Auto-Sector Interview Preparation

Ensures products and processes meet quality standards and continuously improve.

Inspecting and testing products to detect defects.

Building processes to prevent defects and ensure quality.

QA is proactive and process-focused; QC is reactive and product-focused.

A non-conformance to a requirement or specification.

A documented requirement that a product or process must meet.

The permissible variation in a dimension or property.

Examining a product against its requirements.

A failure to meet a specified requirement.

Comparing an instrument to a standard to ensure its accuracy.

Measuring internal and external dimensions and depth accurately.

Precise measurement of small dimensions such as thickness or diameter.

A pass or fail gauge that checks whether a part is within limits.

A graph that monitors process variation over time.

A list used to verify that all required checks have been done.

Finding the underlying cause of a problem rather than just the symptoms.

Asking why repeatedly until the root cause is reached.

A cause-and-effect diagram that groups potential causes.

Failure Mode and Effects Analysis, identifying and prioritising potential failures.

A document listing the process controls used to maintain quality.

Statistical Process Control, using statistics to monitor and control a process.

A data-driven method to reduce defects to about 3.4 per million opportunities.

Define, Measure, Analyze, Improve and Control.

A bar chart that shows the frequency distribution of data.

A chart that ranks causes by frequency, based on the 80/20 rule.

Roughly 80% of problems come from 20% of the causes.

Inspecting a representative sample instead of every unit.

Acceptable Quality Level, the worst tolerable average quality in a sampling plan.

Corrective And Preventive Action.

Rework corrects a defect; scrap is discarded.

The ability to track a product history, location and components.

A systematic check of compliance with standards or procedures.

An international quality management system standard.

The automotive quality management system standard.

Production Part Approval Process, proving a supplier can make parts to requirements.

Advanced Product Quality Planning, a structured product and process development framework.

A study of measurement system repeatability and reproducibility.

Accuracy is closeness to the true value; precision is repeatability and consistency.

Coordinate Measuring Machine, used for precise 3D dimensional measurement.

A top-level document that describes the quality management system.

Cp measures the spread against tolerance; Cpk also accounts for how centred the process is.

Typically 1.33 or higher, which indicates a capable process with low defect risk.

Form a team, define and contain the problem, find the root cause, take corrective action, validate, prevent recurrence and close out.

Common cause is inherent and random; special cause is assignable to a specific source.

Points beyond the limits, trends, runs or non-random patterns indicate a special cause.

Items such as design records, FMEA, control plan, MSA, capability studies, samples and the part submission warrant.

Planning, product design, process design, product and process validation, and feedback and improvement.

Several operators measure several parts multiple times, then the repeatability and reproducibility variation is analysed.

Under about 10% is good; 10 to 30% may be acceptable depending on the application.

List the functions, failure modes, effects, causes and controls, then score severity, occurrence and detection and prioritise.

Risk Priority Number, equal to Severity times Occurrence times Detection.

A control plan defines what to control and how; a work instruction tells the operator how to do the task.

Contain or sort the stock, run a root-cause 8D, implement CAPA and communicate with supporting evidence.

The cost from defects, including scrap, rework, warranty, returns and lost reputation.

Prevention, appraisal, internal failure and external failure costs.

Use a standard such as ANSI/ASQ Z1.4 based on lot size, inspection level and AQL.

Measurement System Analysis, which ensures data is reliable before it is used for decisions.

Run a gauge R&R and check the method, training, gauge condition and standardise the procedure.

Sampling is cheaper and faster but risks acceptance error; 100% catches more but costs more.

Tally defect types by frequency, sort them in descending order and plot bars with a cumulative percentage line.

The defined actions to take when a characteristic goes out of control.

Process FMEA addresses process failures; Design FMEA addresses product or design failures.

Calibrate it and run an MSA covering bias, linearity and gauge R&R.

A checkpoint where parts must meet criteria before they can proceed.

Use lot or serial coding and keep records of material, process and inspection at each stage.

Frequent multi-level checks on key process steps to sustain the standards.

Raise an NCR, contain it, find the root cause, implement CAPA and verify effectiveness.

Corrective action fixes an existing problem; preventive action stops a potential one.

Use Cpk against the single specification limit.

A run chart plots data over time; a control chart adds statistical control limits.

Clarify the requirement, agree the controlling specification and document it through change control.

It verifies that the first produced part meets every drawing requirement before mass production.

Define the problem, measure the baseline, analyse the root causes, improve, then control to sustain the gains.

The maximum defects allowed to accept a lot versus the count that causes rejection.

Through incoming inspection, supplier PPAP, certificates of analysis and supplier audits.

Appoint a champion and team, contain shipped stock with interim action, find the technical and escape root cause, apply a permanent fix, validate it, prevent it systemically and recognise the team.

The spread is fine but the mean is off-target, so adjust the process centre and then re-verify Cpk.

Choose the sample size and acceptance number so the OC curve gives acceptable producer risk at AQL and consumer risk at LTPD.

Run the APQP phases, require the PPAP elements, audit the process, verify capability and approve through the part submission warrant.

Stratify the data, use MSA to rule out gauge error, then study process variation and the conditions present when it occurs.

Define the CTQ, confirm the measurement system, select the chart type, set limits from stable data, train operators and react to signals.

Reduce variation through process improvement, centre the mean, or add sorting or 100% inspection as an interim measure.

Compare the two measurement systems, re-measure jointly, review the specification and disposition the lot using data.

Count the defects per opportunity, scale them to a million to get DPMO, then convert that to a sigma level.

Analyse field data with Pareto, strengthen the DFMEA and PFMEA, improve the controls and feed lessons back to design.

Bias is the offset from true, linearity is bias across the range and stability is drift over time, each assessed against standards.

Use action priority or RPN weighted by severity, tackling high-severity items with weak detection first.

Define the key checks, schedule multi-level audits, track findings, escalate non-compliance and close the loop.

Confirm the root cause was addressed, monitor the data over time and verify there is no recurrence under the original conditions.

Transform the data or use non-normal capability methods such as a Weibull or percentile-based index.

Make the wrong assembly physically impossible or trigger an immediate detection or alarm.

Assess the impact, update the FMEA and control plan, validate the change and require approval or PPAP before release.

Use scatter plots and regression to quantify the relationship and then set control limits on the parameter.

Use dedicated certified sorting before shipment, clear marking and daily reporting until the permanent fix is verified.

Cpk uses within-subgroup short-term variation; Ppk uses overall long-term variation and performance.

Quantify the failure and appraisal costs, model the reduction from prevention and show the net savings or ROI.

Escalate through supplier development, controlled shipping levels, on-site audits or re-sourcing.

Use hypothesis testing such as a t-test or ANOVA to compare before and after at a chosen confidence level.

Capture in-line measurements into a system for live SPC, alarms and traceability dashboards.

Use DFMEA in design, APQP in planning, PFMEA and a control plan in the process, and MSA and SPC in production, with feedback loops throughout.