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The Connected Enterprise: Why a Connected Worker Strategy is Critical to Success

A connected worker strategy is critical to the success of your connected enterprise and digital transformation initiatives.

In today’s always-changing industrial landscape, organizations are acutely aware that adopting innovative technologies and processes is not just a “nice-to-have” but a “must” to stay competitive. According to PwC, 75% of manufacturers believe that Connected Enterprise technologies will have a major impact on their business over the next five years. By 2025, the number of connected devices in industrial settings is expected to reach 21.5 billion, making it clear that the adoption of connected technologies is a critical step for any organization that wants to succeed in the future.

connected enterprise

However, there is one aspect of a truly connected enterprise that many manufacturers overlook – their frontline workforce.

Frontline workers play a critical role in ensuring the safety, quality, and uptime of production operations, yet too often these workers are disconnected from the rest of the business. Connected frontline worker (CFW), refers to the use of technology to connect workers with the digital systems and processes in their organization, making it easier for them to collaborate, access information, and perform their jobs more efficiently. To fully realize the benefits of a connected workforce, it is essential to understand how they fit into the larger Connected Enterprise concept.

Learn more about what a connected enterprise is and the role that connected worker solutions play in the following sections:

What is a connected enterprise?

Connected Enterprise refers to the integration of digital technologies, data, and analytics across an organization’s entire operational landscape to improve efficiency, productivity, and profitability. Companies are rapidly adopting advanced technologies to improve their business operations. This concept spans several initiatives within an organization: assets and equipment, the products being manufactured, the end customer, operations, workers, and the entire supply chain.

connected enterprise - LNS Research

Source: LNS Research

Connected worker (or connected frontline worker – CFW) technology is a crucial part of this concept – as it connects the human workforce with the digital systems and processes in the organization.

How to create a connected enterprise

The first step to creating a connected enterprise is implementing smart, connected worker solutions. AI and connected frontline worker technologies are some of the leading solutions organizations are turning to on their path toward a Connected Enterprise. Augmentir has seen manufacturers achieve significant results after successfully implementing connected frontline worker solutions in conjunction with AI-driven analytics:

  • Up to a 72% reduction in training and onboarding times
  • More than 20% decrease in downtime
  • Nearly a 25% increase in productivity

Solutions that incorporate enhanced mobile capabilities and combine training and skills tracking with connected worker technology and on-the-job digital guidance can deliver significant additional value for an organization’s connected enterprise initiative. Data from actual work performance combined with AI-based analytics can inform workforce development investments, and deliver smart insights that reduce time to productivity, enable targeted reskilling and upskilling, and provide individualized guidance and support at the point of work so that you get the best each person has to offer.

connected worker as part of connected enterprise

However, companies need to be strategic and take a structured approach. It is imperative that the right solutions are identified and tested by the right divisions, personnel, and business units.

LNS Research has developed an “Industrial Transformation Reference Architecture” approach that provides a framework and simplifies implementation into four layers:

  1. Business Processes and Systems
  2. Connected Assets and Operations
  3. Data and Analytics
  4. Connected Worker

These guidelines give organizations reference points to help guide them along their path of industrial transformation and set them up for success in connecting their operations.

Key benefits of connecting your workforce to your enterprise

By leveraging AI and other smart technologies, companies are providing workers with real-time guidance and assistance, enabling them to perform their jobs more effectively. Frontline workers can access information, collaborate with colleagues, and receive real-time alerts on potential hazards, all of which help to improve their productivity and safety.

The benefits offered by AI and connected technologies are significant:

  • Improved efficiency: By automating routine tasks and providing real-time information, AI and connected worker technologies can help streamline operations and reduce errors.
  • Increased productivity: AI and connected worker technologies can help workers perform their jobs more effectively, enabling them to produce more goods in less time.
  • Better quality control: By providing real-time data on production processes and product quality, AI and connected worker technologies can help identify issues early and prevent defects.
  • Enhanced safety: Connected worker technologies can provide workers with real-time guidance and assistance, enabling them to perform their jobs more safely and avoid accidents.
  • Cost savings: By reducing downtime, improving efficiency, and enhancing product quality, connected worker technologies can help companies save money and increase profitability.
  • Improved decision-making: By providing real-time insights and data analytics, connected worker technologies can help companies make more informed decisions about their operations and identify new opportunities for growth.

According to McKinsey & Company, by 2030, the adoption of “Connected Enterprise” technologies is expected to generate $1-2 trillion in value for the global economy, including the manufacturing industry. As the transformation from paper processes to digital continues, industrial organizations are consistently finding that CFW solutions are an essential component of a larger “Connected Enterprise”. By leveraging AI and other advanced technologies to better analyze data and provide actionable insights, companies empower workers with the tools to perform their jobs more effectively, improving productivity, efficiency, and safety. Adopting AI and connected worker technologies is a key part of industrial transformation and of “Connected Enterprise” initiatives, offering industrial organizations an enhanced competitive advantage and solutions to many of the obstacles they face in today’s markets.

Implementing a connected enterprise with Augmentir

If you are interested in learning for yourself why companies are choosing Augmentir to help them connect, digitize, and optimize their frontline operations – reach out to book a demo.

 

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Why You Should Digitize and Standardize QA and Inspection Procedures

Learn how to digitize quality assurance, its benefits, and how digital inspection procedures reduce errors in manufacturing.

Quality assurance (QA) and inspection procedures work hand in hand to ensure customers receive quality products free of deficiencies. But what do the terms mean exactly?

QA is a systematic process that manufacturers use to ensure that a product or service meets the requirements for distribution. QA inspections are a subset of that process, checking products before they go off the line. Inspections are a crucial part in troubleshooting and fixing product defects, making improvements, and maintaining compliance. 

standardize digitize quality assurance manufacturing

These inspection procedures should be standardized and digitized to create a quality assurance system that ensures workers have access to the correct procedures and that tasks are performed in a standard manner to avoid errors on the production floor. This results in reduced defects, optimizes quality data collection, and decreases the need for rework.

Explore the following topics to learn how to decrease mistakes on the shop floor when you digitize and standardize quality assurance procedures:

Standardization and digitization explained

Standardization and digitization work in tandem. Let’s break down the two concepts to get a better idea of how they work.

Standardizing means developing a set of rules for how tasks should be completed. It boils down to this: When you standardize tasks, you’re giving your employees an established, time-tested process to use.

When done right, standardization decreases ambiguity, enhances productivity, boosts quality, and increases worker morale.

Digitization, on the other hand, involves converting information into a digital format. Keep in mind that it’s the information you are digitizing, not the processes or procedures. Automating your work processes using a single system, like a connected worker platform, makes everyday operations much faster and easier to accomplish. Enhancing this further with AI-driven analytics and process optimization empowers manufacturers and frontline personnel with the right tools for quality data collection and inspection procedures.

 

standardize and digitize quality assurance procedures

How standardizing QA and inspection procedures reduces errors

According to LNS Research, to digitize quality assurance processes, manufacturing leaders must leverage emerging technologies. This allows them to achieve step-change improvements across operations. When you standardize quality assurance procedures, you’re ensuring processes are completed using best practices and proven methods.

Think of it this way: When workers complete tasks using their own choice of tools, platforms, or reporting mechanisms, it’s harder to measure and evaluate which procedures are bringing value and which ones are not. It also leaves a lot of room for human error and inefficiency.

QA and inspection procedures should be standardized so that a worker’s way of doing things aligns with the company’s overarching objectives. If you don’t standardize inspection procedures, you’ll have a more difficult time pinpointing product deficiencies and worker errors.

Smart, connected worker platforms and AI-based software allow manufacturers to standardize processes across all units, creating a single source of truth for a truly optimized procedure that can be audited and verified, resulting in fewer errors, reduced defects, and more expedited inspections overall. Every procedure, regardless of how often it’s performed, can have guidelines that define the scope and methods for how to perform it. This in turn ensures a higher quality result every time.

How digitizing quality assurance procedures minimizes mistakes

Converting your paper-based QA procedures to a digital format is one of the smartest things a manufacturer can do. From there, you can set up a unified system to improve QA assurance processes.

Workers are only human, and quality assurance systems safeguard the production process. It identifies mistakes as they happen and uses communication tools to reduce the risk of error. Other strategies such as a “first time quality” (FTQ) or first time right plan enhance standards, practices, and resources to ensure all processes on the production floor are performed correctly the first time.

Deploying an integrated system makes it easier to:

  • Gradually improve your production processes
  • Standardize your QA methods
  • Digitize manufacturing processes

 

Connectivity and connected worker technology empowers all workers to do their jobs better and in a timelier manner. It also gives managers the opportunity to track how well employees are carrying out standardized QA procedures and inspections. When coupled with AI-driven analytics that can process the massive amounts of data connected workers generate, manufacturers are able to derive better insights, faster, and with higher reliability. This essentially transforms frontline workers into quality assurance sensors that further enhance and empower quality inspections.

If you’re still using paper checklists to track procedures, you’ll never see beyond what’s in front of you. By digitizing analog paper practices you are enabling better quality data collection and inspection procedures and strengthening your overall manufacturing operations. 

Thankfully, Augmentir’s connected worker solution gives real-time visibility into all operational processes, from anywhere. Industrial companies use our breakthrough system to standardize and digitize quality assurance procedures.

 

 

If you are interested in learning for yourself why companies are choosing Augmentir to help standardize and digitize their quality assurance procedures – reach out to book a demo.

 

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Autonomous vs. Preventive Maintenance

Learn about autonomous and preventive maintenance, and how they can maximize machine efficiency and worker productivity on the shop floor.

Autonomous and preventive maintenance are two manufacturing strategies for maintaining machinery on the shop floor. The main difference between the two is that autonomous maintenance (AM) places greater responsibility for equipment upkeep on operators, while preventive maintenance (PM) is carried out by maintenance workers. Both autonomous and preventative maintenance strategies benefit from smart, connected worker technologies, although in different ways.

autonomous vs preventive maintenance

AM, for example, focuses on training machine operators to be the point of reference for cleaning, inspecting, and making minor repairs on the spot. This approach aims to empower operators to take the initiative in monitoring their equipment and identifying issues early on. By introducing smart, connected worker technology, like Augmentir’s suite of connected worker tools and closed-loop autonomous maintenance solution, manufacturing leaders can give operators more control over inspections and help intelligently guide and support operators, resulting in minimized machine downtime.

PM, on the other hand, consists of scheduling regular maintenance activities like part replacement, lubrication, and calibration. Workers tasked with PM ensure equipment remains in tip-top condition, which helps to prevent future breakdowns. The goals of this strategy are to avoid machine downtime and reduce the need for unplanned repairs. Smart, connected worker solutions improve the quality, transparency, and efficiency of both autonomous and preventive maintenance and repair procedures by standardizing and optimizing maintenance procedures.

You can learn more about autonomous and preventive maintenance by exploring the following sections:

What’s autonomous maintenance and its advantages?

Autonomous maintenance involves machine operators tackling basic equipment upkeep tasks to ensure that everything runs smoothly on the production floor.

When implemented, AM can yield a number of benefits:

  • Reduced equipment downtime: Conducting routine upkeep activities can prevent breakdowns and limit the need for unplanned maintenance.
  • Greater machine reliability: Operators who are trained to maintain their own equipment are more likely to pinpoint problems before they lead to machine failure.
  • Prolonged lifespan of machinery: Equipment that is maintained will last longer and require fewer repairs or replacements.
  • More operator involvement: Operators who take an active role in preserving their machinery feel empowered.
  • Increased safety: It’s easier to troubleshoot potential hazards before they turn into accidents when operators frequently inspect and maintain their equipment.
  • Cost-effectiveness: Reducing unplanned maintenance can save manufacturers significant money over time.

When coupled with smart, connected worker technology and AI-driven analytics, AM’s benefits are further enhanced. Digitizing autonomous maintenance processes increases standard work adherence, clears defects faster, and improves auditability. Connected worker technology enables operators to share knowledge and gives them access to the resources they need right when they need them.

autonomous maintenance

 

What’s preventive maintenance and its benefits?

Preventive maintenance focuses on performing routine equipment upkeep tasks at scheduled intervals. The goal is to avert equipment failure and limit unplanned downtime or repairs.

The benefits of having dedicated workers perform preventive maintenance are:

  • Enhanced machine reliability: Regular maintenance increases the odds of identifying and fixing problems before they turn into mechanical failures.
  • Decreased downtime: Conducting routine upkeep at scheduled times can decrease unplanned maintenance and increase production efficiency.
  • Greater compliance: PM can help manufacturers better comply with regulatory requirements to prevent unnecessary penalties for non-compliance.
  • Better planning protocols: Recruiting specialized maintenance personnel with extensive training on machine upkeep and repair can lead to better planning and allocation of resources.
  • Increased safety: Training workers on basic maintenance techniques ensures that deficiencies are addressed in a timely manner to avoid any injury.

PM’s impact is improved when used alongside smart, connected worker solutions that allow for digital work instructions and remote collaboration to effectively and efficiently guide technicians. Additionally, by digitizing and automating maintenance notifications, organizations can improve communications, speed up maintenance procedures, and minimize machine downtime.

How to implement AM

Applying autonomous maintenance to everyday maintenance tasks can mitigate potential machine disasters. Organizations can take this even further by creating “smart” autonomous maintenance processes and implementing advanced connected worker solutions with AI-driven insights. This gives operators improved control over maintenence process and expert guidence through a searchable asset hierarchy, maintenance history, and troubleshooting database.

The seven steps of effective AM implementation:

  • Boost operator expertise: It’s important to train operators on the machines themselves and how to perform maintenance tasks. This type of training can be made more effective through AI-based insights that integrate skills management into the flow of work and identify workforce development opportunities for upskilling and reskilling.
  • Conduct initial cleaning, inspection, and repairs: Operators should execute regular maintenance activities to avoid unplanned downtime. Furthermore, with connected worker solutions, operators can use mobile devices to digitally track and manage issues and activities as well as automate maintenance notifications further reducing overall downtime and avoiding unplanned downtime.
  • Eliminate causes of contamination: Routine cleaning and inspection minimize sources of contamination such as improper calibration and defective equipment. This alone can help prevent unexpected machine breakdowns. By building smart workflows into the autonomous maintenance process, manufacturers can schedule and assign standard work procedures (such as routine cleaning and calibration) digitally that have built-in work reporting for better visualization and auditing.
  • Define standards for cleaning, lubricating, and inspecting: Nailing down how to clean, lubricate, tighten and inspect, and how often to perform these upkeep duties, can help keep equipment in pristine condition. Smart digitization can standardize these practices across all manufacturing operations, giving organizations a global best practices standard to measure standard work adherence, clear defects more quickly, and improve auditability.
  • Perform inspection and monitoring: Operators who are trained on maintenance processes can carry out maintenance tasks independently and without error. With smart skills management and AI-enhanced workforce development, organizations can reduce training time and provide individualized guidance and support to workers when and where needed.
  • Standardize visual maintenance: Incorporate visual aids that help operators better understand equipment and labeling. For example, written procedures could contain a diagram showing how fluids should flow in a particular machine. Continuous learning and personalized insights via connected worker solutions are able to take this one step further and integrate things like instructional videos, interactive diagrams, and even remote experts into the flow of work to improve operational excellence and productivity.
  • Work towards continuous improvement: It’s imperative to strive for continuous improvement in maintaining machinery. Operators who are constantly learning and evolving are more productive and empowered with better decision-making capabilities through actionable, AI-driven insights.

Learn more on how to implement autonomous maintenance and the seven steps involved, or get in touch with us for a personalized demo to see Augmentir’s Autonomous Maintenance solution in action.

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How to implement PM

According to Forbes, when implemented correctly, preventive maintenance ensures that upkeep is performed at a set time to prevent unexpected machine deficiencies. Smart, connected frontline worker solutions are able to improve preventative maintenance procedures through smart communication, scheduled notifications and improved collaboration.

Eight steps for implementing preventive maintenance:

  • Establish project scope: Gauge which machinery will be inspected and which maintenance tasks are needed to be done at specific intervals.
  • Pinpoint upkeep requirements: Set requirements for which tasks are crucial for each piece of equipment. Tasks could vary from lubrication and calibration to inspections and part replacements.
  • Create maintenance schedule: Create a set schedule for carrying out PM tasks that’s based on equipment requirements, production schedules, and planned downtime.
  • Allocate worker responsibilities: Assign which tasks each maintenance worker is expected to fulfill.
  • Provide necessary resources: Give staff the proper tools, equipment, and supplies to execute PM tasks (e.g., lubricants, replacement parts, testing equipment, etc.).
  • Define metrics: Establish metrics for gauging the efficiency of PM (e.g., downtime, equipment reliability, maintenance costs, etc.).
  • Create training programs: Hands-on training and how-to instructions can help maintenance workers better understand how to perform upkeep tasks.
  • Monitor performance and adjust: Measure how well your PM efforts are doing and revise if necessary. This may mean updating procedures, adjusting maintenance schedules, or creating more training opportunities.

All of these steps are able to be standardized and optimized through connected worker solutions. Augmentir’s suite of connected worker tools delivers in-line training and support at the point of work, provides a searchable database to allow workers access to knowledge when and where needed, gives workers individualized guidance and support, connects teams for better collaboration, and more. This approach helps standardize and optimize maintenance processes and notifications as well as training, offering a better, more efficient adoption process for both frontline workers and management from start to finish, and giving everyone the proper tools for successful manufacturing operations.

 

If you are interested in learning for yourself why companies are choosing Augmentir to help digitize and optimize their autonomous and preventive maintenance programs – reach out to book a demo.

 

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How Skills Tracking Improves Work Allocation and Workforce Utilization

Learn how skills tracking enhances work allocation and workforce utilization to improve productivity in manufacturing.

Employee skills tracking is an excellent way to stay ahead of the curve in today’s ever-changing manufacturing landscape. Leaders can use this talent management strategy to close worker competency gaps, increase effective training, and hire qualified prospects.

Putting an emphasis on employee skills can also help manufacturers prioritize work allocation and workforce utilization. But what exactly do these two terms mean and how do they relate to tracking skills in manufacturing?

Work allocation is the process of assigning resources and roles to meet the objectives of a given task or production facility. Workforce utilization, meanwhile, refers to how a company or organization effectively utilizes its workforce to meet its operational goals and objectives.

skills tracking and workforce utilization in manufacturing

To keep up with competition, manufacturers should not only try to recruit the best possible hires, but also allocate work in an effective way to retain staff, satisfy customers, and boost profits.

Ultimately, keeping track of skills is a beneficial way to organize a company’s resources to attain sustainable business goals. Implementing a connected worker solution and digitizing skills management processes through smart manufacturing technologies is an effective way for organizations to instantly visualize the skills gaps in teams as well as track workforce skills and quickly assess both team and individual readiness.

Learn more about digital skills tracking and how it improves work allocation and workforce utilization below:

Skills tracking defined

Skills tracking helps ensure that all workers have the necessary expertise to complete tasks to their fullest potential. Basically, it closes the gap between the competencies employees already have and ones they need to further develop.

Every manufacturing firm has a unique set of job requirements and expectations. Tracking worker skills on a regular basis helps a company identify training needs and build workers’ knowledge so that they can meet expected targets. Skills management and tracking software help manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.

skills tracking software

In a nutshell, measuring employee proficiencies can boost retention, decrease the amount of time spent on tasks, and improve overall productivity.

Benefits of tracking skills to improve work allocation

Through digitization and effective skills tracking, manufacturing firms can best allocate work to team members based on expertise, credentials, and actual ability. For example, an operator who has more than 10 years of experience using computer-controlled equipment may be a better fit to handle complex machinery than an entry-level worker who lacks that training.

Additionally, with a centralized digital repository managers have a better idea of each employee’s current skills level and potential areas of improvement. Then they can close any skill gaps through training opportunities. In return, workers who receive the necessary training are more likely to thrive in their roles and be productive.

In summary, measuring worker skills can help improve work allocation by:

  • Hiring or assigning current employees to the correct jobs and tasks
  • Facilitating worker development through mentorship and training
  • Retaining high-quality employees

How tracking skills boosts workforce utilization

Workforce utilization refers to how much of an employee’s time is devoted to billable work. Tracking skills can improve this, in turn boosting productivity and profits.

When you measure how efficiently employees are doing their jobs and how well a business manages its resources, you can assure that tasks are done well and see continuous increase in revenue. Think about how many hours of each staff member’s workweek need to be billable to remain profitable and whether they are on track. With a digitized tracking system, manufacturers are able to automate and streamline this process reducing errors, improving productivity, and ensuring success.

Pro Tip

Through the use of smart, connected worker solutions and AI-based workforce insights organizations can deliver continuous, on-the-job learning based on skill tracking and real job performance, promoting reskilling and upskilling efforts enterprise wide.

To summarize, tracking skills can help enhance workforce utilization by:

  • Setting profitable rates for services based on worker output and time billed
  • Compensating employees fairly
  • Gauging whether staff is being overworked or underutilized

By digitizing these tracking processes and implementing AI-driven support, organizations can also visualize, track and offset employee burnout. By taking highly granular connected worker data and using AI to filter out the unnecessary portions, industrial operations are able to not only improve tasks and productivity but better support and empower frontline workers.

Ways to track workforce skills

Tracking employee skills is a great way to improve worker performance and productivity by matching the right person with the right assignment.

One way to track an employee’s skills is through a skills matrix, which is a grid that maps staff credentials and qualifications. A skills matrix helps managers strategize and oversee current and wanted skills for a team, position, department, and more. A skills matrix is usually managed using a spreadsheet, but there are alternatives to skill matrices. For example, cloud-based skills management software can help identify and track employee competence and correlate it with actual job performance. The software can also help managers filter employee databases by skills to assemble teams or assign work based on specific qualifications.

skills matrix

Leadership can also track competencies through a skills taxonomy. Taxonomies help classify and organize skills into groups to better understand which skills employees have and which they should learn. Essentially, these structured lists help management identify and track skills to better allocate resources and worker training opportunities.

Lastly, a skills-tracking application can include AI-based software to identify and measure worker expertise and actual job performance. This is an excellent method for intelligently assigning work through skills mapping, optimizing training programs, and more. With AI-based insights and connected worker technology, organizations can bridge the gap between the training room and the shop floor, integrating training into the flow of work and creating an environment of continuous learning.

Skills management with Augmentir

Augmentir offers top-notch solutions to easily track and manage your frontline’s skillset. Our connected worker solution provides customized dashboards to streamline processes to improve workforce management, skills management, and deliver in-line training and support at the point of work, closing skills gaps at the moment of need.

If you are interested in learning how Augmentir can help improve your skills management, skills tracking, and workforce development – request a live demo.

 

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How an Asset Hierarchy Can Help with Asset Maintenance

Learn about what an asset hierarchy is and how it can help with asset maintenance and equipment reliability.

An asset hierarchy outlines all of a business’s top equipment, machines, and components visually to help the business plan, execute and track maintenance activities. Asset hierarchies are usually in the shape of a pyramid, similar to an organizational chart. And since every operation is different, it’s likely you won’t have the same hierarchy as your competitor.

The benefits of an asset hierarchy include accurate maintenance planning, faster failure root cause analysis, and improved cost tracking. By implementing an asset hierarchy in conjunction with a frontline operations system, such as a connected worker solution, manufacturers can benefit by dramatically improved maintenance planning and execution. This article answers the following questions to help you learn more:

asset hierarchy improves maintenance

What is an asset hierarchy?

An asset hierarchy is an index of your most critical equipment, machines, and parts to better understand how these assets work together and monitor their maintenance needs. For example, building and maintaining your manufacturing business’s hierarchy can help you track and identify root causes of failure in your equipment.asset hierarchy and taxonomy - iso standard

This taxonomy is often represented as a pyramid, based on the ISO 14224 standard, which was developed for the collection and exchange of
reliability and maintenance data for equipment. Initially developed for the Petroleum, Petrochemical, and Natural Gas industry, this taxonomy for equipment and failure data can apply to any manufacturing environment, and has become the de-facto standard for every other industry.

Asset hierarchies are typically built and maintained within an organization’s EAM (Enterprise Asset Management) or CMMS (Computerized Maintenance Management System), which tracks asset maintenance and condition data, as well as maintenance schedules. Increasingly, EAMs, CMMS, and asset hierarchy information are being integrated with digitized frontline operations systems to improve maintenance planning and execution.

Pro Tip

It’s not enough to simply define your asset hierarchy with your EAM or CMMS. Innovative manufacturing companies are now extending this by integrating their asset hierarchies with connected worker solutions, which help digitize and optimize the actual work being done by frontline maintenance teams, improving maintenance execution.

A

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.

What is asset maintenance?

While maintenance is generally synonymous with repair, in effective manufacturing facilities, maintaining equipment can prevent the need for repairs. Asset maintenance is an umbrella term for everything that goes into keeping your assets in tip-top shape.

For example, asset maintenance in manufacturing machinery may mean frequent inspections to prevent breakdowns and repairs. Your space as a whole relies on this type of maintenance to ensure everything is running smoothly, from equipment to everyday production processes.

Lastly, this term makes daily manufacturing processes more productive to manage. That’s because effective asset management tells you where assets are located, how they are used, and when changes were made to them.

How does an asset hierarchy improve asset maintenance?

An asset hierarchy and asset maintenance work in conjunction with one another. This visual tool gives workers a better idea of what each asset is and the dependencies between them.

Knowing what each asset is can help you schedule preventative inspections and tasks. If any problems arise, you can more easily identify all the working parts, find the root cause and fix it.

 

Augmentir’s AI-powered asset management software helps you simplify the operations and maintenance of your facility by integrating your asset hierarchy and maintenance data within a frontline operations system. Through Augmentir, organizations can benefit from a complete view of asset management, all through a visual mobile interface. Each asset contains a complete view of:

  • Kanban board for all asset activities
  • Work and maintenance procedures
  • Skills required for operation and maintenance
  • Collaboration related to the asset
  • Associated documentation
  • CIL/Standard Work schedule
  • History of all activities on the asset

Asset management with Augmentir

Augmentir’s asset management capabilities include an out-of-the-box autonomous maintenance solution, which gives equipment operators more control over equipment cleaning, inspections, and lubrications (CIL) to improve CIL completion rate, resulting in minimized machine downtime.

Request a live demo today to learn why companies are choosing Augmentir to help standardize and digitize their maintenance activities.

 

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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.

A

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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