HP March 2022 eBook—Energy Transition - 86

Sustainability
is unwise in this case, as the specific initiatives
and projects would cover varying
domains and invoke contributions from
different ecosystem participants. Nevertheless,
common guiding elements are
essential for a successful change toward
sustainability (FIG. 5), as explained in the
following subsections.
Raw materials usage
Process operations
Products and offerings
Gain mindshare: Operational excellence
and supply chain integration have
economic goals that are easier to communicate
and empower. Sustainability
metrics sometimes require trade-offs and
compromises with overall economic objectives.
Safety, for example, can never be
articulated with a business value in mind.
Non-renewables material intensity A normalized measure of non-renewables consumed per unit of feedstock
Recycled/reprocessed feed
Percentage of recycled feed
Water intensity
Energy intensity
GHG intensity
Residuals intensity
Reused/recycled content
Recyclability
Restricted substances content
Total water intake-normalized by unit or volume
Energy consumed in production and overhead
GHGs released in production and overhead
Mass imbalance (products, feeds, consumables)
Percentage of reuse/recycle portion in product
Percentage of recyclable content in product
Percentage of restricted chemicals in product
FIG. 6. Standard sustainability metrics are relevant to process manufacturing.
Visibility-Capture all data and associated classified incidents
Analyze-Historical information: What, where, when, who?
Discover-What we do not know or is not intuitive
Predict-What is at risk, in an actionable way
Prevent and advise-Interactively suggest best actions
Plan-Improve processes, barriers, risk mitigation
Augment-Enrich and add new data
Information integration
Leading indicators
Data mining
Predictive modeling
Cognitive
AI, machine learning
Process improvement
Augment with technology
IoT/sensors/drones
FIG. 7. Technology helps augment existing information, enable predictive capabilities, optimize
processes and deliver visualization with actionable insights.
Maintenance
Inspection
Process operations
Executive oversight
Sustainability stewards
Data analysts and scientists
Contextualization,
models
More than any other domain, this requires
a significant top-down mandate for adoption
and ease of change management.
Take action: Proliferation of key performance
indicators (KPIs), operational
or otherwise, is a sure way to get " lost in
the weeds " and eventually end up as another
wasted opportunity. Identifying the
right metrics, the correct calculation basis
and the actionable outcomes are the essential
parts of any sustainability program.
To that effect, it makes much more sense
to follow a set of standards when defining
the metrics. Standard sustainability metrics
that are relevant to process manufacturing
are shown in FIG. 6.
Sustain and improve: Effectively exCloud
and APIs
KPIs, trends
Statistical analysis
Correlations
ecuting such a transformational initiative
will require change management that is
cognizant of the traditional focus around
operational excellence. Incentivization
and empowerment are key to sustaining
this initiative and incorporating a continuous
improvement program. Leveraging
the right technology-IIoT (for additional/new
information), blockchain (for
traceability of products to batch lots, etc.)
and hybrid cloud options (for enterprise
platforms)-is the primary enabler of
such a program.
Leveraging technology for sustainability.
Technology disruptors, such as
IIoT, blockchain, artificial intelligence
(AI) and robotics, are being adopted in
process manufacturing5
at an unusually
fast rate, particularly for an industry that
is known to be lukewarm toward risk-reward
propositions.
Technology continues to be adopted
Visualizaton/reporting
Authorization and access control
Data warehouse
Analytic tools
Central data store
Operations data store
Reference semantic model
Authorization and access control
Analytics master files
Data lake
Machine learning tools
Model management
Data engineering/prep
Transactional records
Incident
management
Warehouse
and inventory
Work
permits
Process control information
Asset monitoring
LIMS
Process
historians
Process
units
IOT sensors information
Field-force
automation
Warehouse
and materials
Contractor and
employee safety
Extended value chain
Supply
chain
FIG. 8. Different, equally viable and advantaged approaches are available to accomplish
a number of operational goals.
Sustainability
goals/targets
in such a way as to augment existing information,
enable predictive capabilities,
optimize processes and deliver timely visualization
with actionable insights (FIG. 7).
Different, equally viable and advantaged
approaches are available to accomplish
these goals. Organizations adopt a myriad
of options for data ingestion, integration,
staging and analytics. Options such as data
lakes, data warehouses, traditional middleware-based
integration or contemporary
hybrid-cloud enterprise platforms provide
viable paths to efficient information management.
Delivering context to the data
that can be leveraged by advanced analytics
is a key critical success factor to all of these
data-management approaches (FIG. 8).
From an adoption perspective, it is easy
to get lost in trying to prove a technology
Hydrocarbon Processing | JULY 2020 | HydrocarbonProcessing.com
Manufacturing information sources Ingestion/integration Storage/staging Data/cognitive analytics/visualization

http://www.HydrocarbonProcessing.com

HP March 2022 eBook—Energy Transition

Table of Contents for the Digital Edition of HP March 2022 eBook—Energy Transition