16th - 17th November 2023
Agenda
DAY 1 - 16th NOVEMBER
08:00 – 08:40
REGISTRATION
08:55 – 09:00
CHAIRPERSON’S OPENING REMARKS
09:00 - 09:30
HERE’S THE SOLUTION! WHAT’S THE PROBLEM?
- Technological advancements from IOT, Wearables, Machine Learning, and Artificial Intelligence bring exciting new opportunities
- Before investing in these technological advancements, the maintenance problem being solved must be clarified
- The technological choices need matching with the maintenance problem, with clear and measurable benefits
- A digital maintenance strategy requires careful choices – don’t do everything, just because you can
09:30 - 10:00
THE LINK BETWEEN WORLD CLASS ASSET MANAGEMENT AND SUSTAINABILITY, INCREASING ASSET LIFE CYCLES TO IMPROVE SUSTAINABILITY USING CURRENT ASSET MANAGEMENT FRAMEWORKS
- Tracking component life cycles to determine the emissions related to every component, aligning asset management and sustainability within business processes
- Converting technical documentation into a digital asset register to improve data analysis
- Understanding true capacity and demand within infrastructure to optimise business analysis and decision making
- Optimising the interface between operators and infrastructure owners to increase data sharing and improve asset management leading to increase asset lifecycles and reduce cost in parts and labour
- Incorporating tools to measure asset lifecycle emissions and social factors into your asset management systems, building the architecture to support decision making
- Improving demand analysis using RCM methodologies for structured decision making and criticality analysis to identify what the business want to reduce spare parts stocks
10:00 - 10:30
IMPLEMENTING MACHINE LEARNING AND AI TO FIND NEW INSIGHTS IN DATA, DELIVERING A BREAKTHROUGH BY ENHANCING GREEN MOBILITY
- Big data management, what are the challenges in extracting clean machine generated RCM data to pick up patterns and trends that might indicate an impending failure
- Increasing the repeatability and accuracy of algorithms to accurately forecast defects in a particular code with so many categories of codes to analyse from fleet components
- Building trust in the forecast to get the people using the tool, trusting the model
- Implementing machine learning to focus on issues that can impact maintainability, analysing congestion and weather data to understand impact on failures
10:35 - 11:25
COFFEE BREAK
11:30 - 12:00
ASSET CONDITION MONITORING: SIGNIFICANCE AND BENEFITS – A IOT BUSINESS SOLUTION
- Technological advancements such as automation in manufacturing is triggering the use of smart condition monitoring systems
- Smart asset condition monitoring covers all possible parameters that are required to keep a machine in better condition
- Real-time status of the temperature, fuel requirement, environment, and other conditions enable successful machine production
- Machine learning adds intelligence to the assets and allows an interlink between machines to deliver seamless performance within the plant
12:00 - 12:30
USING SENSORS AND PLATFORMS FOR OPERATIONAL DECISION-MAKING PROCESSES TO ACHIEVE MAINTENANCE 4.0
- Asset monitorization through Digital strategies and the impact on productivity and maintainability
- Key elements to consider for building a sustainable and effective ecosystem for Maintenance 4.0
- What is the right path for choosing the sensors mix and how to get the maximum efficiency in the data acquisition?
- Type of data for monitoring and how to manage them for the decision-making process
- Implementing Online sensors, i.e Online lube oil analytics for maintenance in critical assets
12:30 - 13:00
The Fundamental Elements Required to Get Real Benefits from Industry 4.0 Technologies
- Industry 4.0 is promising to maximize equipment production capacity by using AI predictive analytics to detect in advance potential failures in order to perform the corrections before equipment fails
- More than 50% of asset intensive companies operate with unplanned maintenance work over 50%
- ‘Will you be able to perform these corrections on time, when you are constantly flooded with urgent reactive work?
- You must realize that you first need to put the house in order and get out of the relentless reactive mode to be able to achieve real Industry 4.0 benefits
- Efficient Scheduling is at the forefront of the efforts to execute maintenance work in a planned mode
- The 4.0 digital technology must be designed specifically to support the process and ensure that the people are playing their role flawlessly to get real value from it
PLANNED INVESTMENT AREAS
- Predictive Maintenance PdM 4.0
- Remote Management
- Non-intrusive Inspection
- Lubrication Systems
- Augmented & Virtual Reality (AR & VR)
- Artificial Intelligence
- Cybersecurity
- MES / Shop-floor Digitization
- Workforce Training and Development
- M2M Communication
- Unified Communications / Wireless Connectivity
- Cloud, Edge & IoT Data Management
- Asset Lifecycle Management
- Energy Efficiency
- Machine & Deep Learning
- Wearable Digital Technologies
- Predictive Analytics
- Asset Performance Management (APM 4.0)
- Computerized Maintenance Management System (CMMS)
- Reliability Engineering
- Asset Optimization
- Sensors
- Data Analytics
- Condition Monitoring
- Fault detection, isolation, and recovery (FDIR)
13:05 - 13:55
LUNCH
14:00 - 14:30
Challenges in the operation of ground mounted Solar PV
- Intro
- Challenges
- A glance at OPEX
- Impressions from PV operations
- Would you hire an professional O&M provider?
“Does my PV system need operational management?”, Understanding the power plant main components, Main tasks for an O&M provider
Monitoring, KPI´s and preventive data analytics, Preventive maintenance and on hold service, Work save – under load?, Contractual guarantees – implementing standard calculation methods, Spare Parts Management, Curtailment management, Handling of new technologies (such as 1.500 V systems), Revamping / Repowering, business case renewal
Example 20 MWp solar farm, Potentials for cost optimisation
14:30 – 15:00
Enabling technologies for maintenance
I4.0 key technologies supporting the maintenance of the future: The Whirlpool experience in research projects
- Predictive maintenance in UPMASS project
- Augmented reality in 5G-INDUCE project
- Voice Worker assistance in K-HUB project
15:00 – 15:30
Manufacturing process optimization with Explainable Artificial Intelligence
- CNH Industrial business context with focus on manufacturing process before the application of Explainable Artificial Intelligence (XAI);
- Use case description, challenges, and motivation behind the needs of XAI application in manufacturing plant;
- Users’ stories on AI explainability: « what does the user want to know?»;
- Dashboard for XAI application within the XMANAI European project
- Conclusion considering the added value to business improving maintenance with XAI support
15:35 - 16:25
COFFEE BREAK
16:30 - 17:00
INFLUENCING GLOBAL CHANGE IN SUSTAINABILITY WITH OIL-FREE COMPRESSED AIR FOR MAINTENANCE PROFESSIONALS
- Compressed air in the big picture of sustainability – a step towards net zero emissions
- Carbon handprint – achieving your companies goals of carbon neutrality
- Compressed air solutions – a how-to for setting and achieving your climate goals
- Total cost of ownership
17:00 - 17:30
HOW COUPLINGS CAN PROVIDE INSIGHT INTO MACHINE HEALTH AND MAKE A DIFFERENCE IN OPERATIONAL AND FUNCTIONAL VALUE OF ASSETS
- Diagnosis: Challenges faced with conventional methods and identifying typically overlooked areas in equipment maintenance strategies
- Using smart’ couplings as a predictive maintenance tool to identify performance deterioration, optimize overhaul schedules and reduce emissions
- Overview of technology and how online platform can predict fatigue detection on concrete parts and equipment
- Future concepts and best practices
PLANNED INVESTMENT AREAS
- Predictive Maintenance PdM 4.0
- Remote Management
- Non-intrusive Inspection
- Lubrication Systems
- Augmented & Virtual Reality (AR & VR)
- Artificial Intelligence
- Cybersecurity
- MES / Shop-floor Digitization
- Workforce Training and Development
- M2M Communication
- Unified Communications / Wireless Connectivity
- Cloud, Edge & IoT Data Management
- Asset Lifecycle Management
- Energy Efficiency
- Machine & Deep Learning
- Wearable Digital Technologies
- Predictive Analytics
- Asset Performance Management (APM 4.0)
- Computerized Maintenance Management System (CMMS)
- Reliability Engineering
- Asset Optimization
- Sensors
- Data Analytics
- Condition Monitoring
- Fault detection, isolation, and recovery (FDIR)
17:35 – 18:10
PANEL DEBATE: DESIGN THE PERFECT WORKFORCE OF THE FUTURE: ARTIFICIAL INTELLIGENCE (AI) TECHNOLOGY IS RAPIDLY CHANGING THE MODERN WORKFORCE BY CREATING NEW SKILLS AND ERADICATING OTHERS. HOW DO WE READY OUR ENGINEERS AND TECHNICIANS FOR THE CHANGES TO COME
- What is AI’s impact on the skills of the future?
- Having a central platform to understand your workforce and how it compares to the market
- Empowering the technicians and engineers and creating organizational change
- Make informed decisions about where to build and grow talent to drive business growth in real-time
- Skills are the lifeblood of our organizations, how do you know what you’re working with today and what you’ll need to plan for tomorrow?
- How to deliver learning for effective skills development
- What are the must-haves for people-first organizations
18:10 – 19:10
DRINKS RECEPTION
DAY 2 – 17th NOVEMBER
08:55 – 09:00
CHAIRPERSON’S OPENING REMARKS
09:00 – 09:30
Maintenance in a vertical integrated (medical device) company
- Applied Medical, its vertically integrated culture and what it means for the maintenance department
- Applied Medical Automation team
- Maintaining equipment in “as new condition” in highly regulated environment
- Maintenance technicians, recruitment, and commitment in current market
09:30 – 10:00
HOW TO INTEGRAT THE MEGA TRENDS IN YOUR MAINTENANCE & OBSOLESCENCE MANAGEMENT
- The overall contribution of Maintenance within the digital maturity transition
- Critical assets obsolescence management integrating cybersecurity and energy efficiency
- The concept of energy centred Maintenance: a green maintenance system
- Potential of predictive technologies and the scale of smart maintenance practices
10:00 - 10:30
OPTIMAL USE OF SENSORS AND ASSETS TO MAXIMIZE PRODUCTION CAPACITY AND INCREASE UPTIME – ENTERING THE REALM OF PDM 4.0
- Key elements to consider for building a sustainable and effective ecosystem for Maintenance 4.0
- Setting-up asset maintenance strategy based on asset criticality is the foundation to maximize asset uptime
- Preventing asset failure maintenance and production experts are key and will only be achieved with a proper vision and clear definition of roles and responsibilities for all stakeholders involved
- Increased uptime is achieved by people and processes
10:35 - 11:25
COFFEE BREAK
11:30 – 12:00
CONTRIBUTION OF DIGITALIZATION AND ARTIFICIAL INTELLIGENCE TO THE VALUE PROPOSITION OF MAINTENANCE
- Maintenance as a value driver
- Role of digital tools in maintenance
- Example for process improvement using mobile apps
- Examples for applications of text mining and AI
12:00 – 12:30
DIGITAL FACTORY – MAINTENANCE WITH VIRTUAL TOURS, INDOOR NAVIGATION AND REAL-TIME DATA
- How to leverage a digital factory to streamline your maintenance planning and execution and improve your factory’s performance
- Use cases that showcase the capabilities of the digital factory, including work preparation, indoor navigation, and asset identification
- Utilising digital factory solutions to transform factory performance
12:30 – 13:00
IMPLEMENTING PREDICTIVE MAINTENANCE CORRECTLY: BEST PRACTICES AND PRACTICAL EXAMPLES
- First steps and Main challenges by practical implementation of PM functionality
- Selection of PM strategy
- Selection and construction of PM relevant features
- Expectations from PM systems
PLANNED INVESTMENT AREAS
- Predictive Maintenance PdM 4.0
- Remote Management
- Non-intrusive Inspection
- Lubrication Systems
- Augmented & Virtual Reality (AR & VR)
- Artificial Intelligence
- Cybersecurity
- MES / Shop-floor Digitization
- Workforce Training and Development
- M2M Communication
- Unified Communications / Wireless Connectivity
- Cloud, Edge & IoT Data Management
- Asset Lifecycle Management
- Energy Efficiency
- Machine & Deep Learning
- Wearable Digital Technologies
- Predictive Analytics
- Asset Performance Management (APM 4.0)
- Computerized Maintenance Management System (CMMS)
- Reliability Engineering
- Asset Optimization
- Sensors
- Data Analytics
- Condition Monitoring
- Fault detection, isolation, and recovery (FDIR)
13:05 - 13:55
LUNCH
14:00 – 14:30
Physics-based, data-centric and hybrid predictive maintenance strategies
- Strategies for developing prognostics and health management solutions when historical data is limited
- Need for domain-specific data processing strategies and overcoming the black-box nature of existing solutions
- Creation of data-centric explainable machine learning models to enhance prognostics and health management
- Development of hybrid models combining physics-based and data-centric approaches to improve prediction accuracy and reduce uncertainty
14:30 - 15:00
Manufacturing as an Enabler for Maintenance and Reliability
- Lifecycle approach as a way to reliable manufacturing equipment
- Risk exposure as a driver for maintenance levels
- Cooperation between manufacturing and maintenance as a foundation
- Data as an enabler for new ways of maintenance of machines
- Manufacturing equipment asks for maintenance
15:05 – 15:40
PANEL DEBATE – INSIGHTS FROM IMPLEMENTING INDUSTRIAL IOT IN THE AREA OF PRESSURE EQUIPMENT INSPECTION
- Combining compliance and reliability – the and-and perspective leads to co-operation
- Upgrade from run-to-failure to condition-based to predictive – combine sources to increase the level of detail
- Learnings from the deployment of IIoT sensors – all permanent installations are temporary
- Pressure equipment subject to corrosion-erosion – a conventional sensor, with a new level of insight
- Workflow integration as a crucial element of new technology – how many dashboards do you need?