A Single Source of Truth Leaves No Asset Data Behind
Odbok Contributors: Don Sands (Synengco), Steve Miller (Odbok), Mark Freund (Diriger), Jeff Lloyd (Precoda)Author: Greg L Towne (Diriger)When you combine the expertise, experiences, industry leadership, methodologies, technologies, and systems of the members of a collaborative ecosystem like Odbok, you get the synergy of a rigorous and interoperable Asset Unified Namespace (UNS) that leaves no Asset Management Data behind and hence, provides a Single Source of Truth; be it consistent data or documentation and the methodology to achieve it.
Your problem-solving capability is optimised, enhanced, and then extendable via solutions that are innovative, consistent, and user-actionable from the ground (physical devices) up to multi-enterprise views, decisions, and actions. It is just what you would expect when establishing a modern Industry 4.0 environment that needs more than just a reporting and graphics solution; it is a methodology that delivers a Single Source of Truth.
WHAT ISSUES AND PROBLEMS CURRENTLY EXIST IN THE INDUSTRY?
Let’s look at some of the problems we already know about
Industry
Underperforming assets account for approximately 30% share of operating expenses
Repair and maintenance costs increase by 10 – 15% year on year
Every third maintenance and repair activity are potentially unnecessary in this time of knowledge and technology
Predictive and proactive maintenance generally will cost 10% less than preventative maintenance and 40% less than corrective maintenance
People
Working staff spend less than 4 hours daily on the direct execution of work as they are overwhelmed with administration and other distractions
50% of industry employees with ‘across the board’ knowledge will retire in the next seven years, and their detailed site-based knowledge will walk out the door
Good people who understand the whole business and the potential of technology and continuous improvement are locked in silos
Systems and Processes
Critical decisions and actions are occurring in an environment of:
Derailed and disparate systems that employ complex linear forms of integration
Missing, sub-standard or un-attainable reference material (Documents, Schedules, Specifications, Drawings, Standards, etc)
Persisting with legacy systems that are sub optimal or have fallen into a state of atrophy
Alignment to core data references between systems and operating levels causes huge interoperability problems and, hence, little ‘trust’ in both data foundations, information provision, and knowledge-based usage
Band-aid measures such as massive data lakes are struggling for creditability in a dynamic business playground and, hence, are turning into data swamps
Large Asset-intensive enterprises are looking at utilising AI and ML innovation but are getting frustrated and blocked by the lack of salient foundational data quality
Project to Operations Handover - Engineering, Design and Construct Projects continue to ‘overlook’ the key opportunity for introducing better data and reference material during commissioning and handover to Operations
Summary Metaphor
In essence, the current systems and methodologies are akin to a Thermometer; a device that only tells the User the current temperature – whereas what industry really needs is a Thermostat; a device with actionable characteristics in terms of temperature range, durability, vibration resistance, chemical resistance, and application compatibility – so that it can automatically do things in relation to its set point and expected capability.
CURRENT STATE INTEGRATION (Industry 3.0)
Current Industry 3.0 attempts at integration are continuing to fail as current technology and approaches are based on linear, discrete, and complex methodologies that continue to create more and more technical debt and sub-optimal outcomes when compared to newer Industry 4.0 capabilities.
These Current state issues are further exacerbated by existing technologies, resources, skills, system atrophy, and implementation methodologies that serve as band-aids and regularly fail. We can illustrate this in the diagram below, where the ‘current state’ is shown within the ISA-95 Levels and is aligned with the standard DIKW Pyramid.
The significant barriers to success magnify the transitions between ERP, MES and DCS, mainly due to a poor data foundation, linear integration methods and lack of interoperable capabilities. These sub-optimal outcomes result in the Information not being transformed into Knowledge, and Knowledge is not transformed into Insights and Actions.
POTENTIAL BUSINESS IMPACTS OF THESE ISSUES AND PROBLEMS
The atrophy impacts on systems, business misalignment, and interoperability can be the equivalent of a cumulative tax on your organisation from the bottom to the top, with some cumulative estimates being as high as ~70%.
TRENDING BUSINESS GOALS
Existing and predictable business expectations and goals have amplified the needs to:
Maximise asset reliability and availability so that impacts on OEE can be readily assessed
Provide quick access to trusted asset information across all classes and levels in real-time
Foster workforce collaboration to maximise skills utilisation where it is needed most
Visualise AI-based insights that facilitate fast and accurate decision-making and actions
Deliver accurate, data-based remediation to close the loop, control costs, and sweat your assets
INFLUENCES AND MEGATRENDS FOR OUR DIRECTION
Our approach is influenced by leveraging several megatrends impacting most asset-intensive operations:
The transition from human-based insights, decisions, and actions to digital machine-assisted decisions
The gig economy, where personnel do not stay in the same job for long and walk out the door with valuable data, information, and knowledge-based experiences
The transition to sustainable and renewable resources means that traditional life cycle asset management has additional complexity and constraints
The rapid increase in new technologies and methodologies forces organisations to embrace change or risk obsolescence
These megatrends drive towards increased use of digital technologies to support better insights, faster decisions, and sustainability within increasingly complex environments and constraints.
Hence, Asset Management needs to accommodate:
The increasing use of digital technologies to support physical asset management
The ability to use short-lifecycle digital technologies (due to the speed of innovation) with long-lifecycle physical assets (due to maximising lifecycle value from investments)
Customisation of management processes to fit the actual operation and
The provision of systems with high adoption rates through viable Organisational Change Management (OCM) and interfaces that provide low cognitive loads
The quality of the data used by the digital tools and the humans is the key to making digital machines better decision-makers. A key element of our solution is the design and governance around quality data and structures to amplify the collaboration and its benefits between digital devices and humans to facilitate “Explainable” Artificial Intelligence.
INTEROPERABLE DIGITAL ECOSYSTEM
We believe digital solutions should be sticky due to the value they create rather than being sticky due to being locked into a particular vendor’s digital ecosystem. As a result, subscribing to an open standard, vendor-neutral digital ecosystem allows for low-cost solution switching and portability.
The framework adopted needs to provide for future-proofing of digital technologies as the digital services and components are abstracted away from the digital tools, thus deriving several benefits:
Ease of configuration of new digital tools as they can draw upon the Common Conceptual Object Model (OIIE CCOM) for configuration
Simpler management of change as the modifications can be implemented at the CCOM level, and the digital tools can be checked against this shared resource, and
It can extend the life of current enterprise systems at a lower technical debt
We subscribe to ISO18101 and the OIIE (Open Industrial Interoperable Ecosystem) that form part of the standard to ensure the Interoperable Digital Ecosystem is fully vendor-neutral with open ISO standards as the basis of vendor neutrality.
References:
INDUSTRY and ACADEMIC OIIE FOCUS GROUPSYSTEM
Continuing from the above, a joint effort (working group) is also a work in progress between Texas A&MU and Adelaide’s UniSA on an Asset Data Interoperability Framework (ADIF), which focuses on six main problem areas.
P&ID linkage to Engineering Models and Data and visualisation
Normalising Catalogue/Template/Legend sheets
Terms, Definitions and Identity
Maintenance and Operations Data Standards
Tag Management Philosophy and Implementation
Geo-spatial Coordinates and links
We align with these same focus points and do not underestimate the importance and influence of such alignment in the solutions we have crafted and the direction we will take downstream
THE UNIFIED NAMESPACE CONCEPT (UNS)
We are putting forward several best-of-breed solutions that can interoperate with each other and your existing enterprise systems in a vendor-neutral Enterprise-level UNS (Unified Namespace). Our methodologies and experience in delivering such solutions allows us to adapt to the customer’s requirements as they progress, without impediment, through multiple levels within an organisational structure. We do this by packaging the capability of a conceptual UNS, as depicted below.
ATTRIBUTES THAT AN ENTERPRISE UNIFIED NAMESPACE COMPRISES
At a minimum, a UNS should comprise seamless capabilities as follows ….
Business Goals, Decision Drivers, Strategies, and measurable Objectives
Business Functions, Tactics and Asset Life-cycle Management
Related Business models and terminology (naming conventions)
Governance, Directory Services, Policy Management and Versioning
Interoperability and related Technologies within a Secure Data Fabric
Asset Master Data Management (MDM) and salient Change Control (MOC)
Scalable Data Sources and Directories for Meta Data, Documentation, Specifications, Drawings, Parts Lists (BOM, etc.), Templates, Configurations, and Object Libraries
Semantic libraries for Taxonomies, Ontologies, Metrics etc.
Synchronisation and replication capabilities via a messaging broker
Transaction and Event scheduling, logging, and auditing
Data validation and resolution mechanisms to ensure consistency
ECOSYSTEM SOLUTION CAPABILITY OVERVIEW
The Odbok Industry 4.0 Interoperable Ecosystem
This model outlines our Odbok Ecosystem for a federated UNS solution supported by a System-of-Systems interoperable environment and Governance Methodology. The first step in IT/OT Convergence
Our Unified Namespace provides
Enterprise Level UNS - Unified Namespace with a common operational philosophy and infrastructure
Scalable and secure SST - Single Source of Truth with alignment and auditable MDM - Master Data Management
Multiple flexible hierarchies e.g. ISA95, ISO14224 and Multi-system DOA - Delegation of Authority
Effective MOC - Management of Change
MQ - Message Broker interoperability with OIIE, MQTT Sparkplug, OPC-UA API's and others
Business Rule and Workflow capability with extensive Business Function library
Odbok Collaborative Ecosystem
Data Management and Governancebok methodolgies
Advisory and Architectural services
Industrial Standards Librarby and API's - Application Programming Interfaces
Global Business Interoperability standards e.g. OIIE
DirigerHUB Unified Enterprise Interoperability Platform
Syngengco's APM - Asset Performance Management
Precoda Methods and Data Standards
Governance, Methodology and Standards [ODBOK]
Within an interoperable digital ecosystem, the quality of data and alignment of data structures is paramount between all the digital service providers. While each vendor has its data structures and ways of ensuring the quality of the data used, a methodology to support all vendors and solutions reduces the effort required and improves the quality of a combined solution. It also provides for the addition of new vendors into the ecosystem with minimal rework.
Systems-of-Systems Interoperability [Diriger]
The interoperability capability provided by DirigerHUB makes the solution as seamless and scalable as possible, plus allows for flexible transition approaches aligned to the internal capability within the customer organisation. Additional system-of-systems capabilities and data sources can be added as required.
Diriger also provides Industry standard Asset Master Data Management (Asset MDM), Management of Change (MOC), and API Management (OIIE, OPC, MQTT, etc) for verification and validation (V&V) of data consistency across all application levels.
Plant Optimisation, Simulation, Performance [Synengco]
Sentient System is a decision support and real-time optimisation platform for asset-intensive operations. It uses a self-learning digital twin of a process to provide for model-based decisions. The key to the technology is to automatically maintain alignment between the physical plant and the digital representation of the plant.
Taxonomies, Ontologies, and Standards [Precoda]
A significant key to the success of the Unified Namespace is the agreement, deployment and synthesisation of salient industry standards, appropriate taxonomies and ontologies. Our Off-The-Shelf standards library provides the capability for building synergy between various systems and the desired operating philosophy.
CONCEPTUAL UNIFIED NAMESPACE - MODEL COMPONENTS
ODBOK METHODOLOGY OVERVIEW
The Odbok Methodology is a Systems and Data Lifecycle methodology, and it will be refined specifically for the customer to encapsulate their objectives and constraints. The Odbok methodology is designed to be implemented in either a greenfield or a brownfield situation, enabling the customer to determine the pace at which remediation and alignment occur. It orchestrates project and maintenance changes across all systems to maintain the integrity of business objectives, compliance, and operations data.
Govern: Develop and maintain your system and site agnostic references e.g. Attributes, measures, UoM, classifications, functional locations, standards, formulas and aggregations.
Design: Develop and maintain your system and site agnostic template catalogues e.g. Asset templates, Hierarchy templates and composite templates.
Build: Develop and maintain your site and system-specific implementations and changes as change packages.
Deploy: Orchestrate the deployment of your changes in concert with the other associated works being done.
Monitor: Monitor the changes that are deployed or implemented directly. Capture data from the system for input into the quality and health statistics.
SOLUTION CAPABILITIES CHECK LIST
The summary below provides an indication of the capabilities that the Enterprise UNS solution can provide in all varying situations.
Business Functions, Decision Drivers and Asset Life-cycle Management
Library of more than 500 business functions available for rules and workflow adaption
Alignment to common operational philosophies and infrastructures
Multiple Hierarchies and Delegations of Authority and Approvals
Safety Integrity Level (SIL) capabilities
Reduced risk, process safety and improved security
Maximise AI and ML Data Insights and Actions
Quicker time and consistent approach to problem resolution
Rapid, unique business insights and linked analytics
Models and Terminology
Terminologies and object models (hierarchy models, object models, operations activity models, and functional data flow models) across all levels
Activity Models for Operations Management (MOM) - activity models within workflows that facilitate and govern (via Business rules) the integration of enterprise systems with the control system
APM, Modelling and Simulation (Digital Twin)
Monitors the fundamental changes in performance and asset consumption, continuously calibrates the digital twin by sophisticated machine learning and uses this self-calibrated digital simulation to provide….
Detailed asset health and performance at a component level
Precise and quantified system impact from changes to asset health and performance
Predict future behaviour based on historical behaviour changes
Early warning when the expected behaviour does not align with the predicted behaviour
Real-time optimisation by simulation and manipulating the digital representation of the plant to find improved operation from a production and/or asset consumption perspective
Once optimised in the digital world, execute the changes to the real-plant and ensure the actual change aligns with the expected improvement.
Governance Methodology
Designed and established to assist companies to align, integrate and industrialise the data within their systems in readiness for Digital Transformation and Industry 4.0 Automation initiatives.
A Framework for ….
Maintaining a technology agnostic reference architecture
Continuous optimisation of our Data Foundation Methodology
Collaborating across multiple disciplines and sharing outcomes with our customers
Maintaining our focus on ensuring high-quality data outcomes for our customers
Leveraging the years of experience and knowledge across our SMEs
Refer to the separate section on the Methodology Overview above.
Services
Multi-level Services capability from device installation through to ERP/EAM systems
Advisory and Architectural Services (both Strategic and Tactical)
Business and Technology Strategies
Technology
Deployment to Cloud or on-premise
Micro-service architecture
AI / ML deployment via Open technologies
Composable PWA (Progressive Web Apps) for any device, anywhere
Access anywhere (online and offline if required)
Innovation that scales whilst reducing Technical Debt
Interoperability
Autonomous / Interoperable computing capability
API Management to OIIE, OPC, MQTT frameworks
Transactional Interoperability that mirrors how enterprise systems exchange information with manufacturing and automation systems at levels 3 and 4 of ISA-95
Messaging Service Models that define a messaging service model that enables applications performing business and manufacturing activities across ISA-95 levels 3 and 4 and within level 3 to exchange information
Interoperability aligned with the OIIE and ISO 18101
Artificial Intelligence and Machine Learning
Highly scalable and accessible cloud deployments
Micro Services and Containerisation
PWA (Progressive Web Applications) for mobile and offline capability
Integration, Business Rule, and Workflow platform technology
Design Thinking approach to Persona and Process-based low cognitive load UI/UX (Composable User Interface and Experience)
Data Consistency
Methodologies, Architectures, Data Management, and Governance specifically designed for industry and Standards-based Templates
Automated Verification and Validation for each level to Standards and Frameworks
Full audit-ability and corrective actions for all events and transactions
Data Governance Management
Methodology includes…..
Master Data Management (MDM) between all ISA-95 levels
Management of Change (MOC) between all ISA-95 levels
Objects
Various Categorised Object Libraries.…
Documents, Drawings, ISDD’s, Templates, Configurations, Suppliers, External Site References, Contracts, Specifications, Manuals, Procedures, Policies, Guides, Video, Parts lists
User Interface and Experience
Composable UI/UX (Mobile 1st PWA developments) that reduces Technical Debt
Faster and Easier process-based UI/UX with managed corrective capability to V&V rules
Enterprise universes are centred around roles
Automation
Auto-maximise AI and ML Actionable Insights and Data Validation to Business Rule and Workflow Engines
Data Storage
Scalable data storage
Built-in Registers and Database Links
Secure Data Fabric
Secure Consistent Data Fabric to ISO Standards
Standards and Frameworks
Current Standards …..
OIIE, CCOM, SDAIR, CIR, ADIF (Texas A&MU and Adelaide UniSA)
ISO, ISA, OPC-UA, MQTT Sparkplug, CFIHOS, DEXPI