Manufacturing Quality Control Training Course

Participants can map a process and identify the characteristics requiring control.

• SIPOC mapping to define suppliers, inputs, process steps and customers
• Swimlane process maps showing responsibility, handoffs and inspection decisions
• Critical-to-quality characteristics derived from customer and engineering requirements
• Operational definitions that make defect classification consistent between inspectors
• Process control points selected from risk, capability and detection needs
• Specification limits, target values and tolerances distinguished from control limits

Participants can assess whether measurement data are suitable for quality control decisions.

• Measurement system variation and its effect on manufacturing decisions
• Accuracy, precision, bias, linearity and stability defined with examples
• Calibration intervals based on risk, usage history and measurement criticality
• Traceability of calibration standards to recognised national measurement standards
• Gage repeatability and reproducibility study design using crossed trials
• Attribute agreement analysis for visual inspection and defect classification

Participants can create data collection systems that support timely production decisions.

• Operational definitions applied before collecting defect and process data
• Check sheets designed for defects, locations, shifts and machine conditions
• Stratification by product, operator, material batch and production line
• First-pass yield, rolled throughput yield and defect rate calculations
• Defects per unit and defects per million opportunities compared
• Data integrity checks for missing values, transcription errors and duplicates

Participants can distinguish routine variation from signals requiring investigation.

• Common-cause and special-cause variation using Shewhart's statistical model
• Rational subgrouping based on process sequence and variation sources
• Control-chart centre lines, limits and sampling frequency explained
• Specification limits compared with statistically derived control limits
• Run rules used to identify non-random process behaviour
• Reaction plans triggered by signals, trends and control-limit breaches

Participants can select, construct and interpret control charts for measured characteristics.

• X-bar and R charts for subgrouped continuous measurement data
• X-bar and S charts selected for larger subgroup sizes
• Individuals and moving range charts for low-volume production
• Subgroup averages and ranges calculated from sample measurements
• Out-of-control patterns interpreted using Western Electric supplementary rules
• Control-chart actions documented before adjusting a stable process

Participants can monitor defect counts and defective units using appropriate attribute charts.

• p charts for varying sample sizes and defective proportions
• np charts for fixed sample sizes and defective counts
• c charts for defects counted on constant inspection units
• u charts for defects per unit with varying opportunities
• Inspection consistency checked before interpreting attribute chart signals
• Attribute-chart response rules linked to containment and investigation actions

Participants can evaluate whether a stable process can meet specification requirements.

• Normal distribution assumptions checked using histograms and probability plots
• Cp and Cpk calculated against bilateral specification limits
• Pp and Ppk interpreted for overall process performance
• Process centring assessed against target values and tolerance ranges
• Capability analysis limited when processes remain statistically unstable
• Non-normal capability methods selected for skewed manufacturing data

Participants can use basic quality tools to focus improvement effort on material losses.

• Pareto charts rank defect categories by frequency, cost or risk
• Histograms reveal distribution shape, spread and possible mixture patterns
• Scatter diagrams test relationships between process variables and quality results
• Run charts show shifts, trends and cycles over time
• Stratified data separates machine, shift, material and operator effects
• Prioritisation matrices compare defect impact, urgency and improvement feasibility

Participants can investigate defects systematically and verify effective corrective actions.

• Problem statements define defect, location, timing, extent and requirement
• 5 Whys analysis traces causal chains beyond immediate operator error
• Fishbone diagrams organise potential causes using six manufacturing categories
• Is-Is Not analysis narrows investigation boundaries using contrasting evidence
• Containment actions protect customers while root-cause investigation continues
• Corrective-action effectiveness verified through data, audits and recurrence checks

Participants can translate process risks into preventive controls and documented response actions.

• Process FMEA structure connects process steps, functions and failure modes
• Severity, occurrence and detection ratings assigned using agreed criteria
• Action priority used to focus treatment of significant process risks
• Prevention controls distinguished from detection controls within process FMEA
• Control plans specify characteristics, methods, frequencies and responsibilities
• Reaction plans define containment, disposition and restart approval requirements

Participants can design inspection plans that balance quality risk, cost and production flow.

• Incoming, in-process and final inspection purposes compared across production stages
• 100 percent inspection limitations, costs and human-error risks assessed
• Lot formation and sampling units defined before acceptance decisions
• Acceptable quality level and limiting quality risk concepts explained
• ANSI/ASQ Z1.4 sampling plans selected for attribute inspection
• Sampling-plan records capture lot identity, results and disposition decisions

Participants can contain, document and dispose of nonconforming material without losing traceability.

• Nonconforming product identified, segregated and protected from unintended use
• Material review board decisions documented for disposition and approval
• Rework, repair, scrap and use-as-is dispositions distinguished clearly
• Concession requests controlled against customer and engineering authority requirements
• Traceability records link defects to lots, batches and serial numbers
• Containment boundaries defined for suspect inventory, work-in-process and shipments

Participants can plan focused audits that test whether production controls are followed and effective.

• Audit criteria drawn from procedures, control plans and work instructions
• Process-based audit trails follow product flow and control evidence
• Layered process audits verify recurring compliance by management levels
• Objective evidence distinguished from opinion, assumptions and verbal assurances
• Audit findings classified by risk, requirement and process impact
• Corrective-action follow-up confirms completion and sustained control performance

Participants can connect quality losses with throughput, equipment performance and improvement priorities.

• Overall equipment effectiveness separates availability, performance and quality losses
• First-pass yield linked to capacity, labour use and delivery performance
• Scrap and rework costs quantified using material, labour and overhead
• Poka-yoke methods prevent errors before defective output occurs
• Standard work defines repeatable methods for quality-critical operations
• Visual management makes quality status and abnormalities immediately visible

Participants can establish supplier controls for incoming quality and corrective-action follow-up.

• Supplier qualification criteria cover capability, controls, certification and performance history
• Incoming inspection adjusted using supplier risk and demonstrated quality performance
• Supplier scorecards track defect rates, delivery and corrective-action closure
• Supplier corrective-action requests state evidence, containment and response expectations
• Source inspection used for high-risk or newly introduced components
• Supplier process audits examine controls behind recurring incoming defects

Participants can maintain controlled quality records through process and product changes.

• Document control manages approval, revision, distribution and obsolete copies
• Batch records capture materials, equipment, operators and inspection results
• Serialisation and lot traceability support targeted containment and recall
• Change control assesses quality risks before process modifications
• Control plans updated after engineering changes, incidents and capability shifts
• Record retention periods aligned with customer, regulatory and business requirements

Participants can report quality performance using measures that support management decisions.

• Prevention, appraisal, internal failure and external failure costs classified
• Cost-of-poor-quality calculations connect defects with financial consequences
• Quality dashboards combine leading controls with lagging customer results
• Daily management boards display critical measures, owners and action status
• Escalation thresholds set for yield, scrap, complaints and audit findings
• Management review inputs link quality trends to resource and improvement decisions

Participants can plan implementation of improved controls with ownership, timing and verification.

• Control-improvement priorities selected using risk, loss and implementation effort
• RACI matrices assign ownership for controls, escalation and verification
• Pilot plans test revised inspection methods before full deployment
• Training matrices identify competence requirements for quality-critical tasks
• Implementation milestones track document updates, trials and approval gates
• Sustainment reviews confirm control adherence, capability and defect reduction

Participants can build, review and present a complete quality control plan for a selected manufacturing process.

• Process map identifies requirements, risks, control points and handoffs
• Critical characteristics linked to measurement methods and acceptance criteria
• Measurement-system evidence supports selected inspection and monitoring methods
• Control-chart and capability analyses inform process monitoring decisions
• FMEA, control plan and reaction plan aligned across process steps
• Presentation defends implementation priorities, responsibilities and verification measures