Visual inspection

Visual inspection was the first method used for predictive maintenance.Until the Industrial Revolution there was not really any methods used for identifying potential risks or failures, which later evolved to a broad subject of a ‘predictive maintenance’. The first one, that was introduced, was visual inspection and it consisted of a maintenance technicians regular routine. This basically involved daily "walkdowns" around manufacturing systems and it served its purpose to find problems that could affect the product quality or production costs. Even though visual inspection is not a very modern way of monitoring around the workplace, it is still used and should be included in the maintenance management programs.

Categories of visual inspection

Almost all the goods produced in the industry are visually inspected with some intensity. Previously, this was the duty of a highly trained personnel or regular employees, especially designated for the task, however since 1970s, they have been slowly replaced by the automated visual inspection systems. Those have escalated to be more and more popular as well as efficient in the industry and other sectors, and have been rapidly growing since. To visually inspect is simply to inspect with the use of sight. It should play at least two roles - firstly in ensuring the quality factors of final or semi-final products, secondly it should provide detection and analyzation of the variations in the production process. Depending on different approaches, visual inspection can be divided into categories as follows:

1. Product completion: knowledge to recognize the objects, patterns:
   1. assembly site: are there all the components present?
   2. during the charging: is there any space left in the package?
   3. assembly of circuit boards: are all the components placed in position?
2. Accuracy of both positions and orientation:
   1. assembly site: is the place and orientation correct for all the components?
3. Constancy of all the factors: shapes, angles, dimensions of the components and tools
   1. are all the measurements determined?
   2. are all the essential specifications and an error margins agreements fulfilled?
4. Condition of the surfaces, textures
   1. is the surface condition as modeled
   2. is the surface indiscrete and is it within the specific tolerance limits?
5. Additional factors
   1. color
   2. surface reflection behavior
6. Identification of materials
   1. automated sorting of different synthetic materials
   2. detacting and removing impurities from bulk goods streams
7. Defects: Both aesthetic and technical defects:
   1. detection of varnish runs on varnished Surface
   2. detection of scrotchrs on optical components

Even though the visual system of a live person is more effective than the competitive performance of a machine, it still can be flawed with some impactful drawbacks. Some factors which can describe manual visual inspection from the negative perspective are:

• monotony
• subjectivity
• cost
• lack of good reproductability
• slowness
• high cost of keeping a detailed documentation
• physical labor

Classification of visual inspection techniques

Visual inspection can be used most efficiently in a rapid, noncontact survey around specific sections of the workplace and presents the most accurate extent of visual damage when followed by a sophisticated methods. It is very important and simple at the same time to identify gross defects, discoloration and external corrosion. Its efficiency can be enhanced by the use of some, specifically fit for the role, tools such as a magnifying glass, light source and a borescope. It is possible to classify visual inspections techniques in two categories. The first one is about the comparison of the actual images of a brand-new, defect-free patterns and the actual, given ones. The latter is relating to theoretical decisions, which were made when verifying a set of characteristics of a given product and those of an ideal one.The mentioned categories are :

• Comparison with a pattern

The first technique mentioned is all about a very detailed comparison between the two images. One of them being the inspected product and the other one the ideal one. It is also essential to possess the visual model of the second one in order to conduct the study. When the multilevel images are taken into account, it is important to carefully develop the patterns in order to assure the detection of every small defects and that they are not connected with the inseparable variability of the visual factors of the product nor with the measuring operations.

• Theoretic inspection

These types of methods evolve around the adequate factors of the ideal product. This set of factors consists of a many image characteristics. Among those are areas, shapes, moments, textures, histograms, perimeters. It is vital to come up with a classifier in order to decide on the range of defect and general quality of the inspected product.

Examples of Visual inspection

• Observing the physical condition of equipment: This involves checking for signs of wear and tear, such as cracks, loose parts, corrosion, or any other visible damage. This is done to identify potential problems that could lead to a breakdown or malfunction, and to take corrective action before it becomes a bigger issue.
• Checking fluid levels: This involves making sure that all fluid levels, such as oil, coolant, and hydraulic fluid, are at their proper levels. This helps to ensure that the equipment is adequately lubricated and that it is running efficiently.
• Examining moving parts: This involves checking the moving parts of the equipment to make sure they are free of obstructions and that they are not making abnormal noises. This helps to identify potential problems that could lead to a breakdown.
• Evaluating electrical components: This involves checking the wiring and other electrical components to make sure they are in good condition and that they are not causing any electrical issues.

Advantages of Visual inspection

One of the most common methods for predictive maintenance is visual inspection, which involves regular routine inspections to identify potential risks or failures. Visual inspection has a number of advantages, including:

• Cost effectiveness - Visual inspection requires minimal investment and labour costs, making it a cost-efficient option for predictive maintenance.
• Flexibility - Inspectors can quickly adjust their inspection process to different types of equipment and situations, making it a versatile option.
• Early detection - Visual inspection allows inspectors to detect problems early on, which can help minimize the risk of further damage or loss.
• Minimized downtime - Regular visual inspections can help reduce downtime, as problems can be caught and addressed quickly.
• Improved safety - Regular inspections can help identify potential safety hazards and ensure that equipment is operating safely.

Limitations of Visual inspection

One of the main limitations of visual inspection is its inability to detect potential risks or failures until they are actually present. Below are some of the other limitations of visual inspection:

• It is not able to detect any problems that may be hidden or invisible to the naked eye.
• It is an expensive method, as it requires manual inspection.
• It is not very accurate, as it relies on the judgement of the technician, which is subjective.
• It is not very reliable, as the technician may overlook potential problems.
• It is not very efficient, as it is time-consuming.
• It is not very scalable, as it can only be used for limited number of assets.

Other approaches related to Visual inspection

• Introduction: In addition to visual inspection, there are several other approaches that can be used for predictive maintenance:
• Vibration Analysis: Vibration analysis is a method of monitoring the motion and mechanical health of rotating machines. The process involves measuring the vibration data of the machine, which is then analyzed and compared with a baseline to detect any changes in performance. This method can be used to detect potential problems before they result in actual failures.
• Thermography: Thermography is a common predictive maintenance technique that uses infrared cameras to detect temperature changes in various components of a machine. This method can detect potential problems such as electrical overloads or bearing failures before they result in breakdowns.
• Oil Analysis: Oil analysis is a method of measuring the health of a machine by analyzing the lubrication oil used in its operation. This technique can be used to detect potential problems such as wear and tear, contamination, or improper lubrication.
• Wear Debris Analysis: Wear debris analysis is a predictive maintenance technique that involves measuring the particles present in a machine's lubrication oil in order to detect potential problems such as excessive wear or contamination.
• Ultrasound Analysis: Ultrasound analysis is a method of using sound waves to detect potential problems in a machine. This technique can be used to detect problems such as bearing misalignment, air leaks, and other mechanical issues.

In summary, there are several approaches that can be used for predictive maintenance, including visual inspection, vibration analysis, thermography, oil analysis, wear debris analysis, and ultrasound analysis. All of these methods are used to detect potential problems before they result in actual failures, helping to maintain a machine's efficiency and reliability.

Footnotes

Visual inspection — recommended articles

Quality inspection — Failure Mode and Effects Analysis — Quality control — Maintenance strategy — Fault tree — HACCP system — Perfect system — Ergonomic system — Line balancing

References

• Beyerer J. Puente F.L. Frese Ch.(2015)., Machine Vision: Automated Visual Inspection: Theory, Practice and Applications, Springer
• Brown R. (1999)., Handbook of Polymer Testing: Physical Methods, CRC Press
• Denket M.A. (2006)., Frontiers in Robotics Research, Nova Publishers
• Mobley K.R. (2002)., An Introduction to Predictive Maintenance, Elsevier
• Straub J. Weidemann D. Kolbl C. Zielke B. (2015)., Pursuit of Meaning: Advances in Cultural and Cross-Cultural Psychology, Transcript Verlag

Author: Katarzyna Maziarka