L4MS

L4MS-Initiative (Logistics for Manufacturing SMEs)

L4MS-Initiative (Logistics for Manufacturing SMEs)

Launched on October 1, 2017, the L4MS [1] project (Logistics for Manufacturing SMEs) is funded by the European Commission and coordinated by the VTT Technical Research Center in Finland. This project focuses on fully digitizing intralogistics automation in factories. The aim is for suppliers of automation and logistics solutions to be able to develop and be up to ten times faster and more cost-effective than at current prices.

Need for improvement

In a typical factory, 25% of the workforce, 55% of the factory floor, and 87% of the production time are attributable to the transport of parts and components. While large manufacturers are rapidly using mobile robots to increase productivity and flexibility in the factory, less than 2% of European SMEs (small and medium sized enterprises) use advanced manufacturing technologies. For SMEs, which represent 98% of manufacturers, there is a danger that European industry will be left behind.

That is where L4MS comes in, enabling cost-effective, flexible and agile logistics automation in small batches, achieved through robotics and other advanced technologies such as artificial intelligence and virtualization.

OPIL - A comprehensive platform for Intralogistics

L4MS offers complete digitalization with OPIL (Open Platform for Innovation in Logistics [OPIL]) to enable cost-effective deployment of small and flexible logistics solutions. Other benefits include no infrastructure changes, no production downtime and no in-house know-how, making an investment in logistics automation for manufacturing SMEs extremely attractive.

Using OPIL and an external 3D simulation (with an example implementation of Visual Components®), highly autonomous, configurable and hybrid (human-robot) logistics solutions can be enabled.

With OPIL as the base technology for rapid experimentation and innovation on the market, existing and proven components can be easily updated, adapted or replaced with more advanced components as new technological inventions become available.

OPIL architecture [2]

The OPIL architecture consists of 3 layers: The top layer corresponds to the software system Layer; the middle layer comprises the cyber-physical middleware and the bottom layer the IoT agent nodes, consisting of humans, robots and sensors. 

 

Based on an NGSI v2 API [3] implementation, the Fiware Orion Context Broker [4] [5]  can be used to process context information (also called entities) using a REST API.

A big advantage is that the existing infrastructure can be used at a fraction of the current prices and can be procured as PaaS (Platform as a Service) and SaaS (Software as a Service) as needed.

Realization in three pilot experiments [6]

L4MS will benefit from 3 AEs (application experiments). For this, the requirements from the real world of experiments are used as input for the development of OPIL.

MURAPLAST [7] :
Muraplast is the leading producer of polyethylene blown film in Croatia and Southeastern Europe. Muraplast aims to optimize the process of picking up the products (rolls with PE film) from the production lines by using OPIL. The roles are to be transported to the storage area, weighed, while the information is transferred to the local ERP system. Optimization would increase production productivity, reduce the human error factor in measurements, and simplify the manual labor required to manipulate the products.

CHEMI-PHARM [8] :
The main business of Chemi-pharm is the manufacture and distribution of high quality disinfectants and cleaning products, mainly for the medical sector. Chemi-Pharm is currently developing its own IT system, which connects all departments, functions and processes. In many ways, this will provide the foundation for future automation in terms of knowledge, information and data management. It also helps reduce time spent on input to IT systems, reduces human error, and makes resource planning and use more efficient.

Engino [9]:
The Engino® Toy System helps students creatively and easily create technological models so they can experiment and learn in a fun way with science and technology. Due to the rapid growth of Engino, a lot of work force and time is currently needed to transport materials from one production area to another. However, this is not readily possible. The solution implemented with OPIL should support the workforce and make the process easier.

Challenges

In order to achieve the goals and to be able to realize the use of new technologies in SMEs, there are also some challenges to be overcame. These include the productivity challenge, a flexibility challenge, the investment challenge and the Skills & Competence Challenge.

In this context, L4MS aims to provide an integrated and pan-European ecosystem that will help address these challenges and unleash the innovation potential of manufacturing industries, especially SME and mid-cap companies, across Europe. As part of an accelerator program, the L4MS Marketplace will act as a one-stop-shop for manufacturing SME and collect a "catalog of services", which will then be offered by the L4MS network. These include competence centers, business accelerators, trainings and the other partners. The L4MS Marketplace connects medium and mid-cap companies with automation solution providers.

Open call for more industry applications

L4MS launches an Open Call [10] [11] for application experiments (AEs) to validate the cost-effective and rapid deployment of mobile robots in mid-sized manufacturing companies and mid-caps through virtualization (OPIL + Visual Components®). The experiments demonstrate the value of the solution to reduce installation, deployment, and configuration time and costs by a factor of ten. The AEs are performed using the OPIL integration platform and Visual Components®, which are provided with free licenses and complete instructions from L4MS.

 

[1] http://l4ms.eu/

[2] http://l4ms.eu/OPIL

[3] Fiware (2018) NGSI v2 Specification [Online] (Accessed 23. August 2018).

[4] https://fiware-orion.readthedocs.io/en/master/

[5] https://github.com/telefonicaid/fiware-orion

[6] http://l4ms.eu/Pilots

[7] https://muraplast.com/de/

[8] http://www.chemi-pharm.com/en/

[9] http://www.engino.com/w/

[10] http://l4ms.eu/Open-Calls

[11] https://l4ms-open-call.fundingbox.com/

 

Publications

 

1. Towards a Plug and Play Architecture for a Materialflow Handling System

    Authors: Peter Detzner; Tim Pose; Luca Fumagalli; Matteo Matteucci

    Conference: 2019 IEEE Conference on Open Systems (ICOS)

    Year: 2019 | Conference Paper | Publisher: IEEE

 

2. A Novel Task Language for Natural Interaction in Human-Robot Systems for Warehouse  Logistics

    Authors: Peter Detzner; Thomas Kirks; Jana Jost

    Conference: 2019 14th International Conference on Computer Science & Education (ICCSE)

    Year: 2019 | Conference Paper | Publisher: IEEE

 

3. Analysing FIWAREs Platform - Potential Improvements

    Authors: Peter Detzner; Peter Salhofer

    Conference: 53rd Hawaii International Conference on System Sciences (HICCS)

    Year: 2020

    At: Hawaii, USA

Insights into the 5th Consortium Meeting and the 2nd Review Meeting