How to Improve Quality Control and Quality Assurance in the Food Industry

Learn how to improve quality control and assurance in the food industry with digital solutions from Augmentir.

Following quality control (QC) and quality assurance procedures in the food industry is imperative to ensure product quality and consumer satisfaction. Today’s consumers demand safe, reliable goods that meet all quality inspection protocols. The last thing you want is for a product to get recalled because of potential health concerns.

According to Food Manufacturing, quality control is one of the most important aspects of the food and beverage industry. Manufacturers who perform routine inspections of products during each stage of the production process significantly increase their chances of delivering items that are free of health hazards and liabilities. But beyond avoiding these concerns, standardizing and digitizing quality procedures benefits the entire operation.

Ultimately, preventing and catching quality issues can boost product quality, reduce waste, raise profits, increase brand reputation, and avoid media or food safety disasters. Learn more about QC and assurance in the food industry and how to improve it as we discuss:

quality control food industry

Types of quality control measures to take

There are certain QC measures you can take to ensure that all goods meet quality standards, from regular machine inspections to worker training. They fall into two general categories: preventative and reactive.

Preventative (proactive) quality control: Minimizing the number of deficiencies begins with implementing preventative QC solutions. When workers can catch mistakes before they even happen, they prevent product defects. Preventative QC measures should be practiced on a routine basis and can range from inspecting machines and equipment to offering employee training opportunities. By providing workers with real-time information and guidance through mobile, connected worker solutions, manufacturers enable them to make better decisions about product quality, reducing the risk of errors and identifying potential quality issues before products are shipped to customers, reducing the risk of product recalls, and preserving consumer trust.

Reactive quality control: Catching every defect on the production floor is nearly impossible, even if the most fool-proof strategies are taken. That’s why creating a plan of action ahead of a crisis can help solve quality issues as they happen.

What to put in your plan will depend on the potential problems. For example, you can include specific instructions on what to do if machinery breaks down or stops unexpectedly. It’s vital to collect any data at this stage. Analyzing this data can help you improve preventative quality control in the future to make sure the same problems don’t happen again.

Pro Tip

By utilizing AI and modern, digital technologies, companies can connect, engage, and empower frontline workers to drive quality improvements, resolve quality issues faster, and share timely insights with teams across the value chain.

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Keep in mind that practicing quality control in the food industry should be part of every manufacturing process, from product ideation and development to production and delivery. Problems can develop at any time, so it’s crucial to follow protocols at every stage of production to prevent even the slightest of mistakes.

All workers should also uphold QC and assurance protocols in their everyday tasks to ensure continuous product improvement.

Better organization of equipment can also help workers understand how the action of one affects the other to solve any potential problems. This is another benefit of integrating your asset hierarchy with a connected worker solution. In a nutshell, strong hierarchies are a solid foundation for proper maintenance management and reliability.

How to improve QC and assurance procedures in food production

Effective quality control and assurance procedures prevent defective food products from making their way into grocery stores and homes. That’s why manufacturers should document the quality of their goods at every stage of the operational process. Strategies like first time quality (FTQ), or first time right, plans coupled with smart, connected solutions help decrease product deficiencies and increase customer satisfaction.

Manufacturing firms in the food industry must follow specific requirements set by the Food and Drug Administration (FDA), Good Manufacturing Practices (GMP) system, and the Hazard Analysis and Critical Control Points (HACCP). The guidelines set by these regulatory bodies can give businesses a better idea of how their processes should look and what data they need to collect and report.

Data should be collected for real-time production processes. These vary by product but may range from product chilling and thermal processing to testing raw materials for metal toxins and other chemical deposits.

The following steps provide a roadmap for how to improve quality control in the food industry.

Step 1: Source the correct ingredients

A successful assembly line run begins with finding and using the correct ingredients. Some things to think about when deciding which ingredients to choose: where the raw material was sourced, when, and its condition.

Step 2: Include an approved supplier list

Make sure that each ingredient has an approved supplier list. A good rule of thumb is to include three vendors per ingredient and record the ingredient with each supplier’s name, address, and code number on the list. The more information you include, the better. Having an approved vendor list ensures that all parties are properly vetted by the manufacturing firm and meet its requirements for quality and distribution.

Step 3: Document product and recipe creation

Documenting how each food item is made and its recipe helps set the quality standards for finished goods. This documentation can also be useful when improving product development in the future. Your document should include the types of ingredients used, their codes, batch yield, percentage formula, and more.

Step 4: Catalog production procedures

It’s also critical to log all the details of a production process, including how materials should be delivered, the appropriate conditions for storing food, what order each ingredient should be added to the batch, what tools are needed, and who is in charge of each task.

Note that this step is different from documenting product and recipe development because it includes the actual instructions for carrying out each procedure. For example, a worker may be asked to preheat the oven to a certain temperature as part of ensuring the food is ready for customer distribution.

Step 4: Record real-time processes

Machine operators should record in real-time every detail of how goods are created during actual production. This can include factors like product size, weight, expiration date, equipment conditions, and more.

Step 5: Digitize assurance and inspection processes

AI and smart, connected worker systems help digitize and link inspections and other quality control procedures. This creates an additional layer of defense, protecting customers and preventing quality issues before they can impact production.

How Augmentir helps with quality control and assurance

Augmentir offers a smarter way to improve quality control in the food industry by effectively standardizing and optimizing quality assurance and inspection procedures for all frontline workers. With our smart, connected solutions coupled with AI-powered software, food manufacturers have improved quality control and assurance by:

  • Tracking and analyzing data to identify trends and opportunities for improvements
  • Reducing human error in inspections by standardizing and improving training procedures and processes
  • Transforming connected workers into human sensors who can proactively address quality and safety events that surface during manufacturing operations

standardize and digitize quality assurance procedures

 

Our AI-powered connected worker solutions, provide digital work instructions to help employees better perform inspection checks and reduce the number of production errors and rework.

These customized solutions also include:

  • Digital standard operating procedures (SOPs) for how to complete assembly line tasks. These step-by-step instructions can greatly improve workflow efficiency, increase regulatory compliance, and reduce mistakes on the shop floor.
  • Digital workflows that convert your paper-based processes to digital work instructions and personalize them to the needs of each worker.
  • Enhanced product traceability to decrease equipment setup time, reduce process inconsistencies, and better meet customer expectations. Our digital instructions help you to easily track materials from the supply chain, inventory, and across every production process.

If you are interested in learning why companies are choosing Augmentir to help improve their quality control and assurance processes, check out our quality use cases – or reach out to schedule a live demo.

 

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Why Manufacturing Data Collection is Important and How to Improve It

Learn how manufacturing data collection can boost your bottom line and how to improve your gathering data techniques.

As manufacturing operations continue to modernize and evolve it is clear that without big data they won’t be able to sustain themselves. More and more manufacturers are looking to the tremendous capabilities and insights that digitized information can provide.

Shop floor data collection enables businesses to better measure, standardize, and optimize their production processes. It’s more important than ever before to have information that provides real-time insights for measurable progress.

Accurate reporting is more sustainable if management deploys a work culture and production infrastructure that supports digitized manufacturing data collection with connected worker platforms and solutions.

We discuss more about collecting data and how to improve it in the following sections:

manufacturing data collection

Examples of data collection in manufacturing

Data collection has many uses in a variety of situations for a wide array of manufacturing roles, from operators and engineers to plant managers and even leadership.

For example:

  • Plant managers use production dashboards to better gauge where operators need support, such as when a piece of equipment isn’t working.
  • Operators use machine interfaces that show the status of machine processes, part counts, and other measurable data to ensure they are meeting production targets.
  • Quality managers use production line data to identify and proactively address quality issues.
  • Engineers use collected data to check for any bottlenecks and adjust processes if necessary.
Pro Tip

Frontline workers often witness safety, quality, or maintenance issues on the factory floor. They are effectively a “human sensor” on the manufacturing process and can readily identify issues that need to be addressed. Today, recording data and resolving those issues is most often a manual and paper-based process. As such, there is minimal data collection, latency in resolving the issue, and little-to-no feedback to the frontline worker on resolution.

Equipping workers with mobile and digital tools can help optimize shop floor data collection.

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Which data to keep an eye on

Data generated on the shop floor can vary depending on the nature of work, the type of devices and technologies used, and the area of operation. Much of this data is of use to manufacturers and can be used to improve production processes.

Useful types of data for manufacturers that we recommend keeping an eye on are:

Inventory data: This type of data helps manufacturers keep track of product inventory. With it they can better gauge what items need to be restocked or which ones aren’t bringing any value to the customer as well as improve forecasting ability and more.

Quality and Inspection data: Ensuring product quality is a priority in manufacturing. Collecting data related to quality control, product inspection, and identifying defects or deviations from the desired standards is crucial to maintaining high-quality products and operations.

Machine data: Optimizing a production process can become difficult if you don’t know the status of your equipment. Manufacturing data collection can be digitized to analyze machine quality and performance, equipment runtime and downtimes, or other machine-related problems. Sensors monitor machine use and downtime, maintenance time, cycle time, and more. Studying this collected data helps identify where production can be improved to optimize efficiency.

Using AI, manufacturers can filter out the “white noise” data (or data that is of no use) to derive actionable insights more effectively than with traditional methods. Automating, standardizing, and digitizing manufacturing processes also improves manufacturing data collection procedures, making them streamlined, accurate, and reliable.

How to improve production data collection

Manufacturing data collection is transforming the way businesses handle their operational decisions. However, it can also pose setbacks to your production line if you gather inaccurate data.

Manufacturers must implement data collection systems that are easy to understand and navigate. You’re risking inconsistent data collection and reporting when you install a system with complicated functions and navigation tools. This can be avoided by focusing on people-centric, intuitive, and user-friendly systems that fit into the everyday flow of work for the frontline workforce.

quality manufacturing data collection

Implementing a unified system alone won’t improve data collection. Solutions that incorporate enhanced mobile capabilities and provide a truly connected enterprise are able to facilitate and optimize data collection efforts.

Examples of some useful smart, connected solutions to improve manufacturing data collection are:

  • Personalized, Digital Work Instructions: these intelligently deliver personalized digital work instructions matched to the needs of each worker in order to deftly guide them through and streamline day-to-day operations.
  • Connected Asset Management: these tools help simplify operations and maintenance of facilities, manage work and maintenance procedures, collaboration, and more.
  • Skills Management: these systems create visibility into workforce capability and optimize training programs, track individual and team progress, and initiate more targeted training and upskilling.

In addition to all the benefits listed above, these smart, connected worker tools are able to empower frontline workers with improved data-driven decision-making abilities that aid in safety, quality, and productivity efforts.

Benefits of digitizing shop floor data collection

Production data collection can make all the difference to a company’s success and give them a competitive edge. Smart, connected worker solutions enhance collection processes, allowing for real-time data collection, streamlined communication and collaboration between frontline workers.

Data-driven strategies can help with:

  • Creating better maintenance procedures based on real-time insights and equipment conditions
  • Optimizing worker productivity by minimizing production errors
  • Reducing downtime by providing real-time feedback
  • Developing higher quality products that increase customer satisfaction
  • Cutting supply chain costs due to better forecasting and waste reduction techniques

Implementing accurate, connected worker solutions can take your data collection efforts to the next level. That’s where Augmentir can help. We are the world’s only AI-driven, people-centric smart connected worker solution to standardize and optimize data collection using groundbreaking AI analytics technology.

See how our AI-focused connected worker solutions are driving results and improving data collection and data-driven decision-making across manufacturing operations – schedule a demo now.

 

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How to Improve Production Quality in Manufacturing

It’s vital that customers receive products that are free of defects. Learn 5 steps for improving production quality and how the right software can help.

Unexpected product quality issues can be a hassle to manage, especially when staff is stuck with processing time-consuming complaints, replacements, and refunds. Even worse, the impact on your bottom line can be substantial.

Manufacturers risk a significant cut to their profit margins when quality standards are not followed during the production process. To improve quality on the shop floor, plant managers need to pinpoint the root cause of quality issues.

Explore this article to learn how to start boosting your industrial processes today:

improve production quality in manufacturing

 

What is Production Quality

Production quality, or manufacturing quality, measures how well a manufacturing process develops products to fit design specifications. Manufacturers must devise a plan for how they want specific items to appear and function before creating them. This can include things like colors, durability, range of motion, measurements, and more. How well a product is made will depend on meeting these conditions.

After the design is planned, a number of factors can affect production quality, including:

  • Equipment/machines
  • Materials
  • Batch size
  • Human mistakes
  • Environmental issues
Pro Tip

Frontline workers often witness quality issues on the factory floor. They are effectively a “human sensor” in the manufacturing process and can readily identify issues that need to be addressed. Today, recording data and resolving those quality issues is most often a manual and paper-based process. As such, there is minimal data collection, latency in resolving the issue, and little-to-no feedback to the frontline worker on resolution.

Equipping workers with mobile and digital tools can help optimize production quality.

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5 steps to improve production quality

Although there may not be one single method for improving manufacturing quality, there are steps you can take to maximize success.

Here are five steps that should be part of your strategy.

Step 1: Assess your current workflow.

Start by reviewing your existing manufacturing processes. We encourage management to ask the following questions as part of their review:

  • What quality benchmarks do you hope to achieve for each product?
  • How much money have you lost from material, energy waste, and wasted time due to quality problems?
  • What is your margin for improvement?
  • What quality standards are implemented in the creation of products?
  • Is your equipment inter-connected with different databases, or just a single database?

We recommend connecting your factory devices to one central database with a cloud-based, connected worker solution that operations management can use to create, assign, manage, and monitor the work being done. This kind of software can help streamline operational processes and track results in real-time.

Step 2: Remove unneeded processes.

Once you’ve accessed your current workflow and set up a connected worker solution to collect frontline worker data, we recommend coupling it with AI-powered analytics that can derive actionable insights. Then you can use these actionable, data-led insights to see which processes are adding value and which ones are not.

quality manufacturing data collection

Step 3: Boost worker training.

It’s important to maintain regular employee training and skills development programs to ensure workers are staying on top of industry best practices, equipment upkeep, and product knowledge. AI-powered connected worker solutions make learning more accessible, engaging, and effective.

Step 4: Create quality goals.

Developing quality goals is a great way to measure product benchmarks, production time, material usage, labor cost, working hours, and more. By digitizing and standardizing quality processes, you’ll be able to see which manufacturing processes are adding to your bottom line and which can be eliminated to bring value to the customer.

Step 5: Cut production waste.

Cutting waste from your production run can improve your business’s supply chain management. Connected worker solutions can identify which processes aren’t needed to reduce waste. It also gives real-time visibility into your supply chain to help you manage supply problems, optimize manufacturing processes, and adjust production schedules.

FAQs about improving production quality

How can the quality of the manufacturing industry be improved?

Measuring your current production processes to see which methods work can help improve product quality and increase the value of goods manufacturers make. You can strengthen the processes related to production by digitizing and automating them. Implementing a connected worker solution that offers real-time insights helps ensure that all goods meet quality standards and compliance criteria.

How do you ensure product quality in manufacturing?

There are a number of factors that can ensure product quality in manufacturing. We recommend following the five steps listed above to minimize defects as well as improve workflow and output.

What are 5 ways to improve production quality?

Assessing your current workflow, eliminating needless production processes, boosting work training, creating quality goals, and cutting production waste can all help improve production quality (see list above for a full description of each, as well as how implementing a connected worker solution can boost their overall impact).

Why is quality improvement important in manufacturing?

Enhancing production quality in manufacturing is a must as the industry moves towards fully connected enterprises, digital transformation, and automation. Businesses risk huge profit losses when quality standards are neglected in the creation of each product.

Digitize and Improve Production Quality with Augmentir

By digitizing and standardizing quality protocols, organizations can maintain compliance through an auditable and verifiable quality management system that gives workers access to the correct procedures as they need them with expert guidance. This ensures that tasks are performed in a standard manner to avoid errors on the production floor, reduce defects, and decrease resources lost to rework.

Refining your manufacturing methods can be difficult without the right technology. Augmentir’s AI-based connected worker solution makes streamlining and optimizing your production and quality procedures easier than ever before. Get in touch for a live demo today and learn why manufacturers are choosing Augmentir to help standardize and digitize quality processes!

 

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How to Reduce Changeover Time in Manufacturing

Learn how to reduce changeover time in manufacturing and the benefits of doing so to maximize production processes.

Providing quality products consistently and on time is at the forefront of customer satisfaction. In today’s competitive market, manufacturers must execute production runs quickly and efficiently to meet customer demand. But equipment and workers can’t operate 24/7. Machines must be properly maintained, workstations require cleaning and employees need rest. This is where optimizing changeover time comes in.

Changeover time is the period that it takes for workers to adjust machines or for assembly lines to start the next product run. A changeover usually includes swapping parts, sanitizing equipment, and preparing it for the next cycle. A good rule of thumb is to keep the changeover period down to less than 10 minutes. You can keep track of your organization’s changeover time by capturing how long it takes to produce each product.

Keeping an eye on your changeover time can help you maximize production and improve processes. Learn more about how you can reduce changeover time in manufacturing by exploring the following topics:

Three steps for reducing changeover time

Minimizing changeover time is a key component of lean manufacturing, a production method aimed at minimizing waste while increasing worker productivity. Implementation of this process can help manufacturers maximize uptime and cut down on waste caused by downtime.

Although there are various steps you can take to reduce it, here are some essential steps to help you get started:

Step 1: Assess your present changeover method.

It’s crucial to look at your existing changeover protocol before taking action to modify it. Try to identify which processes need optimization in order to cut down on the time between inventory runs.

Step 2: Implement single-minute exchange of dies (SMED).

Single-minute exchange of dies is a tool used in lean manufacturing to reduce changeover time to single digits. This means that a successful assembly run should be less than 10 minutes.

It’s helpful if workers have some idea of how long each task (such as switching parts, cleaning, etc.) takes during the production process. This awareness can be cultivated the more they familiarize themselves with procedures and day-to-day routines.

Step 3: Create standard changeover procedures.

Creating standard operating procedures (SOPs) and standardizing work can help with the changeover process. If there aren’t centralized procedures, changeover times will vary based on the employee, how long it takes them to clean up, set up and begin a new production run.

It’s important for procedures to contain explicit directions on how to perform successful changeovers. This can include highlighting which equipment needs to be calibrated and other machinery-related tasks.

Pro Tip

Digitizing changeover procedures can offer several benefits that enhance the overall efficiency, safety, and effectiveness of the changeover process. Digital procedures can be accessed by frontline workers through a mobile device or wearable technology, and help improve accessibility, accountability, standardization, as well as provide visual aids to less-experienced workers performing the task.

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In a nutshell, having clear instructions makes it easier for workers to know what to expect when it’s time for a changeover.

Benefits of reducing changeover time

Reducing changeover time can yield a number of benefits, especially for companies producing a large number of products on a day-to-day basis.

Some of the advantages include:

  • Makes it easier to transition between production processes
  • Creates a more productive work environment
  • Helps to reduce equipment downtime
  • Gets products to customers faster

How digitization can help

Implementing connected worker solutions that digitize and optimize changeover processes can help reduce the time each changeover takes by providing explicit digital instructions customized to any given task, machine, or worker.

benefits of digital work instructions

Digital work instructions are electronic versions of work instructions, quality manuals, or SOPs that provide necessary visual aids and real-time contextual information to help guide workers through complex tasks. These digital work instructions intelligently deliver guidance and streamline changeover processes with images, videos, augmented reality experiences, and live support from colleagues or subject matter experts.

Augmentir is the world’s first AI-powered connected worker platform that helps industrial frontline workers reduce changeover time in manufacturing using smart technology. Learn how world class manufacturers are using Augmentir to drive improvements across their industrial operations – contact us for a demo today!

 

 

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Benefits of Manufacturing SOPs and How to Write Them

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.

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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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Modernizing Manufacturing Training with Continuous and Workflow Learning

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.

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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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Generative AI Learning Copilots: Transforming Learning as We Know It

Watch Augmentir’s presentation at Learning & HR Tech 2024 and see how Generative AI Copilots transform learning and development in manufacturing.

Generative AI in learning and development has started to shape the future of HR across the board including attracting, developing, engaging, and retaining talent.

AI has revolutionized how organizations approach:

  • Talent acquisition – for smarter recruiting
  • Talent development – for skills analysis and performance evaluations
  • Worker relations – capitalizing on its ability to personalize employee relations
  • Workforce planning – leveraging its ability to make sense of data to perform more accurate forecasting and capacity planning
  • People analytics – using AI to make sense of employee data from an engagement and skills optimization standpoint
  • Performance management – relying on it for benchmarking and progress evaluation
  • HR operations – leveraging AI’s ability to automate and support onboarding and offboarding processes
  • Learning and development – using AI in everything from content creation to delivering personalized and adaptive content

generative ai learning copilots

However, Generative AI in learning and development has yet to make a significant impact on employees where it matters the most – in the flow of work.

This is where Generative AI learning copilots and AI-powered connected worker solutions come in. Together these technologies are transforming learning for frontline workers, improving onboarding, enabling learning in the flow of work, and driving more efficient upskilling and reskilling.

Watch our full presentation from Learning and HR Tech 2024 “Generative AI Learning Copilots: Transforming Learning as We Know It”, on-demand below.

Key Highlights:

  • Generative AI in learning and development has started to shape the future of HR across the board including attracting, developing, engaging, and retaining talent.
  • Deskless workers make up 80% of all workers globally and are underserved from a learning and development perspective, with 78% feeling they don’t have the right amount of training to succeed.
  • Generative AI Learning Copilots can generate training content, translate languages, provide real-time feedback, give on-demand guidance and answers, and serve as a digital performance support tool.

Generative AI Learning Copilots for Deskless Workers

Deskless workers, often referred to as “frontline workers”, generally do not sit in front of a desk and make up about 80% of all workers globally, they are on the front lines – in factories, at retail counters, construction sites, hospitals, and more.

While frontline workers and activities have undergone dramatic changes over the past few years, they are still woefully underserved from a learning and development standpoint.

  • 78% of frontline workers feel they don’t have the right amount of training to succeed at work
  • 65% want information on-demand and “in the flow of work”
  • Only 12% of HR operations leaders are actually satisfied with their L&D processes in support of their frontline employees

The reality is that traditional onboarding and training practices have been proven to be ineffective, however, much like AI has historically been used to improve the efficiency and output of machines, we can do the same with our frontline workforce.

AI learning and development tools and GenAI assistants can help:

  • Identify areas for content improvement, and implement those improvements
  • Measure training effectiveness
  • Create personalized, job-relevant training and curriculums
  • Measure and improve workforce effectiveness

Managing Manufacturing Workforce Challenges with GenAI Learning Copilots

The workforce crisis in manufacturing is accelerating and at the forefront of the minds of operations and HR leaders.

In fact, even if every skilled worker in America were employed, there would still be 35% more unfilled job openings in the manufacturing sector than skilled workers capable of filling them. Deloitte predicts that the skilled labor crisis will cost manufacturers upwards of $1 trillion by 2030.

In 2019, the average tenure in manufacturing was 20 years, the average time in position was 7 years, and the average 90-day retention rate was 90%. As of 2023, however, the average tenure is 3 years, the average time in position is 9 months, and the average 90-day retention rate was 50%.

These are representative of drastically different manufacturing realities. The workforce of 2019 is not coming back, and neither will productivity, unless organizations make significant investments and strides in supporting frontline workers with the appropriate tools and training. Luckily, smart connected worker and generative AI technologies offer a path forward.

Generative AI helps manufacturers answer:

  • What is the skills inventory of the team that is in attendance today?
  • Who can/should perform this work?
  • Who would benefit the most from targeted training?
  • Where should they focus on for process improvement?
  • What type of training would give them the biggest return?
  • What training materials need Improvement?

Generative AI-powered copilots and digital assistants can take this further, allowing frontline manufacturing workers access to vast amounts of knowledge in the flow of work when they need it most, helping to predict and prevent skills gaps before they impact production, and to design efficient and personalized development curriculums to shorten the time it takes for workers to be effective and competent in their positions.

Interested in learning more?

If you’d like to learn more about Augmentir and see how our AI-powered connected worker platform improves onboarding, training, skills management, and other learning and development aspects across organizations, schedule a demo with one of our product experts.

 

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Why Integration is Key for Connected Worker Platform Success

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.

A

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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