Sustainable and Compliant Industrial Operations for the Digital Era

Co-optimising Efficiency, Quality and Sustainability, Circularity

Sustainable Operations

From Environmental to Sustainable and Circular Industrial Operations

Predictive Quality

From Standard to Predictive Quality and Zero Defect solutions

Predictive Maintenance

From Routine to Predictive Maintenance and Zero Breakdown solutions

OEE Optimisation

From OEE to Availability and AI-driven Performance analytics and optimisation

The Z Prime Genomic AI Platform™ solution is an advanced AI system for the manufacturing industry that optimises industrial efficiency and quality in combination with sustainability and circularity in a single system to enable balanced decision-making for Operations and Investments.

~0%

Higher Equipment Availability

20~0%

Aeration energy reduction

30~0%

Carbon footprint optimisation

>0%

Sensor reliability improvement

30~0%

Reduced / Modified Control of DO in Aerated Compartments

10~0%

Man-hours Reduction to Monitor & Operate System

OEE Improvement

10~0%

OPEX Reduction

Throughput Improvement

Defects Improvement

~0%

NO2 Reduction

Z Prime Genomic AI Platform™

The Z Prime platform is an industry-agnostic solution that collects multiple sources of data, models reality in a Genomic AI Platform, which wraps itself around the physical system using sophisticated analytics, provides deep insights and predictive simulations across multiple concurrent areas of an Enterprise: productivity, efficiency, quality, inventory and environmental impact.

The Z Prime Genomic AI Platform is a cloud-based service that is available in private/public/hybrid clouds or on-premise deployment options. 

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Marketecture Industry 4.0 digital transformation: smarter factories with AI-driven Industry solutions

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Z Prime Insights™

The Z Prime Insights software product leverages the data provided by the Z Prime Genomic AI Platform to provide the following key features. 

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Z Prime Genomic AI Platform™ 

At the heart of the Z Prime software platform is the Z Prime Genomic AI Platform that turns data into a real-time digital replica of an industrial organisation to enable insights and advanced decision support systems including predictive simulation and co-optimising of operational and environmental objectives.

Taking pre-processed data from the iDaQ, the Big Data Collider analyses it, understands its context and relationships with other data and manipulates and fuses it in ways that enable it to be used by relevant models in the Reality Modeller.

Z Prime leverages several different models to create a digital twin including ML/AI, data-driven, mass balance, event-driven, physics-based and computer vision models. It also includes the unique Genomic of Industrial Process™ that models causal relationships against desired and undesired outcomes, and identifies the underlying drivers (the ‘genes’) enabling complex diagnosis and rectification of manufacturing process defects beyond the scope of standard Deep Neural Network algorithms.

Data is used by the models to present real-time data that comprehensively models reality through complex calculations integrated across the key areas of: productivity (availability, OEE), efficiency (energy, discrete energy profiling), quality (defects, reliability), inventory (track & traceability, production scheduling) and environmental impacts (carbon footprint, circularity, sustainability).

Z Prime iDaQ™ 

Z Prime’s iDAQ is an intelligent data acquisition system that collects, cleans, and pre-processes data from both Operational Technology (OT) and Information Technology (IT) sources within a manufacturing environment. The system integrates data from a variety of OT devices such as sensors, SCADA systems, PLCs, cameras, and actuators.

Z Prime iDaQ™

iDAQ efficiently handles data from IT systems including ERP (Enterprise Resource Planning), MES (Manufacturing Execution Systems), SCM (Supply Chain Management), and ESG (Environmental, Social, and Governance) databases.
More than simple data collection and formatting, it utilises five critical checks on the raw data, conducting preliminary data preparation and analytics to package it for processing by the Big Data Collider.

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