This lesson covers the course structure and a ‘root cause.’ The definition of a ‘root cause’ is unnecessarily complicated in textbooks and standards. A ‘root cause’ is limited to things you can control. This is both limiting and empowering, as problems are fixed only when you believe the things you can try are achievable. Students are introduced to how ‘root cause analysis (RCA)’ for hardware, software, and manufacturing engineers needs to cover each other's disciplines as each is intertwined with the others.

Students will be motivated by this lesson as the benefits of RCA are discussed at the organizational and individual levels. Thorough RCA not only finds solutions to problems but also a range of cost-effective, fast, and ‘easy’ solutions from which you can choose to implement in ways that suit you and your business plan.

‘Causal chains’ refer to the many different chains of events triggered by potential root causes, each resulting in a plausible scenario for the ‘undesirable event’ your RCA focuses on. Ensuring that as many ‘causal chains’ are identified in RCA allows a much larger range of potential ‘corrective actions (CAs)’ to be introduced, meaning the cheapest, fastest, and easiest ones can be selected.

The ‘5 whys’ and ‘Ishikawa diagrams’ are both RCA tools that help structure the brainstorming process and allow potential root causes to be identified. Students will learn the fundamental differences between the two well-known approaches. ‘5 whys’ is based on ‘observational reasoning’ where the answers to questions of inquiry can be confirmed through inspection. The ‘Ishikawa diagram’ is based on ‘deductive reasoning’ as it allows brainstorming to capture the range of possible ways an undesirable event occurred if we can’t confirm what happened through observation.

‘Fault trees’ are another visualization methodology based on ‘deductive reasoning.’ Students will learn in this lesson how to embark on constrained brainstorming, focusing on identifying the problem that needs to be solved.

‘Immediate actions’ are implemented to minimize the harm of an ‘undesirable event’ but not correct the issue that caused it. They are essential and are usually based on some form of understanding of what went wrong. Students will learn about immediate actions and work through a Space Shuttle RCA example.

‘Pareto analysis’ is a key tool to help us focus on the ‘vital few’ reasons things fail. There are typically only a small number of issues that cause the majority of problems, and they need to be addressed to the exclusion of all else. Students will learn to look for dominant ‘reasons’ for ‘undesirable events,’ focusing on how hardware fails.

‘Failure modes’ are the consequences of hardware ‘failure mechanisms.’ A ‘functional failure mode’ describes what a product or system is not (or is) doing due to failure (such as leaking, not calibrating, and not reaching top speed). A ‘physical failure mode’ describes the state of the product or system (such as bent contact, fractured strut, or discoloredpad). Students are taught what these different failure modes mean and how they can be used to find potential root causes of failure.

RCA needs to identify ‘why’ some undesirable event happened. If that undesirable event involved the failure of a hardware component, system, or product, we need to determine ‘how’ the failure occurred. This means identifying the failure mechanism (the physical, chemical, electrical, or other phenomenon) triggered by a fault (the circumstance that starts a physical failure process like a defect or wrong material being used). Students learn how ‘failure analysis’ can identify ‘how’ something failed as part of RCA.

Hardware failure processes are random. But just because something is random doesn’t mean it is unpredictable or has no ‘signature.’ This lesson starts with a worked example of an investigation into the failure of specific keys on a smart lock keypad. It then teaches students how to look for ‘statistical signatures’ in the failure data of components to see if it is wearing out too quickly, wearing in (likely caused by manufacturing defects), or something else.

Software fails differently from hardware and has its own type of failure mode. Virtually every product or manufacturing process relies heavily on software, so software needs to be included in most RCA. Students (especially those without a background in software) will be taught how to conduct RCA of software either by itself or as part of a more extensive system.

Less than 30 % of software defects are simple coding errors. These simple coding errors are typically easy to identify and fix. The remaining 70 % come from what are called ‘entry points,’ which can be incomplete ‘software specifications’ or steps skipped in the overall software design. This lesson will focus on software defects and how they got there to help RCA.

There will always be a need for ‘simple software debugging’ where defects are resolved ad hoc based on customer or user feedback. However, the root causes of ‘big’ software failures, or repeated software failures, are key procedural (or cultural) issues in the organization responsible for the software. This lesson will focus on the root causes of these software problems and how to address them.

‘Quality’ is a term that can be used to describe manufacturing processes and how well they can produce defect-free parts and components. Manufacturing processes are constantly ‘changing’ as cutting tools blunt, manufacturing machines age, and raw materials change. Students will learn how ‘statistical process control (SPC)’ can look for telltale ‘statistical signatures.’ SPC can be used as a ‘corrective action (CA)’ to address manufacturing issues and trigger RCA to pre-empt manufacturing process failure before defective parts are created.

‘Correlation’ is a statistical relationship between two variables. This can be useful for finding links between temperature and manufacturing settings on part characteristics. This helps find the root causes of manufacturing problems. Students will learn about correlation and its application to the RCA of smart lock keypad stroke defects.

Some manufacturing behaviours are challenging to understand, especially when they are based on things like atmospheric humidity, abrasive material, and lots of factors we don’t initially anticipate influencing our process. ‘Design of experiments (DOE)’ is a useful way of efficiently comparing different scenarios with different characteristics to understand what influences process performance. Students will learn how to use DOE and previously taught tools to inform meaningful, impactful ‘corrective actions (CAs)’

The ‘8D process’ is a robust baseline strategy for RCA. Students will go through a template 8D worksheet that can be tailored and adapted for most RCA scenarios. Students will then use the 8D process as part of a worked exercise where all the skills and approaches taught in the course will be practiced.

Students will review the course where the importance and value of doing RCA well is reinforced. Other activities that focus on preventing problems are also discussed at a high level and how that related to RCA.