By Ashley Belliveau
We’ve all read headlines about product recalls in highly-regulated industries, such as automotive, food processing, medical, and pharmaceutical. You can imagine how financially devastating it would be to discover that a product you’ve been manufacturing for years is subject to a recall for a quality defect.
Should this occur, you’ll need to recall as quickly as possible. In order to do so, you’ll first need to gain visibility into the assembly of that particular group of goods. This is where a reliable, automated lot traceability system can not only provide the insight you need but can also help prevent a recall in the first place.
Lot traceability is the act of tracking and documenting a “lot,” batch, or group of goods that were made during the same manufacturing run using the same raw materials, components, and parts. Increasingly, we’re seeing manufacturers invest in machine vision systems to keep better track of parts as they move through the assembly line. Doing so can yield many benefits that can streamline processes, enhance product quality, and ultimately improve your bottom line.
Integrating Machine Vision in Your Lot Tracking System
When manufacturing complex products that consist of many different parts, it is important to be able to keep track of all components as they move through the assembly process. To accomplish this, identification codes (think: barcodes, lot numbers, RFID tags, etc.) should be assigned to each part where feasible to enable individual parts and components to be tracked.
A machine vision system can then verify the code markings once they are on a part and transmit that data directly to an ERP, inventory, or business management software system where it is stored. In addition to machine vision systems, robotics can also be integrated into the process to pick up, maneuver, and/or place the part as it is being verified.
Taken a step further, machine vision systems can not only trace where a part is located within the manufacturing process but can also ensure that the right part or component is used in the assembly. If parts do not pass the inspection test (for example, if the part was not the correct part number for the sequence and/or the part was damaged), the inspection robot will reject the “failed part” before it can progress any further within the operation.
The Benefits of Automated Lot Traceability
It is undoubtedly important for manufacturers to be able to keep track of parts as they move through the assembly process. Compared to manual methods, which are time-consuming and run a greater risk of human error, automating lot traceability can provide the visibility manufacturers need to ensure quality products.
Some of the many benefits of an automated lot tracking system include but are not limited to:
- Tighter inventory control: Automated lot traceability enables you to track which materials are being used and in which products easily. For instance, you can better track product expiration dates to ensure that nothing goes to waste.
- Greater visibility for root cause analysis: Vision systems can allow you to incrementally track progress on an assembly line to quickly identify the root cause of any problem.
- Increased customer satisfaction: In today’s competitive marketplace, your customers will always expect the best products. Greater visibility throughout the assembly of a product can ensure that it passes the test before it ships.
- Enhanced bottom line: By reducing waste with stronger inventory control and fewer recalls, you can ultimately improve your bottom line with automated lot traceability.
Experts in Robotic Vision Systems for Lot Traceability
The experts at Steven Douglas Corp. (SDC) understand that your company’s reputation and future success depend on consistent quality control and lot traceability. As an experienced integrator of robotic vision inspection systems, we can design and build a custom, automated lot traceability system to track parts and components throughout your manufacturing process. Contact SDC today to discuss your upcoming assembly project. In the meantime, check out some of our past projects.