prioritize ongoing training and development programs for manufacturing personnel. Equip frontline workers with the necessary skills to adapt to evolving technologies and operational requirements. Use performance management systems and other digital tools like skills matrixes to identify skill gaps, set training goals, and track progress, ensuring a skilled and adaptable workforce.

4. Regular Performance Reviews and Feedback:

Conduct regular performance reviews that provide constructive and timely feedback to employees. Use these reviews as opportunities to recognize achievements, address areas for improvement, and set new performance goals. Foster open communication between managers and employees to encourage continuous improvement.

5. Integration with Continuous Improvement Initiatives:

Integrate performance management systems with “kaizen” or continuous improvement initiatives such as Lean or Six Sigma. Use data from performance metrics to identify opportunities for process optimization, waste reduction, and efficiency improvements. This ensures that performance management is not only evaluative but actively contributes to the ongoing enhancement of manufacturing processes.

Leveraging these best practices contributes to a holistic performance management process that aligns manufacturing organizations and their frontline workforce with strategic goals, optimizes operations, and creates a culture of continuous improvement.

Key Performance Management Strategies for Manufacturing Leaders

The following are a few examples of performance management strategies that manufacturing leaders, plant managers, and shift supervisors should consider when implementing their performance management process.

Line-shift Goals

Manufacturers often use production planning and scheduling systems to manage line shifts effectively and ensure a smooth transition between different production configurations. While line shifts in manufacturing are often necessary for adapting to changing demands, introducing new products, or optimizing efficiency, they can also pose challenges, including downtime, quality control issues, employee fatigue, and planning issues. By establishing clear and measurable objectives for each line shift or individual worker that aligns with organizational goals, production leaders can ensure production goals are met.

Individual Meetings and Communication

Manufacturing leaders should implement a performance management strategy that incorporates 1-1 meetings and communication. Regularly providing constructive feedback to employees on their performance can improve performance and boost employee engagement. Offering coaching and development opportunities to enhance skills and capabilities.

Continuous Training

Continuous training in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation, as well as engage and retain top talent. A good example of a continuous learning model is everboarding, a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

Performance Management Tools

Implementing performance management tools can help automate ongoing employee evaluation, as well as align employee performance with other key manufacturing KPIs, including production quality, machine uptime, and labor utilization. These tools can also be used to identify continuous improvement opportunities. This allows manufacturing leaders to adapt and refine approaches based on feedback and outcomes.

Simplifying Performance Management with Digital Tools

According to Forbes, as the future of work evolves and changes so must performance management, traditional methods may no longer be as successful in an era where the workforce is constantly changing.

Digital tools such as connected worker solutions and AI-driven analytics help simplify performance management systems by streamlining processes, improving efficiency, and providing more accurate insights. Implementing these connected worker solutions automates the collection of performance-related data from various sources including connected frontline workers, IoT devices, software systems, and more. This eliminates the need for manual data entry, reducing errors and ensuring real-time access to up-to-date information.

By digitizing the performance management process, organizations create a centralized platform for storing and managing performance-related data. This centralized knowledge base makes it easy for managers and employees to access relevant information, track progress, and collaborate on performance goals. Furthermore, AI-driven connected worker solutions allow for digital performance tracking, customized training and skills development planning, workflow optimization, and improved predictive maintenance.

digital skills management in a paperless factory

Through these digital tools and technology, manufacturing companies can simplify performance management processes, improve operational efficiency, and adapt to the demands of a rapidly evolving industry while fostering a culture of continuous improvement and development for their manufacturing workforce.

Augmentir is the world’s leading connected worker solution, combining smart connected worker and AI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.

Augmentir is trusted by manufacturing leaders as a digital transformation partner improving training and development, workforce allocation, and operational excellence through our AI-driven True Productivity™ and True Performance™ offerings, as well as digitizing and optimizing complex workflows, skills tracking, and more through our patented smart, connected worker suite. Schedule a live demo today to learn more.


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Learn why integrations are key to the success of connected worker platforms, what systems should be integrated, and the benefits of a fully integrated connected worker solution.

Unlocking the potential of connected worker platforms becomes a game-changer when integrated with enterprise systems, giving them a live, closed loop connection to frontline processes and operations. This creates a truly connected enterprise that links diverse systems with the frontline workforce, paving the way for heightened efficiency, productivity, and safety.

connected worker platform integrations

However, a majority of connected worker platforms overlook the fact that connectivity doesn’t end with simply linking workers to their platform. They fail to recognize the immense benefits that live connections to enterprise systems of record bring to frontline business processes and activities.

Manufacturing success hinges on the seamless integration of connected worker platforms with legacy and enterprise systems to provide adequate support to frontline workers, giving them access to data and knowledge that can boost their efficiency and keep them safe.

Read below for more information on connected worker platform integrations; what they entail, which enterprise systems are essential for integration, and how AI-powered technology improves impact on frontline manufacturing activities.

Connected Worker Integrations: More than just an API

In manufacturing, it is critical that connected worker platforms are integrated with various enterprise systems to streamline operations and ensure that workers have the data and information they need at their fingertips. As critical as this is, most connected worker vendors believe that providing an open API is sufficient, and even boast that they integrate to enterprise systems, when in fact they place this burden on their customers.

Having an API is not enough

There are several not-so-obvious aspects to connected worker platform integrations, including:

  • Connected worker integrations with enterprise applications, even streamlined ones, have essential requirements such as logic that needs to be written, customized, run, and supported. Most, if not all, of this logic is initiated by the connected worker platform, propagating events and data from shop floor processes to the associated enterprise system of record.
  • Connected worker platforms with just an “API” require all of this functionality to be developed, hosted, and supported externally. The responsibility is then on the customer to build a custom product and select and support the hosting environment. This effort (building, hosting, and support) can cost between $50K and $150K to build and test, and then another $50K – $150K annually for 5 x 9 support. And, the customer is responsible for maintaining an SLA acceptable to the business (99.9% being typical).
Pro Tip

It’s critical that connected worker platforms include “platform-as-a-service” (Paas) capabilities that provide the ability to write, support, and execute both standard and custom integrations. These can be done by the platform provider, the customer, as well as third-party system vendors and system integrators. Providing PaaS capabilities puts the responsibility on the vendor for operating the integration service, and maintaining SLAs, geo-redundancy, disaster recovery, and privacy and security. In short, just saying “we have an API” places an undue burden on customers, and prevents building the sustainable connected enterprise necessary to remain competitive in today’s global economy.


Which Enterprise Systems Should You Integrate

In any industrial environment, connected worker platforms should be integrated with various systems to support operations, help with cooperation and communication, and gain valuable insights into frontline manufacturing processes. These integrations streamline activities, improve efficiency, and provide a unified digital environment that empowers frontline workers.

This concept of a connected enterprise spans several initiatives within an organization: assets and equipment, the products being manufactured, the end customer, operations, workers, and the entire supply chain, and is highlighted below using the Industrial Transformation (IX) Reference Architecture from LNS Research.

connected worker enterprise system integration

Examples of enterprise management systems of record that are key to connected worker success and should be integrated are:

  • ERP (Enterprise Resource Planning)
  • EAM (Enterprise Asset Management)
  • HCM (Human Capital Management)
  • HR, Training, and LMS (Learning Management System)
  • QMS (Quality Management Systems)
  • MES (Manufacturing Execution System)
  • CMMS (Computerized Maintenance Management System)
  • Supply Chain Management

Enterprise systems such as ETQ, Workday, UKG, SAP, Oracle, IBM Maximo, Microsoft Dynamics 365, Salesforce, and ADP provide transformational value for a manufacturing company if they can be connected into frontline operations. By integrating connected worker platforms with these systems, manufacturers can create an interconnected environment that supports frontline workers and drives operational excellence. Ultimately, integration enhances collaboration, workforce visibility, decision-making processes, and overall operational efficiency, making connected worker platforms an indispensable component for manufacturing organizations.

Improving Integration Success Through Augmentir

At Augmentir, we see integrations differently than other connected worker platforms. Our rich history of building integrations in the manufacturing space enabled us to design a connected worker solution that easily, bi-directionally, and securely integrates the enterprise systems of record to create closed loop processes involving the frontline workforce.

Augmentir has internal PaaS services to run connectors that we build and support for popular enterprise applications like SAP, Salesforce, ETQ, Oracle, IBM Maximo, and more. Additionally, our PaaS enables custom integrations to be built and executed for custom, and niche applications. All third-party integrations running in the Augmentir connected worker platform carry the same SLA and geo-redundant support. By facilitating connected worker platform integrations with enterprise systems in this way, we have provided leading manufacturers with increased workforce visibility, improved productivity, digitized and standardized processes, enhanced training and collaboration, and more.

augmentir enterprise integration

Furthermore, because we are the leading AI-powered connected worker provider, we have brought innovative generative AI technologies such as AI-driven analytics, machine learning algorithms, NLP, predictive maintenance, and industrial AI copilots to improve connected worker integrations with enterprise systems, providing real-time guidance, enabling predictive analysis, and enhancing communication and collaboration among workers.

Schedule a demo to learn more about our AI-powered connected worker solutions and how they are drastically improving frontline processes, training, and manufacturing activities.


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Say hello to the newest addition to the Augmentir platform, Augie – the GenAI powered digital assistant for manufacturing.

Say hello to the future of work in manufacturing with the latest addition to Augmentir’s suite of connected worker tools, Augie™.

augie generative ai assistant for manufacturing

Augie is a digital assistant for frontline operations that utilizes Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) to enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. It leverages enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.

Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.

Continue reading below to learn more about how Augie works and how it can benefit your frontline workforce and manufacturing operations:

How our GenAI Powered Assistant Works

Generative AI-powered smart manufacturing assistants are designed to provide secure, role-based, personalized assistance to frontline workers, engineers, and managers in various industries, including manufacturing.

They work by leveraging artificial intelligence and integrations across different software systems, providing guidance and assistance in various tasks to enhance productivity and performance. This includes providing data insights, recommendations on actions to improve performance, and the ability to create analyses and dashboards with a natural language-based assistant.

A majority of smart manufacturing assistants only draw their information from manufacturing execution systems (MES), without tying in other important systems necessary for frontline manufacturing success.

Augie, however, is different. It leverages enterprise-wide data tying in information from a wide range of platforms including operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.

gen ai industrial manufacturing

How Augie Benefits Your Frontline Workforce

Augie is unique among other smart manufacturing assistants. It leverages proprietary fit-for-purpose, pre-trained LLMs and generative AI, coupled with robust security and permissions, to help factory managers, operators, and engineers improve efficiency, resolve issues faster, and prevent downtime.

With information readily available via Augie, frontline workers can make decisions faster, reduce downtime, and improve troubleshooting with instant access to summarized facts relevant to a job or task. Additionally, Augie is multi-modal, meaning it can return actionable information in the form of work procedures, training videos, recorded collaborations, engineering documents and SOPs, as well as tribal knowledge.

Through Augie, manufacturers can instantly:

  • Close skills and experience gaps with personalized support
  • Gain insights into Leader Standard Work
  • Gain new insights into skills inventories
  • Convert Tribal Knowledge into Digital Corporate Assets
  • Identify opportunities for continuous improvement
  • Forecast potential operational issues

augie gen ai industrial assistant troubleshooting

With Augie by your side, you can streamline manufacturing operations, optimize performance, empower your frontline workforces, and stay ahead in today’s rapidly evolving and competitive landscape.


6 Ways Manufacturers Can Use GenAI Today



Improve Operational Efficiency with Augie and Augmentir

The digitization of frontline processes has become a must-have to keep up with the velocity of change – but not just digitization … smart digitization. Recently, Deloitte found that 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness in the next five years. Leveraging smart, AI-driven connected worker solutions that allow industrial organizations to best support their frontline workforces and optimize processes to make them safer and more efficient is critical to overall enterprise success.

At Augmentir, we have been met with continued success in our efforts to transform manufacturing operations. Our patented Smart AI foundation helps manufacturing organizations close the loop between training and work execution, delivering the data and in-line insights necessary to continuously improve operational excellence day-over-day, year-over-year. Augmentir is the world’s leading connected worker solution, combining smart connected worker and GenAI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.

The addition of Augie to our platform is a game-changer for factory floor and other frontline workers, allowing for quick reference troubleshooting and useful, contextualized information to be delivered at the moment of need. Furthermore, with Augie, less experienced workers are provided with additional support and individualized guidance based on the job or task needs.

With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.


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The evolution of AI in manufacturing has seen tremendous growth over the past few decades, now becoming more adaptive and collaborative, and being used to augment and directly support frontline workers.

The evolution of artificial intelligence and machine learning technologies in manufacturing has seen tremendous growth over the past few decades, with astounding leaps in technology and industry-wide transformations.

evolution of ai in manufacturing

Dating back to the 1960’s, manufacturers started using AI in robotics and basic automation. This early usage focused on automating manual, highly repetitive human tasks such as assembly, parts handling, and sorting, allowing for higher levels of production and efficiency.

Over time, this evolved with AI-enabled machine vision systems, which were used to automate visual inspections, allowing for better quality control and precision during production cycles. More recently, AI has been at the center of warehouse automation, as well as the Industrial Internet of Things (IIoT), where physical machines and equipment are embedded with sensors and other technology for the purpose of connecting and exchanging data, which is used in predictive analytics for machine health monitoring. Manufacturers can now glean valuable insights from data collected over time about optimizing their operations for maximum efficiency without sacrificing quality.

Despite the breath of applications that AI has in the industrial setting, there is a common thread across all of the above examples – AI has largely been used to automate highly repetitive or manual tasks, or perform functions designed to replace the human worker.

However, these examples laid the groundwork for the adoption of AI in manufacturing and for the use of AI technologies that augment and directly support frontline workers today.

Read below for more information on how the use of AI and GenAI is evolving in manufacturing, and being used to augment the human worker, transforming productivity and efficiency at a time when workforce optimization is needed most.

Using AI to Augment, not Replace the Workers in our Factories

Today, AI technologies in manufacturing have evolved to encompass a diverse range of applications. According to Deloitte, 86% of surveyed manufacturing executives believe that AI-based factory solutions will be the primary drivers of competitiveness in the next five years. Robotics and automation have become more adaptive and collaborative, working alongside and augmenting human workers to streamline production processes and increase efficiency – rather than simply trying to replace them.

As computing power and algorithmic capabilities improved, AI in manufacturing has become more advanced and widespread. The emergence of Industry 4.0, characterized by the convergence of digital technologies, further accelerated AI’s role in manufacturing. By leveraging tools like connected worker solutions to gather frontline data, manufacturing organizations can now capitalize on AI’s extraordinary computing power to analyze that data and derive actionable insights, improved processes, and more.

Much like the industry has learned to optimize equipment from the 1.7 Petabytes of connected machine data that is being collected yearly, we are now able to optimize frontline work processes and people from highly granular connected worker data, with one major caveat: In order to leverage this incredibly noisy data, a system has to be designed with an AI-first strategy, where the streaming and processing of this data is intrinsic to the platform – not added as an afterthought.

The potential for AI to help augment the human worker is there, but why now?

Because for today’s manufacturers, time is not on your side.

The workforce crisis in manufacturing is accelerating, and at the forefront of the minds of Operations and HR leaders. Job quitting is up, tenure rates are down, and manufacturers struggle daily to find the skilled staff necessary to meet production and quality goals. The threat is huge – with significant impacts to safety, quality, and productivity.

AI-based connected worker solutions allow industrial companies to digitize and optimize processes that support frontline workers from “hire to retire”. These solutions leverage data from your connected workforce to optimize training investments and proactively support workers on the job, across a range of manufacturing use cases.


paperless factory

Furthermore, solutions that leverage Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) can enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. Generative AI assistants can leverage enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.

Augmentir’s AI-First Journey

At Augmentir, since the beginning, we pioneered an AI-first approach toward manufacturing and connected frontline worker support. 

augmentir's ai-first journey

Many manufacturing solutions incorporated AI technology as an add-on or afterthought as the technology gained more advanced capabilities and popularity. We, however, have been championing and building a suite of solutions using AI as a foundation. Our platform was designed from the bottom up with AI capabilities in mind, placing us as a leader in the connected frontline worker field. 

  • 2019 – Augmentir launched the world’s first AI-first connected platform for manufacturing work empowering frontline workers to perform their jobs with higher quality and increased productivity while driving continuous improvement across the organization. This marked the start of our AI-first journey, giving industrial organizations the ability to digitize human-centric work processes into fully augmented procedures, providing interactive guidance, on-demand training, and remote expert support to improve productivity and quality.
  • 2020 – Augmentir unveiled True Opportunity™, the first AI-based workforce metric designed to help improve operational outcomes and frontline worker productivity through our proprietary machine learning algorithms. These algorithms take in frontline worker data, then combine it with other Augmentir and enterprise data to uncover and rank the largest capturable opportunities and then predict the effort required to capture them.
  • 2021 – Building on user feedback and field data, Augmentir reveals True Opportunity 2.0™, with improved and enhanced capabilities surrounding workforce development, quantification of work processes, benchmarking, and proficiency. By Leveraging anonymized data from millions of job executions to significantly improve and expand the platform’s ability and automatically deliver in-app AI insights we were able to increase benefits and returns for Augmentir customers.
  • 2022 – Augmentir announces the release of True Productivity™ and True Performance™. True Productivity allows industrial organizations to stack rank their largest productivity opportunities across all work processes to focus continuous improvement teams at the highest ROI and True Performance determines the proficiency of every worker at every task or skill enabling truly personalized workforce development investments.
  • 2023 – Augmentir launches Augie™ – the GenAI-powered assistant for industrial work. By incorporating the foundational technology underpinning generative AI tools like ChatGPT, we enhanced our already robust offering of AI insights and analytics. Augie adds to this, improving operational efficiency and supporting today’s less experienced frontline workforce through faster problem-solving, proactive insights, and enhanced decision-making.
  • 2024 – As this year progresses, we have already continued to refine our AI-first solutions and apply user feedback and additional features to best support frontline industrial activities and workers everywhere.
  • 2025 and beyond – True Engagement™, looking forward we predict the evolution of AI in manufacturing activities will continue, progressing until we can accurately measure signals to detect the actual engagement of industrial workers and derive useful information and insights to further enhance both HR and manufacturing processes.

We are deeply involved in applying AI and emerging technologies to manufacturing activities to augment frontline workers, not replace them. Providing enhanced support, access to key knowledge (when and where it does the most good), and improving overall operational efficiency and productivity.

The Future of AI in Manufacturing – The Journey Forward

As we press onward into the future, we at Augmentir are determined to champion the application of AI and smart manufacturing to augment and enhance frontline workers and industrial processes. We will continue to evolve our application of AI and its use cases in manufacturing to help frontline teams and workforces, reinforcing our AI-first pedigree.

The addition of Augie to our existing AI-powered connected worker solution is an important step forward. Augie is a Generative AI assistant that uses enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement. Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.

With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.


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AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data, and personalized instruction.

Deloitte recently published an article with the Wall Street Journal covering how AI is revolutionizing how humans work and its transformative impact. They emphasized that AI is not merely a resource or tool, but, that it serves almost as a co-worker, enhancing work processes and efficiency. This article discussed how the evolving form of intelligence augments human thinking and emphasized this as a catalyst for accelerated innovation.

Manufacturing is uniquely situated to benefit from AI to improve operations and empower their frontline workforces. The skilled labor gap has reached critical levels, and the market is under tremendous stress to keep up with growing consumer demand while staying compliant with quality and safety standards. Manufacturing workers are crucial to the success of operations – maintenance, quality control and assurance, and more – manufacturers rely upon their workforce to ensure production proceeds smoothly and successfully.

AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data for informed decision-making, troubleshooting, personalized instructions and training, and improved quality assurance and control. According to the World Economic Forum, an estimated 87% of manufacturing companies have accelerated their digitalization over the past year, the IDC states 40% of digital transformations will be supported by AI, and a recent study from LNS Research found that 52% of industrial transformation (IX) leaders are deploying connected worker applications to help their frontline workforces. Not only that, AI technology is expected to create nearly 12 million more jobs in the manufacturing industry.

Integrating AI into manufacturing not only enhances productivity, but also opens the door to new possibilities for worker safety, training, and innovative new manufacturing practices. Here are some ways AI is transforming manufacturing operations:

  • AI-based Workforce Analytics: Collecting, analyzing, and using frontline worker data to assess individual and team performance, optimize upskilling and reskilling opportunities, increase engagement, reduce burnout, and boost productivity.
  • Personalized Training in the Flow of Work: With AI and connected worker solutions, manufacturers can identify and supply training at the time of need that is personalized to each individual and the task at hand.
  • Personalized Work Instructions: AI enables manufacturers to offer customized digital work instructions mapped to their skill levels and intelligently assign work based on each individual’s capabilities.
  • Digital Performance Support and Troubleshooting Guide: Generative AI assistants and bot-based AI virtual assistants offer support and guidance to manufacturing operators, enabling access to collaborative technologies and knowledge bases to ensure the correct actions and processes are taken.
  • Optimize Maintenance Programs: AI algorithms analyze data from sensors on machinery and other connected solutions to predict when equipment is likely to fail. This enables proactive maintenance, minimizing downtime and reducing maintenance costs. Additionally, with AI technologies, manufacturers can implement autonomous maintenance processes through a combination of digital work instructions and real-time collaboration tools. This allows operators to independently complete maintenance tasks at peak performance.
  • Improve Quality Control: AI-powered solutions can improve inspection accuracy and optimize quality control and assurance processes to identify defects faster. With connected worker solutions, manufacturers can effectively turn their frontline workforce into human sensors supplying quality data and enhancing assurance processes.
  • Ensure Worker Safety: AI-driven safety systems coupled with connected worker technologies monitor the work environment, supplying real-time data and identifying potential hazards to ensure a safer workplace for employees.

connected enterprise

As AI continues to advance, the manufacturing industry is poised for even greater transformation, improving both the quality of products and the working conditions for employees. AI is revolutionizing the way humans work and how the manufacturing industry approaches nearly every process across operations, augmenting work interactions, productivity, efficiency, and boosting innovation.

AI-powered technology may be the missing puzzle piece for today’s workforce crisis.

It wouldn’t be fair to attribute all of manufacturing’s current labor shortage woes to the pandemic–there are a lot of factors contributing to this frustrating situation, and many of them were looming long before we ever heard of COVID-19. Did it make things worse? Probably. And the forecast doesn’t look very sunny if you believe what analysts have to say about it. However, despite the current crisis, there is hope yet for manufacturing, specifically in the form of AI and Connected Worker Technology.

Sure, the face of the workforce has changed dramatically. The pool of potential laborers has shrunk. Businesses are being forced to hire people traditionally considered under-qualified. And that leads to a whole host of other complications, including a drop in operational efficiency, a rise in safety issues, and more. The pessimists out there would only see the threat to the global market these challenges pose–the manufacturing industry makes between 11 and 12 percent of the US economy after all.

Good thing we’re optimists at heart! Behind every challenge is an opportunity, as far as we’re concerned. And when it comes to this challenging labor market in particular, we see a huge opportunity for businesses to work with what they’ve got, and still reach operational goals. We have the potential to assess how every worker performs on the job, regardless of the experience and skill set they bring on day one, and use that information to improve individual and enterprise-wide performance. Puts a new light on the labor shortage, doesn’t it?

You can’t fix what you can’t see.

We know using data is important to directing and improving operations–that’s business best practices 101. But insights drawn are only as good as the data itself. And even though there can’t be many businesses out there who haven’t yet jumped on the digital transformation bandwagon, we suspect a lot still rely on outdated data collecting and reporting mechanisms. Those digital spreadsheets had their moment, but we’ve got better options now. Maybe you opted for a Bluetooth software program or distributing a digital survey for your workers. But even with those innovations, what do these data indicators really tell you? Is this reliable and usable information? We didn’t think so either.

Imagine what you could do with real-time data, rather than a summary of operational KPIs at the end of set periods? Even better–imagine capturing the performance metrics of each individual worker rather than their self-generated assessments and observations and having the potential to use that knowledge to improve their skill set and operational proficiency. That’s when data becomes intelligence. And that intelligence has the potential to become so valuable to your enterprise that you’ll wonder how you ever operated without it.

Not convinced you could benefit from data at that level of individual performance? Let us draw an analogy we think you’ll appreciate.

Think of each worker as a newly licensed driver; what happens after passing the road test?

Remember the day you got your driver’s license? We spent hours, if not days and weeks practicing behind the wheel, eagerly waiting to be evaluated by a driving instructor. And let’s be honest, plenty of us winged it, too. Either way, once you show them you can do a three-point-turn and know to stop at the flashing pedestrian crossing sign, everyone walks away with the proof of their proficiency–a driver’s license. 

Then what happened? Nothing. Maybe a celebratory high-five and then eventually years of driving. In one, five, or ten years, what do we know about each person’s capabilities? Unless they’ve wracked up a stack of tickets for traffic violations, we don’t know anything. For all we know, they haven’t sat behind the steering wheel since passing. There is no mechanism to re-assess whether drivers are highly skilled or at-risk of creating an accident in operations.

Now what if we looked at our frontline workers through that lens? You know when they were hired that they could perform X, Y and Z. Some could do even more. But what about after that? What if you could assign an AI-based driver instructor to follow each new driver around for ongoing assessment and intervention in the moment of need?

Put smart connected worker technology in the passenger seat

Adopting connected worker technology powered by artificial intelligence (AI) increases the reliability and credibility of data by analyzing employee performance in ‘real-time.’ That individualized data can be used to connect workers with a company’s digital library of training tools and resources, having an immediate impact on operational proficiency and cultivating a healthy learning environment for workers.

Connected worker technology that leverages AI offers self-guided learning processes when opportunities are identified, reduces human error and improves safety, provides updates on pressing issues and equipment failures and access to a variety of applications. Who wouldn’t want to work for an organization like this? One that offers a high probability of job satisfaction and encourages personal skill development? A culture like that can help the operation on many levels, from reducing operational costs to attracting new employees. 

What now? There is only one connected worker solution that can provide this level of intelligence on your workforce–contact us to learn more about how Augmentir can benefit your business and ask for a demo!