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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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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!

 

See Augmentir in Action
Get in Touch for a Personalized Demo