Skip to main content

RLW Navigator


The RLW Navigator aims to develop an innovative Process Navigator to configure, integrate, test and validate applications of remote laser welding (RLW) in automotive assembly addressing today’s critical need for frequently changing operating conditions and product-mix provisions. The RLW Navigator will serve as a crucial enabler for embedding new processes such as RLW for future energy efficient smart factories. RLW is emerging as a promising joining technology for sheet metal assembly, with benefits that include reduced processing time (50-75%), decreased factory floor footprint (50%), reduced environmental impact through reduced energy consumption (<60% including benefits related to process and product re-design), and a flexible process base for future model introduction or product changes. Currently, RLW systems are limited in their applicability due to an acute lack of systematic ICT-based simulation methodologies to navigate their efficient application in automotive manufacturing.

The project aims to address this by developing a Process Navigator simulation system that will deal with three key challenges thereby, allowing manufacturers to utilize the advantages of the RLW system: (i) the most critical obstacle that currently prevents the successful implementation of RLW is the need for tight dimensional control of part-to-part gap during joining operations, essentially to ensure quality of the stitch (WP3 & WP4); and, (ii) the existing assembly system architecture must be reconfigured to provide the opportunity to evaluate the RLW system in terms of its feasibility to perform all required assembly tasks (WP1). This will provide crucial information about the most advantageous workstation/cell reconfiguration, which will serve as the basis for optimal robot path planning to reduce joining process time and workstation level efficiency assessment (WP2); and finally, (iii) the project will develop systematic evaluation and learning methods to assess and improve the overall performance, cost-effectiveness and eco-efficiency of the RLW system (WP5 and all other WPs).


The Work-Package 1 is aimed at developing methodologies for the configuration of hybrid assembly systems, including Resistance Spot Welding (RSW) and Remote Laser Welding (RLW) processes. The overall objectives of WP1 are as follows:

  • Select candidate stations for the implementation of RLW and its performance specifications.
  • Evaluate the performance of hybrid assembly systems.
  • Configure the hybrid assembly system including RLW and RSW stations.
  • Perform sensitivity analysis enabling estimation of the robustness of the suggested system configuration.

The Work-Package 2 is aimed at developing methodologies for the configuration, offline programming, simulation, and evaluation of RLW assembly stations. The overall objectives of WP2 are as follows:

  • Develop methodologies for the design and configuration of RLW assembly workstations.
  • Generate off-line robot programs and simulate RLW processes.
  • Evaluate RLW workstation configurations (both static and dynamic).

The Work-Package 3 is aimed at developing methodologies for the error map generation, robust fixture optimisation for MAX and MIN gap control of multiple sheet metal parts and subassemblies, and RLW laser parameters selection and optimization. The overall objectives of WP3 are as follows:

  • Develop a quantitative model to characterise the different sources of error for RLW.
  • Develop a map of optimal laser parameters for different RLW working conditions.
  • Develop a methodology for robust fixture design for RLW of automotive sheet metal parts.

The Work-Package 4 is aimed at developing methodologies for the (i) root cause analysis (RCA) of faults during the RLW assembly process, (ii) corrective actions and preventive actions (CAPA) which aim at adjusting process (laser, or/and fixture; as well as PLC/events logs & process sequences) to eliminate 6-sigma failure occurring during production. The overall objectives of WP4 are as follows:

  • Develop a root cause analysis methodology for RLW.
  • Develop adjustment strategies to compensate for 6-sigma level faults in RLW assemblies.
  • Develop laser parameter adjustment system to compensate for output parameter deviation from performance profile-adaptive control.
  • Develop process adjustment to compensate for output parameter deviation from required performance profile – SPC control.
  • Develop event and process driven failure analysis methods in RLW.

The Work Package 5 aims:

  • To integrate the software modules (individual sub-processes) of all work packages.
  • To define eco-evaluation methods for automotive joining processes.
  • To conduct eco-evaluation of RLW processes and benchmark with other automotive joining processes (RSW and SPR).
  • To identify main factors (process parameters, materials, workstation configurations, etc.) that determine the eco-efficiency of the RLW process.
  • To develop a prediction model of RLW eco-efficiency.