Aktiviteter

Digitalization and continuing pressure from the automotive industry with regards to quality-, efficiency- and product/process-optimization are a daily challenge to medium-sized component manufacturers.

Specifically medium-sized component manufacturers are aware of the necessity to identify suitable smart manufacturing (industry 4.0) tools, however the inhouse knowledge, experiences and internal resources are limited to successfully scout, develop & implement tailored solutions in the own facilities.

Purpose of the event:
The idea of the event is to introduce three proven smart manufacturing solutions in a brief hands-on webinar to mid-size companies that are interested in quality & efficiency improvements in order to remain internationally competitive.

Each innovation provider will make an “application pitch” (15min) to present its technology & use cases and to explain on how to apply the solution to various manufacturing processes & set-ups.

The event is specifically tailored to manufacturing mid-sized companies that are NOT looking for a theoretical smart manufacturing session but for application & solution oriented input focused on the todays challenges in the manufacturing industry.

Date and timing:
January 28th, 2020 from 15.00-16.30

Timing Content
15.00 Reception & Housekeeping

15.15 Introduction of Acerta

15.30 Introduction of Lincode

15.45 Introduction of Atollogy

16.00 Break-out Sessions
Three independent, parallel Break-out Sessions to connect personally with each individual innovation provider

16.30 End of the event

Introduced innovation providers:

Acerta Analytica – Ontario, Canada (https://acerta.ca/ )
Summary: Evaluating & processing raw machine/equipment data (lines of codes generated e.g. by the production equipment) for proper decision making/quality & bottleneck forecasts.
Company Description: Provides an AI-powered automotive application intended to detect manufacturing defects in manufactured components and the assembly line.
The company’s application turns raw machine data into informed decisions by quickly diagnosing anomalies to discover critical problems in vehicles as well as offers valuable insights into vehicle performance, health and maintenance, enabling automobile companies to better understand their vehicle data by reducing the resources needed to detect faults.

Lincode – Menlo Park (CA) USA (https://lincode.ai/)
Summary: Artificial intelligence advanced web based visual surface defect inspection at the assembly line, with normal inexpensive 2D cameras.

Company Description: Lincode’s proprietary and patentable technology on AI, ML and IoT combined technology allows manufacturers to benefit from Industry 4.0 at scale.
Their visual inspection, action recognition and AI innovations automatically digitize various process inside the factory floor to save process time, augment resources, reduce returns and save loss.
Lincode’s existing clients have saved 25% on returns, 18% more savings on employee productivity.
Lincode combines an innovative approach on deployment techniques, using off the shelf hardware for computer vision, partnering with other industry solution providers to enable faster on deployments, quicker go to market cycle and fully integrated solution for the clients.

Atollogy Santa Clara (CA), USA (https://atollogy.com/ )

Summary: Artificial Intelligence / Internet of Things devices (cameras, sensors, etc.) monitoring equipment, people, processes and material & components flow to improve efficiency and security.

Company Description: Atollogy’s proprietary algorithms & capabilities are revolutionizing how physical operations are managed by integrating the physical world with artificial intelligence.
Our focus is helping companies enter the modern world of operations technology to drive improvements to their bottom line without enduring the pain, expense & process changes that are the hallmarks of classic enterprise systems.

Fees: None

The webinar will be in english.

Registration: Please send your name, company name and emailadress to info@fkg.se whit the subject “Smart manufacturing”.