Aerospace firms would benefit enormously if their suppliers shared process capability data from their lines. But first, you will have to overcome a supplier’s reluctance to share data from their equipment. The key to doing so is conveying the benefits for both parties, such as an enhanced relationship and being able to identify issues as early in the process as possible, which reduces costs for all parties. Emerging real-time quality data systems are being deployed to improve the exchange of information between suppliers and aerospace quality personnel, especially around inspection reports. This exchange can include process specifications, SPC data, and other information from machines, inspection, maintenance, R&R gage studies, etc. Connected suppliers could eventually provide the foundational data that would lead to predicting maintenance issues via sensors and the Internet of Things – but is this realistic? Software as a Service (SAAS) systems will likely be able to have quality managers connect directly to the supplier and indirectly through a web portal to gain access to quality measurement data, capability data, and employee performance data. An important part of this will be institutionalizing the system of measurement, ensuring that the supplier also knows how to access the system and use it, and methods to proactively measure supplier capabilities and evaluate issues as they arise. This is the opposite of the typical quality assurance process which is reactive. Every non-conforming part would have real-time information on process capability and where it in the system, ideally before it leaves the supplier’s facility. Being able to quickly identify quality problems can go a long way toward reducing the Cost of Poor Quality, or simply, the Cost of Quality. This cost comprises not only the increased inspection costs, but also the cost of rework for products that are discovered to have non-compliance issues within the process. Real-time visibility to quality problems can also help to quickly track down the source of the problem, using data and analytics to drive down to the root cause. Early detection is invaluable because the Cost of Quality quickly escalates once products are shipped. They are then discovered prior to production or even installed onto an aircraft, which can result in massive costs, FAA fines, and other problems. It is far less expensive and better for customers if systems are used to quickly notify everyone in a production network of a possible problem at a node in the supply chain, leading to reduced rework, lower costs, and improved product quality and customer satisfaction. Once it is decided to move forward with real-time data sharing, there are a few items that should be ironed out between the supplier and the customer before getting started.
- Will the data be used as an incentive or linked directly to contract payment terms? Real-time quality data works best when it is shared in the spirit of continuous improvement.
- How will the veracity of the data be determined? Understanding the quality of the data, the measurement error, and other factors will become important to understand.
- Who owns the data and how will it be transmitted? Can the data be referenced if warranty issues arise?
- Who will be assigned to problem solving and ongoing quality assurance efforts? Will it be an engineering issue, a quality issue, or a manufacturing issue? Governance needs to be established on who gets to see and act on the data.
- How will such data be applied in new products? At what level does it go to for approval before a product is released?