According to a recent study, human errors alone cause an extraordinary 23% of unplanned downtime in manufacturing. Mistake-proofing - also referred to as Poka-Yoke - is a Japanese ideology describing any method used to detect and prevent errors that cause defects.
Common mistakes made
The most common human error in production is the failure to follow instructions for various reasons. Skipping steps, using the wrong tools and wrong parts are examples of why mistake proofing is critical in today’s assembly processes. The rise in consumer demand for highly customized products is the driving force behind this failure rate. Due to the increasing complexity and frequency of new product introductions, first-time quality has become a critical KPI.
Traditionally, manufacturers contained human errors by producing the exact same product on a mass scale. As complexity increased, the effectiveness of the lean and Software Process Control (SPC) based manufacturing models started to decline.
These techniques were augmented by additional mistake proofing techniques, such as printed paper instructions and methods based on rigid hardware sensors, actuators, and other mistake-proofing devices to contain human errors. Smart factories today are focusing on using new Industry 4.0 technologies, such as software-based plant floor error-proofing, to improve first-time quality.
Top 5 mistake-proofing techniques in error proofing software
Below are the top 5 mistake-proofing techniques in a plant floor error-proofing software that will help manufacturers achieve first time quality in a complex and ever-changing environment.
1. Visual instructions based on operator skill and product maturity
Interactive assembly instructions and operator guidance are tied to every work step and provide continuous feedback to the operator, based on their skill level. As an example, managers would have the ability to display smaller step progression for an operator with one week on the line, versus only critical checkpoints for a five-year veteran. The same principle applies to a new product or process on the line compared to an existing, well-known process. The key word here is “interactive”, ensuring operator engagement and mistake-proofing error checks at every critical point in the assembly process. These checks prevent an error from happening or catch the error within a few seconds of its occurrence. This method greatly reduces the amount of overall production downtime.
2. Part verification to avoid rework process in manufacturing
Automatic verification of parts uses barcode, RFID, or vision systems to contain repairs and product recalls. A rising number of model variations and product complexity often cause human errors, such as the installation of wrong lookalike parts.
Electronic control modules (ECU), for example, look alike on the outside with different software inside. Mistake proofing the assembly process by automatically verifying the scanned part against a predefined part number, or real-time verification from the bill of materials can account for substantial savings in rework, repair, and even recall costs.
3. Tool Interlock to protect against recall liabilities
The correct tool and tightening program for a product variant in a station is selected dynamically. Products with screws and fasteners tightened with the incorrect tool or program are highly susceptible to recalls, leaving a manufacturer’s reputation at stake.
Production line mistake-proofing by automating the tool and program selection based on the product in the station can help protect brand reputation and safeguard against recall liabilities.
4. Operator identification and certification check for increased accountability
Controlling an operator’s access and checking their certification level and checking their certification level before allowing them to perform specific assembly tasks is a must for accountability and compliance. Operator engagement in an increasingly dynamic manufacturing environment is one of the key challenges manufacturers face.
Ensuring operator accountability is the first step towards mistake-proofing by driving engagement and ultimately reducing downtime.
5. Data collection to identify trends and optimize production
Recording data at the bolt level is essential in big data analytics, compliance, traceability, part documentation, and other uses. Most manufacturers record data for regulatory compliance purposes, but the real value of data is when it is used for optimization, trending, and predictive purposes in the world of mistake-proofing.
What would it mean for the brand’s reputation if every customer received a birth certificate with the exact build data for the product serial number they’ve purchased, confirming it was built to specification?