Learn how to standardize quality assurance procedures in manufacturing to improve overall quality and reduce errors.

It takes implementing just one wrong procedure for a product to end up defective and nowhere near ready for customer delivery. That’s why it’s important to standardize quality assurance (QA) procedures to ensure conformity on the shop floor and prevent product malfunctions.

But what is quality assurance? According to TechTarget, it is a process used to determine whether a product or service meets necessary requirements, in manufacturing specifically these are required standards for distribution. In a nutshell, QA procedures ensure customers receive quality products that are free of defects.

quality assurance procedures manufacturing

Learn how to standardize quality assurance procedures in manufacturing by exploring the following content:

What are quality assurance procedures?

QA procedures are a systematic process of establishing and maintaining set requirements for manufacturing reliable products and services. These procedures should be standardized by setting up a quality assurance system for workers to access. There, they can see how to complete certain tasks to avoid errors on the production floor.

Quality assurance methods can be categorized into three types, which we explain in the table below.

 

Type of QA methodDescriptionExample
Failure testingThis is the process of testing a product to see if it can withstand stress. The purpose is to identify any deficiencies.Manufacturers may place a product under heat, pressure, or vibration to test outcomes.
Statistical process control (SPC)SPC is an industry-standard practice for measuring and controlling product quality during the production process. Data is collected by measuring process inputs (dependent variables) in real time. This data is then transferred onto a graph with predetermined control limits based on how a type of product is expected to perform.A manufacturing line would apply statistical and analytical tools to monitor input variables and look for excesses or waste.
Total quality management (TQM)TQM is the idea that every employee, from assembly line workers to leadership, is committed to improving processes, products, and services.TQM may be implemented to raise overall productivity and make a manufacturer more competitive.

 

How to standardize quality assurance procedures

Quality assurance procedures help manufacturers develop products and services that meet customers’ needs and expectations. If implemented successfully, QA can catch any defects before they arise and substantially increase product quality.

It’s also vital to implement a quality assurance system to improve efficiency. Developing a unified system makes it easier to incrementally improve your production processes, and it’s essential for standardizing your quality assurance procedures.

Read on about the seven steps for successful QA implementation:

Step 1: Define Organizational Goals

Successful manufacturing QA begins by identifying how workers’ jobs are tied to an organization’s goals. It’s crucial for workers to know their company’s mission and how they fit into it. When employees understand how their individual goals relate to the organization’s goals, it can boost worker confidence — and in turn, production efficiency.

Step 2: Pinpoint Necessary Success Factors

It’s important to list the factors that make your quality assurance process successful. For instance, factors can include production processes, technical or customer support, and other things that make your organization great. Creating a list of major factors that contribute to company achievements will make it easier to update and manage those factors later on.

Step 3: Identify Your Customer Base

It’s vital to define your client case. If you know your customer, you’re more likely to create products and services that they would value.

Step 4: Gather Customer Feedback

Once you’ve established your customer base, it’s vital to incorporate what they think about your products and services. Frequent customer feedback can keep your quality assurance on track since it helps you identify and resolve product issues before they become critical problems. Reports can be gathered though surveys, email, phone, focus groups, or other methods. The goal is to achieve continuous feedback regardless of which methods you choose.

Step 5: Strive for Continuous Improvement

Quality assurance goes hand in hand with continuous improvement. The information you’ve gathered from customer surveys or other methods can now be used to implement any needed changes to your quality assurance process.

Continuous improvement can also be in the form of customer service training, changes to production processes, improvements to products or services, or anything that adds value to your organization.

Whatever you do, it’s crucial to study customer comments and use them to enhance operational procedures to ensure you’re delivering products that bring value and sell.

Step 6: Find QA Management Software

Once you’ve established the above steps, it’s time to start thinking about which quality QA software, or system, will help you better implement QA procedures. Picking the right software will aid with maintaining and improving production processes.

Step 7: Assess Results

Lastly, it’s important to measure your results. Your main goal is to ensure that your business meets the needs of each customer. Create measurable objectives for employees so that everyone knows what needs to be accomplished in a timely manner. If goals aren’t met, make sure workers are clear about what actions need to be taken to meet client satisfaction.

Take note: If your manufacturing firm does not reach its goals, it is hard to show a positive ROI to stakeholders. That’s why taking corrective action to meet company targets is more imperative than ever before.

Benefits of Implementing QA Procedures in Manufacturing

Quality assurance in manufacturing can offer a wide variety of benefits if management makes it a priority.

Some benefits of standardizing QA procedures include:

Cost-effectiveness: When done right, QA can prevent quality product issues before hitting the market. For instance, manufacturers won’t have to worry about scrapped parts, product returns, or other expenses due to poor-quality goods.

Greater workplace efficiency: Manufacturers will be able to better allot resources like time, money, and warehouse space if fewer product deficiencies exist. It boils down to this: it takes fewer resources to develop quality items if processes are in place to support the feat of QA procedures.

Enhanced Customer satisfaction: Customers will almost surely receive quality products in a timely manner if workers employ quality assurance techniques. If fewer product malfunctions exist, customers are more likely to keep coming back for more. In the end, it’s a win-win situation for both businesses and clients alike.

Industrial companies use Augmentir’s breakthrough system to standardize and optimize quality assurance procedures in manufacturing. With Augmentir, you will experience fewer errors and reduced product defect rates with our connected worker solution. Learn more about our quality use cases.

Contact us for a live demo to start optimizing your frontline operations today!

Learn how to track employee skills in manufacturing and discover modern approaches to effective skills tracking.

In today’s manufacturing environment, it is daunting and time-consuming to keep track of employee skill levels across the many different job tasks. With the constantly accelerating rate of turnover in the workforce, Excel or paper-based skills tracking in manufacturing has become obsolete.

Leading manufacturers are now turning to smart digital technology to streamline skills tracking and connect it with frontline operations, giving them a competitive edge and boosting workplace safety productivity. Skills tracking software can be a great help to identify workers’ current skills and find any gaps. In a nutshell, such a tool helps automate, organize and simplify the process of evaluating employees’ skills and better understanding your workforce.

track employee skills in manufacturing

Learn more about how skills tracking is changing and the importance of integrating skills management into the flow of work by exploring the following topics:

Five approaches to effective skills tracking in manufacturing

According to a recent survey by McKinsey & Company, companies reported that tracking and validating skills and competencies was their top talent challenge.

Effective skills tracking can improve safety, productivity, and worker performance by helping match the right people with the right tasks. For any organization, there are multiple methods and tools that can be used to track the skills of your workforce:

1. Direct assessment

This approach focuses on one employee directly assessing another. This may be done as a form of peer review between employees or by a manager.

2. Self-assessment

This approach consists of employees conducting self-assessments of their skills and qualifications through surveys every few months.

3. Anonymous peer assessment

This approach involves coworkers anonymously assessing each other’s performance on projects or other tasks.

4. Skill assessment using HR or learning systems

This type of assessment can be done using an HR system (or a Learning Management System) to assess and update employee profiles based on training completed. For example, workers can report any courses finished, track their training data or report new certificates.

5. AI-based skills tracking software

Any of the above 4 methods are commonly used, however, the increasing workforce variability, absenteeism, and turnover is forcing new requirements. Increasingly, manufacturers are turning to AI-based software solutions to help digitally track and manage skills, and connect them with work execution.

HR/Learning systems or standalone skills tracking software solutions that attempt to automate skills tracking fall short of meeting the needs of today’s manufacturers because they do not connect the “skills that workers know” with the “work being done”. These standalone solutions may have been ideal for the stable, unchanging workforce of the past, but they are not suited for today’s era of high workforce variability.

skills and work

An integrated, closed-loop skills management system is the solution for this era of high workforce turnover and absenteeism. Skills management solutions that combine skills tracking capabilities with AI-based connected worker technology and on-the-job digital guidance can deliver significant additional value. Data from actual work performance can inform workforce development investments allowing you to target you training, reskilling, and upskilling efforts where they have the largest impact.

Benefits of skills tracking in manufacturing

Tracking skills in manufacturing can help identify the skills your employees already hold and those they still need to learn to properly do their jobs. Furthermore, using AI-based connected worker solutions, organizations can digitize and easily manage skills tracking and training programs and connect them with frontline operations.

Some benefits of tracking your employees’ skills using this approach include:

1. Boosts productivity on the shop floor

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. Skills tracking also ensures that workers are qualified to perform their job.

2. Ensure safety

Solutions that close the loop between training/skills and the work being done 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.

5. Boosts internal communications

Employers who actively develop their employees’ skill levels are likelier to retain them. Tracking skills can also motivate and spur connections with team members.

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.

7. Enhances competitive edge

Although the purpose of effective skills tracking is to aid in worker growth and development, a byproduct is a stronger, more competitive organization as a whole. 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.

Features to look for in skills tracking software

Having the right features for skills tracking in manufacturing can help a company be more productive and efficient. This type of software should help manufacturing facilities no only identify, assess, track and cultivate employee skills, but also improve operational safety and performance.

It’s important to look for the following features when deciding which software is right for you:

Training management
This feature helps businesses see how their teams are progressing and evaluate whether training opportunities are making an impact. It helps store employee training records for real-time access and evaluation, and measure training effectiveness based on actual job performance.

Certifications management
This feature helps employers manage employee certifications. If a worker’s certification is expiring, the software’s tracking functions should easily notify the parties involved.

Skills tracking integrated into the flow of work
Skill levels and current endorsements ensure that workers can perform tasks safely and correctly and, therefore need to be considered at the moment of work assignment and again at the moment of work execution.

Live dashboard
Skills tracking software with customizable dashboards offer a real-time view of employee skills, qualifications, and any skill gaps that may exist. Managers will have a better idea of where to allocate resources to train employees and who is a better fit for a role.

intelligently assign jobs

 

Learn how Smart Skills Management software is helping manufacturers bridge the gap between training, skills, and work to build a more resilient and agile workforce.

Download our latest eBook – The Future of Work: Connecting Skills Management with Standard Work.

 

Smart Skills Management software is helping manufacturers bridge the gap between training, skills, and work to build a more resilient and agile workforce.

Skills management and tracking software helps manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.

These smart insights can help businesses improve their talent management strategy, including training and development programs and recruiting opportunities.

If you’re interested in learning how to find the best skills tracking software, explore this article as we cover:

  • Benefits of skill management and tracking software
  • What to look for in tracking software
  • FAQs about skills tracking and management tools
  • Why Augmentir

Benefits of skills tracking and management software

Skills management involves identifying workers’ expertise and experience to determine whether they’re a right fit for a role, which areas need improvement, and how to best facilitate learning opportunities. A reliable skills tracking and management software solution lets you keep track of what your employees can and can’t do, and integrates that information with the actual work being done.

Here are a few reasons why you should invest in a tracking tool:

Enhanced training and development programs: Improve employee engagement by making sure courses and training opportunities are relevant to the jobs they perform. Management software makes it easier to assign employee courses that are appropriate and timely, and then track each individual’s training progress.

A more productive workforce: Employees who have access to training resources can further develop their skills to better perform assigned job duties and maximize output. This will empower workers to strive for continuous improvement and grow in their roles.

Improved retention: Offering continuous development and training programs can help your employees feel appreciated and taken care of. In return, they are more likely to stay and do a good job. Considering that turnover rates cost manufacturing firms an overwhelming amount, it’s critical to invest in programs that will improve retention rates.

What to look for in tracking software

Knowing how to effectively track employee skills can be challenging, but the right software can ease the burden. It makes it easier to identify who is lacking which skills and how to best close the gap.

Unfortunately, standalone skills management software solutions that attempt to automate skills tracking fall short of meeting the needs of today’s manufacturers because they do not connect the “skills that workers know” with the “work being done”. These standalone skills management solutions may have been ideal for the stable, unchanging workforce of the past, but they are not suited for today’s era of high workforce variability.

Skills management 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 investments allowing you to target your training, reskilling, and upskilling efforts where they have the largest impact.

When looking for the best skill management and tracking software, its critical to make sure it can:

  • Keep a centralized database of competencies
  • Pinpoint worker skill gaps
  • Let management look for employees with specific expertise
  • Track the skills of individual employees in a centralized database
  • Intelligently assign work based on true worker skills and competencies
  • Personalize on-the-job guidance based on worker skills and experience
  • Create reports or dashboards to study competencies and skill gaps across departments

AI-powered software enables managers to filter through employee databases by skill to assemble teams best suited for a project.

 

skills tracking software

 

Skill management solutions should also integrate with core human resources software to offer seamless sharing of employee data. Some tools may even work in tandem with corporate learning management systems to provide access to educational content that could help workers develop new abilities.

Lastly, HR can use skill management software to make it easier to follow compliance regulations that require evidence of employee capabilities or certifications. For example, a health manufacturing facility may need workers to upload certain certifications to show proof of compliance.

FAQs about skills tracking and management tools

How do you keep track of employee skills?

You can track employee skills using software that manages worker competencies. These programs should allow you to build customized job profiles, create reports to study competencies, and fill skill gaps.

What is skills software?

Skills software is a tool that helps manage and keep track of worker expertise and experience. It’s used by businesses to optimize job performance and boost worker productivity.

Should I invest in skills tracking software?

Manufacturing facilities can benefit from investing in software that provides an easy-to-use centralized database of worker profiles, training resources, and much more.

Why Augmentir

Augmentir can help manage the skills of your workforce with its AI-powered connected worker solution. Our skills management tools create visibility at all times to optimize training programs, track individual and team progress, and initiate more targeted training. Check out our live demo.

 

Learn how Smart Skills Management software is helping manufacturers bridge the gap between training, skills, and work to build a more resilient and agile workforce.

Download our latest eBook – The Future of Work: Connecting Skills Management with Standard Work.

 

Augmentir’s take on the trending Workforce Institute’s staggering survey numbers.

Do you remember when offshoring–the outsourcing of production internationally–was once considered the “gold standard” for manufacturers because of reduced costs? Funny how things change. We can partly thank the global pandemic for this. Reshoring, also referred to as ‘onshoring’, in manufacturing is now the way to go–the apparent panacea to supply chain disruptions and a healthier economy. This should have manufacturers cheering and dancing in the streets, right? Not so fast. We’ve also got a massive labor shortage to deal with. But don’t fret. There are solutions to be found, and they happen to exist in software tools already being embraced by organizations on their journey to digital transformation.

The perks and pressures of onshoring in manufacturing

If your organization isn’t already thinking about onshoring its operations, maybe you should be. Onshoring in manufacturing means greater resiliency, agility, and sustainability by shortening the distances between process and delivery. Less travel means reduced emissions and adherence to ESG standards. Reshoring addresses issues associated with shipping costs, lead times, and new regulations. Working in familiar markets can help identify supply and demand trends more accurately. National employment rates are likely to increase when hiring residents and working with other domestic business partners.

But labor shortages and the variability of today’s workforce have not made reshoring an easy shift. So while there is tremendous opportunity to bring production home, the lack of affordable and skilled labor is having a tremendous impact on our domestic production capacity.

Here’s how you make onshoring work for you. First, stop thinking the old way of recruiting, training, and retaining workers will still work today.

Work with what you’ve got

What’s wrong with training today? Yes, training programs can help improve worker knowledge and skills development. But only if they are meeting the unique needs of individual workers with content-rich, high-impact learning and hands-on training programs. Forget those standard training programs–they are useless in the face of the variable workforce we have available today. The workers you can find are showing up with a mixed bag of experience and skills. That doesn’t have to be a disadvantage anymore. Because there is a smarter way to train and optimize the skills of each of those workers to meet productivity goals individually and fulfill the potential for your organization’s production capacity.

Smart digitization is the ticket to effective onboarding, training, and more–from hire to retire

“The secret of change is to focus all your energy not on fighting the old, but on building the new.” – Socrates

This new era of workforce instability is forcing manufacturers to change. It’s forcing them to turn to digital technology and look at smarter ways to hire, onboard, train, and retain their workers. At Augmentir, we call this Smart Digitization.

What do we mean by ‘smart’ digitization? Smart digitization involves adopting modern, digital tools, mobile technology, and supporting workers throughout their entire lifecycle.

smart digitization throughout worker lifecycle

 

Modern connected worker tools are at the core of the solution that supports workers throughout their employment, from training to troubleshooting in real-time to ongoing learning and development. If you look at the entire employee lifecycle, this means:

  1. Using software tools to digitize and automate onboarding and skills tracking to help get workers operational faster, regardless of their skill and experience.
  2. Once on the job, digitizing and personalizing work instructions based on the individual needs of the worker – whether they are a novice worker or an expert.
  3. Proving instant access to support, within the flow of work.
  4. And finally, using an AI-based system to analyze how workers are performing on the job, and intelligently targeting upskilling and reskilling based on actual work performance.

Workers have access to a suite of digital tools and knowledge resources at their fingertips – digital work instructions, collaboration, and support tools to guide them on the job and quickly problem-solve complex tasks, allowing them to do their personal best.

For employers, this means not only more engaged and collaborative workers, it also means deeper insights into work performance that can help drive continuous improvement efforts.

skills job proficiency mapping

AI-based smart insights intelligently optimize workers’ performance by identifying and tracking their skills in real-time. Smart insights pull from these performance metrics and learn to prompt workers who need new training programs or work opportunities, continuously upskilling and reskilling.

It’s the advanced medicine needed to maximize productivity and operational health.

So as you plan to bring more of your production back home, make sure you’re ready to seize the opportunity and address the challenges of a restricted labor market at the same time.

 

Find out how and why so many manufacturers are turning to Augmentir to turn their workers into efficient, productive, and long-term assets for their businesses.

Check out our latest webinar – Smart Digitization of Frontline Workers to learn more.

 

AI and connected worker technology is helping frontline managers combat employee burnout and improve engagement and retention.

In today’s fast-paced manufacturing industry, staying ahead of the curve is critical to success. To remain competitive, companies must continuously reskill and upskill their workforce. One way to achieve this is to operationalize training and bring it closer to the factory floor using artificial intelligence (AI) and connected worker technology. Operationalizing training means taking a more systematic approach to training and workforce development, rather than treating it as a one-time event.

operationalizing learning

According to a report by McKinsey, companies that embrace AI-powered learning reduced training time by up to 50% and improved learning outcomes by up to 60%.

AI-powered solutions make learning more accessible, engaging, and effective; and by integrating training and learning solutions into the everyday operations of the company, manufacturers can create a culture of continuous learning and improvement. In fact, here at Augmentir we’ve seen manufacturing companies use this approach to reduce new-hire onboarding and training time by up to 72%.

Learning: When and Where it’s Needed

AI has the potential to revolutionize many industries, and manufacturing is no exception. Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions.

With AI, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially operationalizing training and 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 (or workflow 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.

This approach 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 customized to each worker’s skill level, making it easier for them to learn at their own pace.

Additionally, AI-driven learning solutions offer:

  • Personalized Learning: AI-powered learning solutions can be customized to each worker’s skill level, making it easier for them to not only learn at their own pace, but also matched to their experience level. For example, novice workers may be required to watch a micro-learning video as a safety prerequisite to performing a task, whereas a more senior worker with the appropriate level of job experience and proficiency may not be required to watch the learning video.
  • Performance-based Learning: AI-powered solutions provide workers with hands-on learning experiences that are customized based on their actual job performance. These experiences can be delivered through a variety of content mediums – rich media, self-help guides, microlearning videos, and even augmented reality (AR) experiences.
  • Real-Time Feedback: AI-powered solutions can monitor worker performance in real-time, providing instant feedback to help workers improve to provide access to content to help resolve issues in the flow of work.

AI can also help with the assessment of employee performance. Traditional performance evaluations often rely on subjective assessments from managers. Conversely, AI-powered performance evaluations can provide a more objective and data-driven assessment of employee performance, while also providing a more accurate picture of an employee’s strengths and weaknesses.

Better Training, Better Work

By implementing AI-based solutions, companies can identify and operationalize training needs across the organization. Using performance data, AI can uncover gaps in knowledge or skills across the workforce, which can then be used to develop targeted training programs to “fill” these gaps.

Once implemented, AI can be used to effectively track and improve learning and training effectiveness, leveraging data on worker performance before and after training to measure impact and refine training programs to ensure that they are delivering the best outcome.

As the manufacturing industry continues to evolve, so must how they approach learning solutions. A recent Deloitte survey found that over 90% of companies believe that AI-powered learning will be important for their organization’s success in the next three years. AI has the potential to operationalize training and transform learning in the manufacturing industry by bringing it closer to the factory floor. By leveraging AI-powered personalized learning, real-time feedback, data-driven performance evaluations, and identifying training needs, industrial organizations can create a more efficient, effective workforce.

Being thankful for AI might not seem like one of the usual items to include on your “What I’m Thankful For” list, but, AI truly has laid the foundation for not only the Augmentir platform, but for transforming the manufacturing workforce in positive ways

Every year as Thanksgiving approaches in the United States, we take time to reflect on what we are thankful for in our personal lives, such as family, friends, and health to name a few. As we started thinking about what we’re thankful for from a work perspective here at Augmentir, many things came to mind: our wonderful clients, an awesome team, our incredible founders, but one item high on our list is something that has allowed us to stand out in the Connected Worker platform space and make our product what it is today – Artificial Intelligence. Specifically AI in manufacturing. 

Being thankful for AI might not seem like one of the usual items to include on your “What I’m Thankful For” list, but, AI in manufacturing truly has laid the foundation for not only the Augmentir platform, but for transforming the workforce in positive ways as you’ll see below.

Improved Safety in the Workplace

One of the most common use cases for adopting AI has been in workplace screening and safety primarily as a result of the pandemic. Manufacturers found use in AI to monitor interactions of employees that needed to be in person on the shop floor during the pandemic so that they could conduct contact tracing and facility sanitization if necessary. Seeing the value of AI in workplace safety, manufacturers have continued to implement AI strategies for long-term solutions to identify safety events before they happen or to speed up post-incident root cause analysis for accidents like trips and falls. Industrial companies that implement AI-powered connected worker solutions as part of their digital transformation strategy have seen up to an 80% decrease in reportable injuries.

Connecting the Frontline Worker

According to Cisco, there are over 3 billion workers across the globe, and nearly two-thirds of these workers are frontline or field workers, whose day-to-day duties require that they physically show up to their jobs. Over the years, the manufacturing industry has done a really good job of connecting machines in the fabric of the business and giving operators the necessary data to help run those machines better. Our frontline workers are the least connected set of workers in the company. Frontline workers should be fully integrated into the fabric of the business from a collaboration standpoint so that they have access to the data that they need, when they need it. AI-powered connected worker tools provide not only a path to connect workers, but also intelligently deliver the right level of performance support so they can perform at their best.

Making Sense of Valuable Data

As workers become more connected, companies have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of productivity, quality, and workforce development, setting the stage to address the needs of a constantly changing workforce. AI algorithms in manufacturing are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse data and find correlations and patterns that can be used to identify opportunities for improvement and create a data-driven environment that supports continuous learning and performance support. Using AI insights derived from Augmentir’s Connected Worker Platform, Colgate-Palmolive was able to save 10-30 minutes saved per shift and as much as 120 minutes reduced between Maintenance Notification and Maintenance Order Closure (Maintenance Execution Time).

Continuous Learning & Development

The new workforce dynamics and the nature of hybrid work are also now forcing manufacturers to re-think employee onboarding and training. The historic methods of onboarding and training taught workers everything they could “possibly” do which resulted in overtraining. The data-driven era we’re entering into is one of continuous learning and development powered by AI. Training shifts from the things frontline workers are possibly going to do to what they are probably going to do. Implementing AI in manufacturing training results in reduced training times, continuous learning and development, and the ability to upskill at any point as needed. Learning is always available, training content is available on-demand to the worker on the shop floor at the time of need. Reducing the initial onboarding training and allowing training to occur at the moment of need, coupled with AI for scoring, provides insights into the most effective training modules as well as what needs to improve based on demonstrated execution.

 

At Augmentir we believe that the purpose of a Connected Worker platform isn’t simply to deliver digital work instructions and remote support to a frontline worker, but rather to continually optimize the performance of the connected worker ecosystem. AI is uniquely able to address the fundamental macrotrends of skills variability and the loss of tribal knowledge in the workforce. With an ecosystem of content authors, frontline workers, subject matter experts, operations managers, continuous improvement engineers, and quality specialists, there are dozens of opportunities to improve performance – and that’s something to be thankful for.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, check out our latest eBook – Build a Modern, Connected Workforce with AI.

These virtual events were a great way to connect with manufacturing professionals and discuss some of the industry’s top challenges and topics – workforce transformation, learning and development, lean manufacturing, and autonomous maintenance.

Last week, Augmentir participated as a sponsor in the 2021 American Food Manufacturing Summit. This 3-day virtual event was designed to bring food and beverage manufacturers together to discuss current trends, strategic insights, and best practices in an ever-evolving environment. The event focused on addressing today’s top challenges and future of food processing and manufacturing, specifically around embracing digital transformation and technology for manufacturing excellence. Attendees were able to connect with top industry influencers and learn about different strategies to improve automation, operational excellence, quality, and safety in the food manufacturing industry through open roundtables and 1:1 meetings.

Augmentir’s Enablement Director, Shannon Bennett, hosted an open roundtable discussion on the role digital transformation plays in food and beverage manufacturing, and how technologies like artificial intelligence (AI) and connected worker platforms are helping companies kick-start their digital transformation efforts. During the discussion, Shannon opened the floor to the attendees to discuss the day-to-day challenges they face at their manufacturing organizations and the tools they’re looking into to solve those challenges. 

Solving Manufacturing’s Biggest Challenges with AI and Connected Worker Technology

The roundtable consisted of executives and manufacturing leaders from some of the world’s largest food and beverage companies to smaller family-owned and operated specialty food and beverage manufacturers. Throughout the roundtable, we heard the same challenges and frustrations related to standardization, moving from paper to digital processes, data collection, lack of traceability, and an overall need for digital transformation.

The overarching roundtable discussion was around digital transformation. Food and beverage manufacturers are accelerating the pace of digitization to address their top challenges – the labor crisis, increasing skills gap, and increased pressure for improved production efficiency, changes in consumer demands, and increased regulatory compliance related to food safety.

Moving from Paper to Digital

During our roundtable discussion, most of the manufacturing leaders were in the discovery phase of their modernizing process, where they were beginning to look into digital solutions to solve their challenges around manual processes and efforts to reduce paper. Some of the discussion around paper included issues with quality on the shop floor and wanting to go paperless, easier access to training for employees, lack of traceability (for example, maintenance schedules need more visibility of completion, where issues arise, and more transparency all around), and digitizing information from a quality standpoint.

Digital work instructions reduce the need for paper and deliver information to frontline workers when and where they need it. This provides frontline workers with a standardized way of performing technical work.

Lack of Data-Driven Insights into the Work Being Done

Another key challenge was the lack of insight into how workers were performing their jobs – whether it be in quality, equipment operation, or maintenance. One participant discussed labor challenges in their organization and that when they collect data it often gets lost and when they come back to it, they don’t know or remember why they’ve collected it in the first place.

Connecting workers with digital tools is merely a first step in the process of truly understanding and getting clarity on the work being done. Connected Worker data is inherently noisy, generating misleading signals that traditional business intelligence (BI) tools aren’t designed to handle. This leads to murky or contradictory conclusions that prevent organizations from taking anything but a “one size fits all” approach to work process and workforce investments. Or, even worse, false conclusions are generated about the state of work process and workforce opportunities, leading to targeted investments into the wrong areas.

The discussion shifted to AI as a solution not only bringing clarity to the work being done, but also more generally democratization of the workplace, and giving employees the tools to use data effectively to improve manufacturing operations. AI is designed for purpose to recognize patterns in the noisy data sets generated by a factory workforce, letting your continuous improvement and operations teams focus on what’s really going on.

Training

Employee onboarding and training was also a hot topic of discussion. Many participants spoke about manual processes and how traditional training methods are proving to be ineffective.  Traditionally, there was a clear separation between training and work execution. However, many participants shared that they are starting to re-think how they are training and onboarding their workers, and shifting more towards delivering training at the moment of need. The roundtable participants discussed at length approaches and strategies for re-thinking how training is delivered for today’s workforce.

Build a Modern, Connected Workforce with AI

To address these challenges, the roundtable participants overwhelmingly agreed that digital transformation initiatives for food manufacturing should start by focusing on streamlining data collection and digitizing valuable data. Using an AI-powered connected worker platform to accelerate this effort not only furthers a company’s digital transformation efforts, but also provides a whole new set of data that can provide really interesting insights and optimization opportunities. AI doesn’t remove the human worker from the equation, but rather, takes the human worker and embeds them into the digital operation.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, check out our latest eBook – Build a Modern, Connected Workforce with AI.

 

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.

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

Manufacturing workforce challenges

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

Build and grow a top performing manufacturing 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”.