CloudPulse

Cloud-Powered Intelligence,
Shaping Manufacturing's Future

From consulting to delivery, we help manufacturers embed digitalization into the shop floor, supply chain, and daily operations.

Manufacturing DXC-MRS PlatformQuality & Process Assurance
Challenge

Plenty of Systems, Problems Remain

Most enterprises don't lack systems — they lack the ability to see problems clearly, design the right path, and push delivery all the way to the shop floor.

01

Information Silos, Broken Collaboration

ERP, MES, QMS, and SCADA each manage their own slice. Process parameters, quality data, and production execution can't flow through. Cross-department coordination relies on manual follow-up.

02

Data Collected, Value Unreleased

Millions of data points are already being collected, but data stays at the storage and display layer — not yet converted into traceability, early warning, or decision support.

03

Systems Delivered, Shop Floor Disconnected

Acceptance is the peak. Six months after go-live, adoption is below 30%. What's missing isn't features — it's a delivery system that spans planning, rollout, training, and sustained operations.

Consulting

See Clearly, Then Act

We typically start with research, diagnosis, and solution design before moving into systems, connectivity, and implementation.

Current-State Diagnosis

Conduct systematic diagnosis of the enterprise's digital foundation and key bottlenecks, centered on business objectives and shop-floor realities.

Path Design

Design a phased, actionable digitalization roadmap with clear milestones.

Phased Delivery

Ensure platform, data, equipment connectivity, and organizational rollout proceed in the right sequence.

Capabilities

More Than Software

Software, industrial systems, equipment networking, data collection and governance, delivery, and ongoing operations — a complete implementation chain.

Solution Consulting

Systematic assessment around business objectives, management pain points, shop-floor conditions, quality requirements, equipment status, data foundations, and project phases.

Platform & Application Development

Building platforms and applications around business processes, role collaboration, and management requirements — making systems fit real operating patterns.

Equipment Networking & Installation

Beyond software, we have hands-on equipment networking capability — physically connecting shop-floor devices, data collection links, and system infrastructure.

Data Acquisition

Supporting PLC, CNC, sensor, and measurement device integration — bringing equipment-layer, process-layer, and quality-layer data into a unified pipeline.

Data Governance

Making data understandable, linkable, traceable, and usable — truly entering analytics, early warning, collaboration, and continuous optimization scenarios.

Project Delivery & Implementation

Emphasizing integration testing, training, go-live support, and continuous optimization — so project value starts releasing after delivery, not before.

Quality Methodology

Digitalization Must Reach the Process Level

G-PACV

Rooted in Honda's Global Process Assurance & Capability Validation (G-PACV) framework, encompassing a complete methodology of quality prevention, process control, change-point management, and continuous improvement. We continuously inherit and absorb the core understanding of this system, embedding it into digital system design, shop-floor quality management mechanisms, and process assurance practices.

01

Quality Prevention

Establish prevention mechanisms before problems occur, intercepting quality risks at the process source rather than final inspection.

02

Process Control

Implement real-time monitoring and interlocking management of critical process parameters, ensuring process stability and consistency.

03

Change-Point Management

4M1E change-point identification, assessment, and response — preventing the spread of anomalies across Man, Machine, Material, Method, and Environment.

04

Continuous Improvement

Data-driven PDCA cycles combined with shop-floor feedback and analytical insights, driving process parameter optimization and continuous evolution of the quality management system.

Platform

One Platform, End to End

C-MRS modules are deeply integrated with Agent intelligence, enabling data, processes, and knowledge to flow, collaborate, and evolve within a single platform.

01

Organization & Business Collaboration

Identity Management IAMHuman Resources HRMSupply Chain SCMSupplier Management SRMBusiness Intelligence BI
02

Manufacturing Execution & Shop Floor

Manufacturing Operations MOMProduct Lifecycle PLMQuality Management QMSEquipment Asset EAMEnergy Management EMSWarehouse Management WMS
03

Equipment Connectivity & Data

SCADA Data AcquisitionMaster Data Management MDMData Analytics BI
04

Knowledge & Intelligent Collaboration

Knowledge Base KBRetrieval-Augmented Generation RAGIntelligent Agent
Intelligence

From Data to Decisions

What we're building is not just tools, but industrial intelligent agents that continuously learn and evolve.

Predictive Maintenance Agent

Built around equipment status, operating trends, maintenance records, and anomaly signals — helping enterprises shift equipment management from reactive response toward proactive prediction and prevention.

Process Improvement Agent

Built around process execution, parameter changes, issue feedback, and improvement experience — helping enterprises identify process optimization opportunities more efficiently and support continuous improvement.

In-Process Visual Inspection

Built around work-in-progress quality identification, in-process inspection, and manufacturing scenario adaptation — continuously building industrial vision capabilities with stronger technical barriers.

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NEXT STEP

If you're thinking about what the next step in manufacturing digitalization should be, we'd like to help you map out the direction first.

Whether you're at the digital assessment, solution design, system construction, or project optimization stage, we're ready to work with your business context, shop-floor realities, and phase objectives to determine which problems deserve priority, which paths are most viable, and which capabilities are worth building first.