Quality and Productivity Improvement Training Course

Participants can define process boundaries and create baseline maps for improvement analysis.

• SIPOC diagrams defining suppliers, inputs, process steps, outputs and customers
• Swimlane maps exposing hand-offs, approvals, delays and accountability gaps
• Process boundaries set from trigger event through customer outcome
• Standard work documented through task sequence, timing and acceptance criteria
• Value-added analysis separating customer value, business value and waste
• Baseline process map validated with frontline staff and process owners

Participants can design a reliable measurement system for quality and productivity improvement.

• Operational definitions preventing inconsistent classification of defects and delays
• Data collection plans specifying sources, owners, frequency and sampling rules
• Leading and lagging indicators for quality, flow, cost and capacity
• First-pass yield calculated from accepted output and total units processed
• Cycle time, lead time and takt time distinguished correctly
• Data stratification by product, customer, shift, location and process step

Participants can identify waste and select Lean actions that improve process flow.

• Lean principles focused on value, flow, pull and perfection
• Eight wastes identified through process observation and work sampling
• Value stream maps showing material, information and decision flow
• Work-in-process inventory analysed as a source of delay and risk
• Pull systems designed using customer demand and replenishment signals
• Kaizen opportunities prioritised by impact, feasibility and implementation effort

Participants can apply workplace organisation and visual controls to improve reliability and productivity.

• 5S audits assessing sort, set, shine, standardise and sustain
• Red-tag methods removing unnecessary tools, stock and workplace clutter
• Visual controls showing status, targets, abnormalities and escalation actions
• Standard operating procedures written with clear steps and quality checks
• Visual work instructions reducing variation in repetitive process tasks
• Daily management boards connecting team actions to performance measures

Participants can quantify the financial effect of poor quality and lost productivity.

• Prevention, appraisal, internal failure and external failure cost categories
• Cost of poor quality calculated from scrap, rework, returns and concessions
• Hidden factory capacity estimated from correction work and repeated processing
• Labour productivity measured against output, hours, quality and demand
• Capacity losses separated into planned, unplanned and performance-related causes
• Improvement benefits expressed through cash, capacity, risk and service measures

Participants can use control charts to distinguish common-cause from special-cause variation.

• Common-cause and special-cause variation interpreted through process behaviour
• Run charts revealing trends, shifts, cycles and unusual process patterns
• Individuals and moving range charts used for continuous data
• P charts monitoring proportion defective across varying sample sizes
• Control limits distinguished from specification limits and target values
• Out-of-control signals investigated using documented escalation procedures

Participants can assess measurement reliability and evaluate whether a process meets specifications.

• Measurement system errors classified as bias, repeatability and reproducibility
• Gage R&R studies assessing operator and instrument measurement variation
• Attribute agreement analysis testing consistency of inspection decisions
• Process capability indices Cp and Cpk calculated against specifications
• Process performance indices Pp and Ppk interpreted for baseline performance
• Specification limits reviewed against customer needs and technical requirements

Participants can identify verified causes and define corrective actions for recurring problems.

• Problem statements written with measurable gap, location, timing and impact
• Pareto charts ranking defect categories, causes and loss values
• Fishbone diagrams structuring possible causes across major cause categories
• 5 Whys analysis tracing observed symptoms to controllable process causes
• Cause-and-effect matrices linking input variables to critical outputs
• Corrective actions verified through evidence, ownership, deadlines and follow-up

Participants can assess process failure risks and prioritise preventive controls.

• Process FMEA structure covering functions, failure modes, effects and causes
• Severity, occurrence and detection ratings applied using defined scoring criteria
• Action priority methods selecting failure modes requiring prompt treatment
• Prevention controls designed to remove or reduce failure causes
• Detection controls positioned before defects reach downstream customers
• Residual risk reviewed after actions, evidence and control ownership

Participants can structure a data-driven improvement project using the DMAIC method.

• DMAIC phases connecting project definition, analysis, improvement and control
• Project charters defining scope, problem, objective, benefits and governance
• Critical-to-quality trees translating customer needs into measurable requirements
• Hypothesis tests used to compare process groups and improvement results
• Scatter plots examining relationships between input variables and outputs
• Pilot plans specifying test conditions, measures, risks and decision criteria

Participants can analyse equipment losses and develop actions to improve asset productivity.

• Overall Equipment Effectiveness calculated from availability, performance and quality
• Six big losses classified from breakdowns, stoppages, speed and defects
• Planned maintenance schedules linked to failure patterns and critical assets
• Autonomous maintenance tasks assigned through operator care standards
• Downtime codes standardised for consistent equipment loss reporting
• OEE improvement actions prioritised using loss magnitude and recurrence

Participants can improve throughput by identifying and managing system constraints.

• Theory of Constraints identifies the system constraint limiting throughput
• Constraint capacity calculated using demand, uptime, yield and available hours
• Drum-buffer-rope scheduling protects constrained resources from starvation
• Queue analysis explains waiting time, utilisation and flow instability
• Bottleneck workload reduced through task transfer, setup reduction and prioritisation
• Capacity decisions tested against demand scenarios and service targets

Participants can apply quality and productivity methods to supplier and service processes.

• Supplier quality measures covering defects, delivery, responsiveness and corrective action
• Incoming quality controls matched to supplier risk and material criticality
• Service blueprinting maps customer actions, frontstage work and support processes
• Error-proofing methods prevent common transaction errors and omissions
• Service-level measures track accuracy, response time, resolution and backlog
• Complaint data converted into process priorities and corrective actions

Participants can sustain improvements through standards, governance, audits and performance review.

• ISO 9001 process approach applied to documented operational controls
• Control plans specify measures, limits, responses, owners and review frequency
• Layered process audits verify adherence to critical operating standards
• Standard work updates controlled after approved process improvements
• Daily tier meetings escalate abnormalities through defined management levels
• Benefits tracking compares realised results with approved improvement targets

Participants can build, review and present a complete quality and productivity improvement project.

• Project charter consolidating problem statement, scope, objectives and stakeholders
• Baseline dashboard presenting quality, productivity, cost, delivery and risk measures
• Current-state process map identifying waste, variation, controls and bottlenecks
• Root-cause evidence supporting verified causes rather than assumed explanations
• Future-state design combining Lean actions, risk controls and performance measures
• Implementation plan sequencing pilots, ownership, resources, milestones and communications
• Control plan defining review cadence, escalation triggers and sustainability checks
• Executive presentation defending benefits, risks, assumptions and recommended decisions