Professionals within manufacturing, construction, projects, and asset integrity management in general, as well as practicing personnel from mechanical, process, structural, chemical, etc., engineering disciplines will be benefited with acquiring knowledge for continuous improvement (CI) in the digital age.
The course is focused to minimize variability in assessment and control processes which is the most central human activity, intrinsic in our biology and done both consciously and unconsciously in an ad hoc manner causing suboptimal decision prioritizations. Use of artificial intelligence (AI) for minimizing variability in risk-based asset integrity assessment and control will be explained with practical cases.
The use of analytic hierarchy process (AHP) will be explained, for assessing and documenting the priorities assessment and control process in various offshore/onshore applications. Setting priorities based on own industrial problems from the participants will be discussed with special emphasis on developing decision hierarchy and making pairwise comparisons by considering their benefits, costs, risks, and opportunities, and the resources need.
In summary, this course focuses on continuous improvement (CI) via performance measurement (‘You can't manage what you don't measure ‘) to increase profit margins via reducing operational costs [i.e. by minimizing ‘waste’ in physical (e.g. at plant level or field operations) and knowledge work (e.g. at assessments and recommendations carried out in the office work)].
Course Agenda (Day 1 – 5)
The lectures will be on Zoom following dates:
From 09.00 to 15.00
Introduction to performance measurement continuous improvement (CI) in the digital age
- Digital age strategy management: from planning to dynamic decision making
- Asset Integrity Management (AIM) vs. human factor challenges.
- Variability in assessment and control activities
- Asset Performance Management (APM) vs. Asset integrity management (AIM)
- Need for organizational alignment and role of barriers
- Agile and Adaptive Strategy Execution Model
- CI methods, Decision Analysis for Optimization at design, construction, operation, inspection, maintenance and modification Activities
- Case Studies and group Exercises
Strategic innovation/disruptive innovation: importance of agility
- Industrial cases of strategy failures from Petroleum Industry
- Industrial failures due to Taylorism and/or 100% Dependence on Standards.
- AIM for Balanced Performance
- Improvement of project performance via alignment
- Asset Owner/Engineering Contractor
- Digital age strategy management in engineering applications
- How to formulate strategies for the digital age?
- Balanced Score Card strategy execution system: ‘strategy maps’ for technical organizations
- Development of ‘dashboards’: KPI and KP management in industrial organizations
- Asset Management Standards for CI: PAS55 1&2 to ISO55000
- Classroom activities
Decision prioritization in industrial applications: multiple criteria decision analysis with a software support
- Nature of real-life challenges/problems
- Need of decision analysis in daily engineering/technical/ industrial applications
- How, and why, bad decisions are made: cases from previous industrial failures
- Guidelines for good decision analysis: cases from previous industrial successes
- Need of decision prioritization in industrial applications;
- AHP approach and decision structure developments
- AHP approach, related mathematical foundation and digital AHP analysis
- Decision sensitivity analysis
- Case studies and group exercises:
- Project contractor selection decision prioritization
Industrial projects’ management and strategy execution (SE) in the digital age
- Traditional projects’ management techniques: Gantt chart, Critical path and PERT methods
- Project crashing and cost analysis
- Why the engineering (construction, mechanical, etc.) and/or industrial projects fail?
- How to deal with overbudget, delay and satisfying business intent?
- Use of Last Planner® System in engineering/construction projects’ management.
- Potential use of Last Planner® System in knowledge work, office work in a technical organization, and other engineering projects.
- Necessity for using ‘lean philosophies’ for enhancing industrial projects’ performance.
- Role of digital age project management and Building Information Modelling (BIM)
- Project Management (PM) & Strategy Execution (SE) in the digital age:
- Use of BIM Concept and Immersive Learning approaches (AR, VR, MR and XR)
- Case Studies and Group Exercises
Performance measurement using lean tools for continuous improvement (CI)
- Process mapping methodology for CI in the industrial applications: physical work and knowledge work.
- Value stream mapping’ for CI in the industrial applications: physical work and knowledge work (case study from valves requisition process).
- Use of lean tools for CI in the manufacturing/construction and petroleum industry activities.
- Classroom case studies:
- Mapping an industrial process and carry out process analysis
- Mapping a value stream and carry out value stream analysis
- Use of VSM approach to improve valve requisition process.
- Prioritization of product features in the product development.
Who Should Attend?
This training course is suitable to a wide range of technical and administration/management professionals within mechanical, process, structural, electrical and chemical engineering/technical disciplines. Also, those who want to gain further knowledge within:
- Manufacturing and construction engineering disciplines.
- Operation, inspection, maintenance, repair and modification professionals in mechanical, process, structural and chemical engineering disciplines.
- Key operations’ supervisors/leaders in mechanical, process, structural, electrical, computer, and chemical engineering disciplines.
- CI consultants in mechanical, manufacturing, construction, process, structural, electrical and chemical engineering disciplines.
The course is held by Professor R. M. Chandima Ratnayake.
Read more about him here.