fss-decor

Smart Industry

FSNext:Artificial Intelligence Integrated Industrial Solutions

Smart Industry Components

• Smart Energy

• Smart Inventory Management

• Smart Plant Maintenance

• Smart Quality Assurance

AI-Artilificial Intelligence

• Machine Learning

• Deep Learning

• RPA-Robotic Process Automation

Industry 4.0

• Big Data & AI Enhanced,

• Holistic (End-to-end) & Integrated Approach with

• Decision Support & Early Warning Systems

Smart Inventory Management

Material (Raw Material, Semi-Product, Finished & Trading Goods, …) Transactions are managed by AI integrated services of Machine/Deep Learning to increase the operational efficiency. Big Data are collected in FSCore and integrated to FSSmart; AI integrated decisions guide the operations such as Unloading, Unpacking, Putaway, Replenishment for Production, Picking, Packing & Loading… considering the necessary criteria and algorithms for each operation.

img
img

Smart Quality Assurance

The results of the Quality Control Operations for Receipt, Sampling, Production, Shipment, … are tracked and including the data collected from external systems & ERP, the Big Data & Data Models are formed in FSCore. The preventive actions are generated by the AI Services of Machine/Deep Learning in FSSmart to decrease the Non-Conformities due to Quality Issues.

Smart Energy

Energy Consumptions & Carbon Emissions are examined by our consultants and necessary measurement & consumption plans are offered. Internal/external parameters are continuously tracked by measuring & analyzing in order to Decrease the Energy Consumptions & Carbon Emissions by AI Services with Machine/Deep Learning in FSSmart. The Big Data are formed in FSCore which is integrated to FSSmart.

img

Smart Plant Maintenance

AI integrated predictions are genereated by collecting external and ERP data into Big Data in FSCore which is integrated to FSSmart with AI Services in order to prevent downtimes and nonconformities before happening in the Work Centers.

AI Integrated Supply Chain

FSStockChain manages the Vendor Inventories (in various scenarios such as Consignment, Safety, Minimum, Reorder Level, … Stocks) and makes predictions on Quality Control Results (in various operations such as Receipt, Sampling, Production, Shipment, …) to decrease the QA Issues. The Predictions and Results can be published (optionally on a BlockChain) to vendors and/or events can be triggered by RPA).

img

Industry 4.0

We recommend a holistic & integrated approach for the updating of processes & infra-structures during transition of industry 4.0; enhanced with Big Data & AI-Artificial Intellligence having Decision Support/Making & Early Warning Systems.

Smart Industry References All

img
Smart Inventory Management for Produciton

This Project has been approved and funded by TUBITAK (National Scientific & Technical Research Council). It has been started in Jan.2022 and is planned to-be completed in Dec.2023. Kora is the AI Partner in the Project.Big Data will be formed by collecting data from FSMobility and SAP by FSCockpit in FSCore. The results will be provided by AI Services with Machine/Deep Learning in FSSmart.Uses Cases will be selected from FG, Production & Material Warehouses including Work Center Replenishment in order to increase operational efficiency.

img
Smart Plant Maintenance for Production

This Project has been approved and funded by TUBITAK (National Scientific & Technical Research Council). It has been started in Jan.2022 and is planned to-be completed in Dec.2023. Kora is the AI Partner in the Project.Big Data will be formed by collecting data from the pilot MTP101 Work Center (IoT/M2M), BITEG-Manufacturing Execution System and SAP by FSCockpit in FSCore. The results will be provided by AI Services with Machine/Deep Learning in FSSmart.Uses Cases will be selected from MTP101 as a pilot Work Center in order to predict preventive actions and decrease the downtimes of the Work Center.

...
Integrated Framework for Real Time Supply Chain

This Project has been approved and funded by TUBITAK (National Scientific & Technical Research Council). It was started in Jan.2019 and completed in Dec.2020. Galaksiya was the AI Partner in the Project.AI-Integrated Services were developed in order to decrease the QA nonconformities by predictions according to the Receipt Quality Results. The results were published to the vendors.