Success Story video

Smart Factory Greenfield Planning at Saurer

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NEONEX not only helped us to shape the idea of our unique smart factory, but also supported us in developing the right concepts with the right technologies in the right way. Through this trustful collaboration, which lasted until the final implementation on the shop floor, we could reach our aim of establishing the most modern factory in the textile machinery sector.

Project approach

The project Saurer Intelligent Production focused a Smart Factory greenfield planning activity. The goal was to create one of the most modern and advanced factories in the textile machinery industry following the principles of process excellence, digitalization and Industrie 4.0. The project started with the development of a Smart Factory Vision, followed by the design of detailed concepts and mock ups for dedicated use cases and the definition of IT-Backbone-Systems (Micro Service Private Cloud Platform and MES) through to the selection of suppliers and the final implementation and rollout support.

Implemented Use Cases

The smart milkrun travels autonomously and provides material to single workstations via defined routes.
Use Case 1

Smart Milkrun

  • Automation
  • Intralogistics

Initial situation:

Transporting material in the factory is a non-value adding task.


Digital Solution:
Automation of logistics with a Smart Milkrun

Autonomous

No human driver needed.

Reliable

Delivery of the right materials to the right workstations at the right time.


Results:

Freed capacities

Employees in logistics can now work on value-adding tasks instead.

An Andon & Escalation Management System was set up to improve the Mean Time To Repair (MTTR).
Use Case 2

Andon and Escalation Management System

  • Andon
  • Shopfloor

Initial situation:

Deviations are not managed in a structured and monitored process, which makes KPI tracking and continuous improvement a challenge.


Digital solution:
System for ad-hoc deviation reporting and management

Mobile Reporting

Sending out requests for immediate support is possible via mobile devices. Moderation of the whole problem solving process within one system.

Searchable Knowledge base

Each deviation is classified and saved in a standardized way. KPI like Mean Time to Repair (MTTR) can be tracked precisely. A searchable Knowledge base about past incidents helps to handle future deviations more efficiently.


Results:

Reduced downtime

Decreased Mean Time to Repair (MTTR)

Increased productivity

The availability of information in real time allows informed and timely decisions.
Use Case 3

Performance Measurement System

  • KPIs
  • Automation

Initial situation:

Manual and paper-based collection of relevant data for KPIs takes a lot of time and resources. There are no standardized formulas for KPI Calculation between plants.


Digital solution:
Performance Measurement System for automated and standardized calculation of Key Performance Indicators

Automated

Calculation of global and local KPIs based upon standardized formulas

Globally accessible

Via any mobile device from inside and outside of the company network

User-Friendly

Structured and comprehensible visualization of KPIs

Real-time

Decision making based on actual data


Results:

More accurate and timely decisions

Shorter continuous improvement cycles

Remote support app to support local optimizations at the location in China through global expertise from the Saurer production network in real time.
Use Case 4

Remote Support System

  • Digital Communication
  • Support

Initial situation:

Bringing expert knowledge to remote locations and production facilities during the ramp-up phase of new machines or products is costly and time consuming.


Digital Solution:
Remote Support System

Communication via Live Chat

instead of face-to-face meetings or asynchronous e-mailing

Worldwide access

to Machine Data without actually being on site


Results:

Expert knowledge is available fastly available at any site at low cost

More efficient and affective problem solving

Improved production planning thanks to the provision of information on the condition, location and expected arrival time of individual shipments.
Use Case 5

Supply Chain Transparency

  • Supply Chain

Initial situation:

Arrival times of material and component shipments are not predictable and therefore production planning is difficult.


Digital solution:
Shipment tracking based on current status information

Monitoring each shipment:

location, status and estimated time of arrival

Combination of shipment information with order data from the ERP:

display of all relevant information in a uniform dashboard


Results:

Improved Production Planning

Increased On Time Delivery (OTD) for final products to end customers

Reduced Inventory Level