EAM Blog

Manufacturing Execution Systems Explained

Humans have continually striven to improve upon the tools and processes they’ve developed throughout history to make the tasks for which they’re used easier and more efficient. This has led to developing inventions and improvements that have become integral to human society. Manufacturing automation has also undergone such a transformation in smart factories. One key tool that has helped manufacturers attain higher productivity levels is the manufacturing execution system (MES), which ties together automated systems within industrial settings. (more…)

How To Automate Defect Detection with Machine Vision

Quality assurance (QA) began as a philosophy during the Industrial Revolution. In the late 19th century, American engineer Frederick Winslow Taylor developed a new system for improving efficiency and productivity in factories. His methods focused on providing training for employees, rather than allowing them to just learn on the job. The protocols Taylor implemented were also based in science, which is why he also promoted rigorous documentation.

In 1911, he published a book explaining his QA methodology. Taylor’s techniques have since proved integral to the world of manufacturing. Automation has largely replaced the manual QA methods he promoted, as technology and software have both advanced to perform increasingly complex tasks. As an important aspect of the QA process, defect detection has evolved as well, with machine vision now becoming an important means for ensuring efficient production.

The Importance of Quality Assurance

Quality AssuranceBefore looking into the custom automation that’s now being used for detecting defects, it’s important to understand the importance of QA in modern manufacturing. Automation has certainly enhanced the quality of goods coming out of factories, but defect detection has been a part of manufacturing prior to the introduction of this new technology.

Developed in the 1950s, a system known as the Failure Mode and Effects Analysis (FMEA) became one of the first structures for improving products and processes. The FMEA methodology is still used today, though variations have been developed for specific purposes. It helps manufacturers anticipate failures, either in the design stage or the manufacturing process.

The steps for developing an FMEA are:

  • Define scope of FMEA: This step involves collecting key information in order to determine what aspects of a product cause failure. This step involves investigating documented cases of defects in order to develop a plan for identifying and reducing their prevalence in end products.
  • Strategy development: This stage of the process looks at the information from these documented events, calculating what functions are likely to fail, how they’re likely to fail, the effects of this failure and how to measure the severity of a failure.
  • Defining processes: This point in the development stage involves looking at the potential causes of failures, which are selected either from design inputs or past failures.
  • Determining mode of failure: This part of the development process looks at adding a means for detecting defects by ranking them, which helps ensure that a product is properly designed and what may happen should specific defects in a product are passed on to the end user.
  • Calculating risk and prioritizing remediation: Actions taken in the three previous steps – strategy development, defining processes and determining the mode of failure – are then assigned a risk priority number (RPN) to determine how these issues should be remediated. To calculate the RPN, the severity and occurrence of a potential failure is considered, along with detection rankings.
  • Taking corrective action: This element of the process consists of countermeasures taken as a means to reduce risk of failure.
  • Assessment: Once actions to mitigate risk have been taken, the ranking system adjusts to calculate a new RPN to improve product design or the production process.

This manual process for defect detection is increasingly being enhanced via automation. Engineering defects can be spotted much more easily by technologies like machine vision, whereas human inspectors are inconsistent in their classification of defects. This inconsistency leads to variable quality of products depending who is doing the inspecting.

Using Automated Visual Inspection for QA

Often referred to as machine vision, these programmable systems offer a means for inspecting an array of industrial applications. They utilize a smart camera specifically calibrated to automatically inspect products and processes in real-time. They essentially replace human inspectors, helping to identify any irregularities along the production line or problems with the manufacturing process.

Machine vision inspection systems increase efficiency, and generally pay for themselves within 24 months. While they perform tasks more proficiently than human eyes, they do have their limitations. Many of these are due, however, to the fact that designers often don’t take into account

Machine vision systems sometimes have difficulties due to factors like:

  • Camera resolution
  • Lack of quality data
  • Lighting anomalies
  • Shutter speed
  • Type of defect

To detect defects, machine vision systems look at a product’s surfaces and dimensions during manufacturing. Automation of QA is very much based upon statistics, much like the manual FMEA models. Computers are very good at forecasting probabilities and can be programmed to detect whether a product on the assembly line falls within specific parameters. From these calculations, artificial intelligence (AI) software then helps the system determine whether a product is defective.

This doesn’t mean the end of human QA inspectors, however. Machine vision capabilities depend on cataloguing defects so that the system can automatically do its work. These directories, collated with the help of human QA inspectors, help the AI ascertain what’s acceptable and what isn’t.

Types of Machine Vision Systems

There isn’t just one kind of machine vision system used for manufacturing. Automation of this type is diverse and can be used for numerous applications. Factors that affect the type of machine vision system needed include a manufacturer’s budget, properties of the process or product, inspection speed needed and other factors.

The different types of machine vision systems include: 

  • Custom automation packaging: These systems specifically look at packaging, designed to both meet specific quality standards and limit false rejections; they inspect for such things damage to items, misapplied labels and any deformities to a product packaging’s molded features.
  • Defect detection: These systems catch and resolve issues related to the product or its packaging; working in real-time, they identify broken components, faulty seals, misplaced labels, surface deformities and other defects.
  • Print and code inspection: By identifying damaged or incorrect product labels, these systems check for things like unreadable barcodes, text quality, incorrect nutritional or ingredient labels, artwork quality and other labeling issues.
  • Process control: These machine vision systems work to perfect processes on a production line, enabling precision control of robots, gathering and applying measurements within data logging systems, collecting historical process data, logging data trends, monitoring systems and other imaging tasks along the production line.
  • Tolerance measurements: When a machine vision system is integrated into a production line, it helps ensure the quality of products, making these production standards repeatable; these systems can verify component tolerances, compare finished products with computer-assisted design (CAD) images, count threads, inspect heat seals, scan with cameras or lasers, analyze radiometric data and provide other information regarding product fabrication.
  • Webbing inspection: These systems use real-time image processing to detect any damage to webbing, while also resolving these defects by removing damaged webbing sections.

Manufacturing Automation for Defect Detection

Automated visual inspections offer a means to improve the quality of end products while making manufacturing processes more efficient. Advances in AI have made this possible, with machine vision now capable of performing better in certain cases than human eyes. Additionally, they’re ideal defect detectors as, unlike humans, they don’t get distracted, tired or sick.

Developing a custom automation system for visual inspections involves these steps: 

  • Camera installation requires first choosing the best camera and lens for the application, along with ensuring the camera is well-positioned and has optimal lighting.
  • The AI needs images to be able to accurately perform visual inspections, so there must be adequate storage for these, with backups performed regularly.
  • Each image should have annotations to assist the AI when doing inspections, with which machine learning algorithms should also be developed.
  • Using AVI video files, a highly accurate model should be fabricated to train the AI and assist in its deployment.
  • These models should then be validated so that the AI can properly conduct its tasks, which entails creating a document to detail what’s in the AVI system.
  • As a final step, a dashboard should be built so that operators, using process control software, can check on the inspection results; this dashboard can also include such things as the proportion of defective products over time, number of defects by category and other QA statistics.

AI has enabled manufacturers to perform tasks that once required human brainpower with the support of machine vision. It has enabled this technology to be used for a wide range of applications, combining hardware with software to facilitate QA manufacturing automation. Engineering these automated visual inspection systems to perform ever more complex QA duties is the future of machine vision technology.

3 Flexible Automation Examples Explained

When industries utilize tools and systems that allow them to quickly change from one task to another, it’s referred to as flexible automation. Engineering robots or automated systems to switch from one type of operation to another via a command change to a controller or altering a line of code in software enables smart manufacturing facilities to quickly adjust when needed. For example, robot arms can be pre-programmed to conduct a variety of tasks along a production line, such as drilling holes inserting rivets or screws, sanding, spray-painting or welding.

This kind of custom automation expands the capabilities of industrial facilities through the use of a simple-to-use yet sophisticated computer programming. It gives factories, warehouses and other facilities that utilize manufacturing automation a means to teach their automated equipment new skills. In essence, it’s a form of artificial intelligence, which with current technology could even respond to verbal commands or react automatically to visual cues. The possibilities of flexible automation for industry are nearly endless.

Flexible Automation: Engineering Factories for the Future

The theory of flexible manufacturing emerged in the 1960s with the introduction of automated technology to the production line, as computerized numerical control (CNC) machines, programmable controllers and robots began to take over factory floors. Today, it allows industrial equipment to be programmed to do a number of specific tasks, and enables changes to these tasks within a short time frame. This offers factories flexibility in their processes, permitting them to switch production between different types of products quickly.

Typically, flexible automation systems consist of the following: 

  • Part processing machines: CNC machining equipment carries out a portion of these processes, with inspection and other automated work stations used in combination.
  • Material-handling system: Conveyancing and other systems move parts from one area along the production line to another, with robots generally used for the loading and unloading of product.
  • Central computer control system: Communications that come from this central controller provide component routing information and adjust timing within the material-handling system while also coordinating the operational processes of these machines.
  • Human labor: While these systems are based around automation, engineering this flexibility still requires humans to manage, repair, maintain and alter procedures when necessary.

Flexible automation systems have highly automated processes that allow them to produce smaller batch sizes as efficiently as bigger production runs. Such fabrication techniques are ideal for on-demand manufacturers, many of whom deal with smaller orders from e-commerce distributors. Though typically these methods are associated with front line manufacturing, automation flexibility can be applied to other processes, such as packaging.

Examples of Flexible Manufacturing Automation

Flexible manufacturing techniques allow low-volume and high-mix manufacturers to apply custom automation equipment with negligible cost implications. These techniques and the technology that support them permit manufacturers to react rapidly to design modifications, new orders or even market changes, while also making small batches of product more economical to fabricate. This flexibility is not only used in product manufacturing, automation can be used in the packaging process as well.

Robots are being used with increasing frequency in packaging operations. Robots have been adapted to handle products with a variety of sizes and shapes, including more delicate products. This is especially true of collaborative robots that work alongside human operators. Capable of dealing with changing requirements and environments, they’re easy to train for new tasks. Such manufacturing automation has become more commonplace within the packaging industry, including with automated packaging, source tagging and automated labeling.

Automated Packaging 

Manufacturing automation for packaging products is as diverse as the types of products that require packaging. Packaging ranges from wrapping single pieces of candy that’s then bagged for consumers to whole shrink-wrapping pallets of products in preparation for shipping to a distributor. Depending on the product, packaging machine designs must meet the requirements of a manufacturer or distributor, and often these systems are highly customized. Automation for packaging depends upon the type, size, fragility and other elements of the items being packaged, so the design of packaging systems should provide a wide range of capabilities.

Custom automation in packaging equipment should include the following capabilities:

  • Easily integrated with other manufacturing automation systems
  • Feature up-to-data safety technology
  • Programmable operations that are data-centric
  • Real-time diagnostics for maintenance and servicing

Automated packaging equipment maximizes efficiency, allowing smaller manufacturers to stay competitive against mass-produced packaged products. Current automation engineering also makes it possible to accommodate more types of products with distinct packaging requirements. It helps manufacturers to reduce the time it takes to package a product, thus reducing operating costs.

There are three general types of packaging automation: primary, secondary and tertiary.

Primary Packaging Automation

Whether it’s a head of lettuce or an automotive component, primary packaging is what a consumer sees when buying a product off the shelf in a retail outlet. Regardless of the product, manufacturers need to consider a number of issues regarding equipment, including floorspace, quality control, throughput and volume. Consideration must also be paid to what’s being packaged, particularly any cleanliness requirements and dimensional issues. How the product is presented also matters, as packaging is also a form of marketing.

The first stage of automated packaging involves equipment like:

  • Conveyancing system to infeed or outfeed products.
  • Hoppers for gathering products from which they’re conveyed in a steady flow.
  • Linear feeders that both orient and sort the product.
  • Vibratory bowls that help orient bulk products as they’re fed singly through other machinery.

Packaging systems are designed to classify, orient, allot, position and introduce products quickly, and in a manner that won’t damage the product.

Secondary Packaging Automation

Also known as case packaging automation, it involves packaging single products together in larger cases, or other types of containers, to protect them when in transit. Custom automation equipment provides greater speed, reliability and accuracy to packaging than manual packaging. For equipment at this stage, flexibility is integral to deal with changeovers in products. Manually packaging at this stage often requires much more space for material storage and workstations, while packaging automation often will reduce the space needed.

There are a few different types of custom automation at this stage. The most common method involves top loading cases vertically, which is typical for bags, bottles, cartons, flow packs, pouches and sachets. To create a smaller footprint when packaging, a method referred to as side load case packaging entails mainly packaging retail cartons or other structured products horizontally. Wrap-around case packaging offers the lowest cost, using precut flat sheets that seal the sides of the product; this method is often used for canned beverages or foods.

Tertiary Packaging Automation

This final stage of packaging automation – also described as end-of-line packaging – prepares products for shipment to retail outlets or warehouses. Providing protection during shipping, this method allows products to be moved easily in bulk. Though mechanical palletizers have been around for decades, flexible automation utilizes robotic palletizing systems for greater efficiency. While generally more reliable, their greater flexibility and smaller footprint make them more desirable in manufacturing. Engineering of these systems allows them to perform multiple tasks, sometimes even simultaneously, including packaging products, loading boxes onto pallets and wrapping pallets in shrink wrap.

Source Tagging 

Source tagging is the application of electronic article surveillance (EAS) tags or labels, applied onto or within a product during packaging or manufacturing. Automation of this process saves time, with hard tags used for source tagging clothing while adhesive labels typically go on inflexible merchandise. Many of these tags or labels use radio-frequency identification (RFID) or similar technology to protect items against theft, or to automatically reorder items when stock gets low. RFID tags can also be used on packaging to track their location within the supply chain.

When introducing electronic ID tags, it’s important to understand:

  • Precise purpose for tags or labels
  • At which frequency tags or labels will operate
  • Conditions under which they’ll be operating
  • Scanning equipment to be used to read them
  • Length of lifecycle for tags or labels
  • Expected lifecycle of the label or tag

Source tagging adds value to a product, as retailers don’t then need to add anti-theft devices themselves, while this procedure is made much quicker due to automation. Engineering RFID tags into packaging also improves the speed of processing orders and accuracy within inventories. Their use in packaging and logistics helps manufacturers automate workflows, data collection and processes, along with helping to identify bottlenecks and improve visibility throughout the supply chain. When large volumes of goods require quick shipping and receiving, an electronic tag that details all contents of a pallet will save manufacturers time. And it does this without one box having to be opened or moved.

Source tagging doesn’t come cheap, however. Costs go well beyond acquiring tags or labels. Tagging merchandise and goods requires investing in automated equipment, changes to processes, new design features and the labor involved in installation of these systems. As these systems become more common in the packaging industry, however, these electronic tags are being reused and recycled.

Automated Labeling

Manufacturers use labels to identify and market their products. Manual labeling systems are normally either inflexible or only accommodate labels within a certain size range. Conversely, automated labeling systems work for a wide range of label sizes. Having a single machine that can be configured for a diverse assortment of product types and sizes allows greater flexibility during the packaging process.

While automated labeling is commonly used by manufacturers for packaged products and in the packaging industry, automatic labelers have become increasingly more flexible in what they can do. Those that integrate robots within a flexible manufacturing system into their automated labeling systems offer numerous benefits.

These automated labeling machines will often feature capabilities that include:

  • AI that enables a robotic arm to act intelligently within its programming while placing labels.
  • Implements designed to keep from damaging the product.
  • Label dispenser/applicator to dispense and apply labels of varying dimensions.
  • Machine vision camera systems to allow them to accurately and precisely place labels, even on randomly placed products.
  • Memory storage within the labeler with figures on how to calibrate the machine for labeling different products.
  • Motor for roller or other implement to apply labels.
  • User interface to permit human operator to adjust, monitor, control and load configurations.

Stored calibration information allows operators to set machines for a single label, then recall these settings when needed again. Labeling machines also need to consider such things as the pressure needed for precise application and speed of operation necessary to keep up with the production line. Considering the advantages for manufacturing, automation for labeling processes allows factories to label products in batches economically enough to compete with mass-produced labeling.

Flexible Automation Solutions by EAM

EAM Inc. has provided custom automation solutions for manufacturers since 1967. Our automation expertise has been applied to production lines for the medical, food processing and other industries. From the integration of robots with machine vision capabilities onto factory floors to automated labeling and source tagging of products, EAM provides manufacturers and packaging companies with automated capabilities that allow them to improve the efficiency, speed and accuracy of their production lines. To learn more about the automation solutions we can provide to increase the profitability of your business or factory, contact us today.

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