  This paper provides a structured and practical roadmap for practitioners to
integrate Learning from Demonstration (LfD ) into manufacturing tasks, with a
specific focus on industrial manipulators. Motivated by the paradigm shift from
mass production to mass customization, it is crucial to have an easy-to-follow
roadmap for practitioners with moderate expertise, to transform existing
robotic processes to customizable LfD-based solutions. To realize this
transformation, we devise the key questions of "What to Demonstrate", "How to
Demonstrate", "How to Learn", and "How to Refine". To follow through these
questions, our comprehensive guide offers a questionnaire-style approach,
highlighting key steps from problem definition to solution refinement. The
paper equips both researchers and industry professionals with actionable
insights to deploy LfD-based solutions effectively. By tailoring the refinement
criteria to manufacturing settings, the paper addresses related challenges and
strategies for enhancing LfD performance in manufacturing contexts.
