/ Manufacturing
Manufacturing data from sensor to decision
From discrete manufacturing to process industries, we build the Industry 4.0 stack that pays for itself: IoT platforms, predictive maintenance, and quality analytics wired into the ERP. Downtime drops, defects surface early, and the plant runs on numbers instead of hunches.
- 28% less unplanned downtime
- 21% lower defect rate
- 99.2% equipment availability
- OT and IT integration
Manufacturing since 2006
IoT, quality, and supply-chain data in production.
Why plants fly blind
The line already talks.
We make it heard.
SCADA, MES, ERP, and quality systems each hold a slice of the plant, and failures announce themselves in sensor data days before they stop the line. A platform that reads every slice catches them while they are still a work order. We wire OT and IT into one place and keep it running.
99.97%Uptime across 72+ servers
Enterprise IT operations automated with DevOps and monitoring. The same operations discipline we bring to plant systems.
Read the case study
/ What we build for manufacturing
Industry 4.0, with the numbers to show it.
01
Predictive maintenance
Models that read sensor and maintenance history and flag failures before they stop the line. Across 50+ production lines on one engagement: 28% less unplanned downtime, 45% lower maintenance costs, and 99.2% equipment availability.
Azure IoT HubDatabricksPython
Azure IoT Hub
Databricks
Python02
IoT data platform
Edge-to-cloud platforms that ingest and process data from thousands of sensors in real time. Built to scale with the plant network, not to be rebuilt when the second site comes online.
Azure IoTAWS IoTKafka
AWS IoT
Kafka03
Quality analytics
Computer vision and ML quality control that catches defects early and traces root causes. One deployment cut the defect rate 21%, detected defects 35% faster, and took the rework bill down with them.
AWS SageMakerOpenCVSnowflake
Snowflake04
Supply chain intelligence
Demand forecasting, inventory optimization, and supplier risk prediction on one governed view of the chain. The disruption shows up in the data before it shows up at the dock.
DatabricksSAPPower BI
SAP
Power BI05
Digital twin
Digital representations of physical assets for simulation, monitoring, and what-if analysis. Try the process change on the twin before you try it on a running line.
AzurePTCSimulation
06
MES and ERP integration
Manufacturing execution systems connected with enterprise platforms for end-to-end visibility and OEE optimization. SAP stays the system of record; the platform makes its data usable.
SAPSiemensRockwell
/ Manufacturing systems
Fluent on the plant floor.
The control, execution, and enterprise systems a manufacturing engagement has to integrate with. We connect what you already run.
SCADA/PLC Integration
Industrial control systems
MES Platforms
Siemens, Rockwell, SAP
IoT Platforms
Azure IoT, AWS IoT, PTC
ERP Systems
SAP, Oracle, Microsoft
Quality Systems
QMS integration
Edge Computing
Real-time processing
/ Results
Measured on the line, not the slide.
Fortune 500 Manufacturing Client
84%Reduction in Service Request Processing Time
How ACI Enabled Integrated Service Management for a Multi-Region Construction Leader
Read the case study
Fortune 500 Manufacturing Client
87%User Adoption Rate
ACI Digital Procurement Platform Improves Customer Experience and Savings by 22%
Read the case study
Fortune 500 Manufacturing Client
$12.4MAnnual Cost Savings
ACI Streamlines Logistics for Chemical Manufacturer, Saves $10M
Read the case study/ How an engagement runs
Five phases. No mystery.
01
Assess
Walk the plant, inventory the systems, and pick the use case with a number attached: downtime, defects, or OEE. Baseline it before building anything.
02
Connect
SCADA, MES, ERP, and quality data wired into one governed platform. Real-time where it earns its keep, batch where it does not.
03
Model
Predictive maintenance, quality, or supply chain models built on the connected data and tested against your own history.
04
Prove
Results measured on one line or plant against the baseline. A first governed use case lands inside the 10 to 14 weeks we quote.
05
Scale
Roll out across lines and sites with 24/7 operations under SLA, so the platform outlives the pilot team.
The plant floor is a data source.
Predictive maintenance and quality analytics stand on the same foundation as every other model: governed pipelines that pull sensor, MES, and ERP data into one place and keep it trustworthy. That foundation is our data engineering practice.
Data Engineering/ Why ACI
Why manufacturers build with us
/ Downtime
28% reduction in unplanned downtime on delivered engagements, measured against client baselines rather than a brochure.
/ OT and IT
SCADA, MES, ERP, and quality systems brought into one platform.
The whole line in view, not one slice of it.
/ Scale
Founded 2006.
1,200+ engineers across 11 global delivery hubs. 500+ enterprise projects.
/ Operations
ISO 27001 certified and CMMI Level 3 appraised, with 24/7 managed operations under published SLAs.
From the blog
Digital Transformation
Industry 4.0 in Action: How to Transform Your Factory Into a Self-Optimizing System
Discover how manufacturers use AI, IoT, and real-time analytics to build self-optimizing smart factories and drive Industry 4.0 transformation.
Read
Technology Trends
Smart Manufacturing with AI and IoT: Predictive Maintenance that Prevents Downtime
Learn how AI and IoT enable predictive maintenance to reduce unplanned downtime, improve OEE, and drive smarter manufacturing operations.
Read
Insights
Polyfunctional Robots in Manufacturing: Automation Trends Driving Efficiency
Polyfunctional robots bring flexibility and AI to modern manufacturing, improving efficiency, agility, scalability with ACI Infotech automation solutions.
Read/ Manufacturing FAQ
Manufacturing questions,
answered straight.
What manufacturing problems do you typically solve?
Supply-chain visibility, predictive maintenance, quality analytics, and pulling SAP and shop-floor data into one place you can report on. The common complaint is data trapped in systems that do not talk.
Do you work with IoT and shop-floor data?
Yes. We bring sensor and machine data together with ERP and quality systems so you can see the whole line, not one slice. Real-time where it earns its keep, batch where it does not.
Can you reduce unplanned downtime?
Predictive maintenance models that read sensor and maintenance history flag failures before they stop the line. We measure the downtime avoided against your baseline, not against a brochure.
How do you integrate SAP with everything else?
We move SAP data into a governed platform alongside MES, quality, and logistics, with the lineage to trace any number back to source. SAP stays the system of record; the platform makes its data usable.
How long does a manufacturing data project take?
A first governed use case, like supply-chain visibility or downtime prediction, in 10 to 14 weeks. We prove it on one line or plant before rolling it across the network.