Alfred H Knight Group Quality Apprentice

Alfred H Knight has an exciting opportunity for a Group Quality Apprentice to join our team in Liverpool, UK. You will support the continuous improvement and delivery of the AHK Quality approach in Group Laboratory operations focused on metals and minerals analysis.

What you'll do at work:

• Lead or support non-conformance (NC) investigations and root cause analysis.
• Assist with Corrective and Preventive Action (CAPA) planning, verification, and effectiveness checks.
• Maintain accurate NC and CAPA records and ensure timely progression of actions.
• Investigate Quality Control (QC) failures, trends, and anomalies.
• Conduct data integrity checks and support compliance monitoring.
• Support internal audits and audit readiness activities.
• Prepare evidence and documentation for external assessments.
• Conduct compliance reviews and contribute to corrective actions.
• Support CI projects aligned to UK Quality priorities.
• Assist with process optimisation and risk reduction activities.

Where you'll work:

Alfred H Knight Group Headquarters (UK)
Kings Business Park
Kings Drive
Prescot
L34 1PJ

Training details:

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider:
CAPELLA ASSOCIATES LTD

Training course:
Improvement specialist (level 5)

What you'll learn:

Course contents:

• Leading improvement teams: Holding team members/stakeholders to account for delivering agreed actions within an improvement project and building/maintaining appropriate stakeholder relationships inside and outside the organisation to deliver improvement project objectives
• Strategic Deployment of Continuous Improvement: Contribute to deployment of improvement strategy, participating as an active member of the improvement community
• Communication: Prepare and present concise proposals and plans. Capture and share progress through effective formats and channels. Use and handle questions effectively. Build rapport with others.
• Capability Development: Train, facilitate and critique the application of tools used by improvement practitioners including tool-selection, links between tools, how they are used within a structured method, analysis of results and presentation of recommendations
• Project planning: Plan and manage finances, multi-stakeholder delivery and benefits realisation
• Change planning: Design reinforcement, engagement and communication strategies
• Principles and Methods for Improvement: Guide others on the selection of appropriate methods (e.g., Practical Problem Solving, Define-Measure-Analyse-Improve-Control, 8-Disciplines, Identify-Define-Optimise-Verify) to deliver improvements. Conduct gateway assessments to ensure suitability of projects to progress
• Project selection & scope: Guides others on the selection and scoping of improvement projects and the initial response to product/process performance issues. Identify, scope and prioritise improvement opportunities that map to high-level organisation objectives and key value-streams
• Process mapping & analysis: Guide others on the selection of appropriate process mapping and analysis tools. Critique improved state
• Lean tools: Identify and analyse value-streams using appropriate methods and tools to optimise flow to customer. Develop a plan for Lean deployment within the organisation including effective and relevant performance metrics
• Measurement: Guide others on the planning, analysis and interpretation of data collection & measurement studies including the design of tests to recreate failures & steps to diagnose/reduce short & long-term measurement variation
• Statistics & measures: Confirm data and fit for a range distribution models. Establish predictions. Calculate confidence intervals
• Data analysis-statistical methods: Model random behaviour and make inferences with levels of confidence. Calculate/recommend sample size. Test hypotheses for all data types. Assess input/output correlation. Generate, analyse and interpret simple and multiple predictive relationship models
• Process capability & performance: Identify data stability/distribution issues and apply appropriate strategies to enable robust Capability Analysis. Analyse life data to establish rates and patterns
• Root cause analysis: Make appropriate use of data to assess contribution of critical inputs/root cause(s) to product/process performance using appropriate graphical and statistical tools to draw and communicate conclusions
• Experimentation & optimisation: Guide others on the planning, analysis and interpretation of experiments. Plan, conduct, analyse and optimise both full & fractional experiments
• Data analysis – Statistical Process Control: Monitor and assess ongoing process variation and changes through chart-selection, control-limit setting, sample sizing/frequency and control-rules
• Benchmarking: Guide others on benchmarking to support all stages of improvement projects including future-state design
• Failure mode avoidance: Decompose complex systems in order to define main functions. Analyse system interactions. Cascade knowledge through fault tree analysis. Create and assess design rules, standards & verification methods. Complete robustness studies to select appropriate control strategies and detection methods
• Sustainability & control: Guide others on control and sustainability planning including methods and tools to maintain benefits, extraction of learning, replication, sharing and consolidation of new knowledge into organisational learning