As per a recent analysis, smart factory investments can increase up to 205% by 2025 compared with 2020 across the “Big-5” cluster (US, China, India, Brazil, and the UK).

At least some of this growth can be attributed to the growing prominence of technologies like computer vision. After all, by leveraging an AI-powered computer vision platform, manufacturers now believe that they can enhance quality and productivity at various production stages, reduce operational costs, and eliminate human errors.

For the purpose of this article, we’ll specifically focus on the influence of computer vision on improving quality across the manufacturing domain.

How Computer Vision Helps in Raising the Quality Bar in Manufacturing Sector?

Computer vision offers manufacturers a competitive edge in quality management. Here’s how:

1. Enhanced Productivity through Automation

The manufacturing industry is catering to the growing demand for high-quality products with precision and consistency. Automation plays a crucial role in achieving this by assigning repetitive tasks of varying difficulty to robots, thus, eliminating human errors. 

Computer vision systems, which combine visual analytics and human oversight, offer opportunities to enhance efficiency and productivity. For example, machine vision inspection systems can identify flawed details for human auditors to verify and ensure top-notch equipment quality. 

2. Cycle Time Control and Optimization

Computer vision systems enable accurate measurement and analysis of production cycle times. Manufacturers can deduce the best practice time for each cycle and reduce target time and meet takt time requirements. This optimization ensures smooth workflow on the conveyor, boosting efficiency and overall productivity.

Besides, implementing computer vision in warehouse management and inventory control streamlines supply chain operations, reducing costs and enhancing customer satisfaction. For example, giant retailers like Amazon and Walmart employ drone systems to monitor warehouse inventories, while AI processes real-time camera streams for efficient empty container identification and restocking optimization.

3. Quality Inspection

Quality inspection using computer vision in manufacturing is realized in several ways. One example is measuring time spent in specific areas, enabling precise tracking and optimization of production processes. The computer vision systems enable step verification, ensuring that each operation step is approved before proceeding to the next stage, reducing the production of faulty items. 

Additionally, computer vision facilitates root cause analysis by providing video records of assembly line operations, allowing thorough examination of defective product manufacturing and pinpointing areas for improvement. 

4. Digital Lean Manufacturing

Deloitte estimates that digital lean transformation can lead to an improvement of $20 million in yearly earnings before interest, taxes, depreciation, and amortization (EBITDA), along with a 15% cost reduction per line per year and an 11% annual improvement in overall equipment effectiveness (OEE).

Computer vision systems are pivotal in boosting productivity, reducing waste, and toning down variability in manufacturing operations, thus, paving the way for digitally lean operations. With a computer vision platform, manufacturers can accurately measure process efficiency, optimize workload across the plant floor, and detect equipment malfunctions early on. 

5. Visual Inspection and Tolerance Monitoring

Tolerance monitoring is the process of ensuring that products meet specified tolerances. This is important for ensuring that products function properly and meet customer requirements. Computer vision can be used to monitor tolerances in real-time, which can help prevent defects and ensure the quality of manufactured products.

This is precisely why automotive manufacturers use computer vision to inspect car parts for defects, such as scratches, dents, and cracks. Computer vision can also be used to monitor tolerances in car parts, such as the dimensions of engine components and the alignment of body panels. This helps ensure that cars meet safety and performance standards and are not assembled with defective parts.

6. Track-and-Trace

Track-and-trace is vital for certain manufacturers, especially in industries like fresh food and medicine, where products must be traced from production to the end consumer. To achieve this, packages are marked with unique identifiers like serial numbers, manufacturing dates, and expiration dates. 

Manufacturers employ a master database to auto-generate these codes and later print them onto containers during the production process. Subsequently, high-tech cameras in the computer vision system read the printed numbers or alphabets, recognizing them with optical code recognition. The system then cross-references the information with the master database to validate the printed labels. Any packages with unclear or mismatched codes are promptly rejected, ensuring accurate track-and-trace throughout the production and distribution process.

How KamerAI Helps Ensure Superior Manufacturing Quality

For any manufacturing organization, sustaining higher quality, amplifying productivity, ushering in flexibility in the production process, reducing machine downtime, lowering the setup cost, realizing reductions in scrap rate, and improving inventory control, are strategic goals. 

KamerAI is a real-time computer vision automation platform that can help modern manufacturing establishments raise the quality bar. More profoundly, it can be used for the following tasks:

• Automate inspection tasks: KamerAI can be used to automate the inspection of parts and products, which can aid in improving accuracy and reducing the risk of human error.
• Identify defects early: KamerAI can identify defects early in the manufacturing process, which can help prevent them from being passed on to the customer. 
• Improve efficiency: KamerAI can help improve efficiency by helping automate factory floor tasks and providing real-time feedback on the manufacturing process.
• Reduce costs: The platform can reduce overall costs, especially those related to machine downtime and post-mortem analysis.

If you are a manufacturing company looking to raise the quality bar, KamerAI is a powerful and versatile option. Schedule a demo today to learn more about how it can help.