IN
DEGREE PROJECT MECHANICAL ENGINEERING, SECOND CYCLE, 30 CREDITS
,
STOCKHOLM SWEDEN 2019
A Feasibility Study of an
Automated Repair Process using
Laser Metal Deposition (LMD) with
a Machine Integrated Component
Measuring Solution
FLORIAN SÄGER
KTH ROYAL INSTITUTE OF TECHNOLOGY
I
KTH – Royal Institute of Technology
Production Engineering and Management
A Feasibility Study of an
Automated Repair Process using Laser
Metal Deposition (LMD) with a Machine
Integrated Component Measuring Solution
Master Thesis (M.Sc.)
Florian Säger
Supervisor: Zhao Xiaoyu
Examiner: Amir Rashid
In Cooperation with
II Statement of Originality
I hereby confirm that I have written the accompanying thesis by myself, without con-tributions from any sources other than those cited in the text and acknowledgements. This applies also to all graphics, drawings, tables and images included in the thesis.
Stockholm, 22. August 2018
Florian Säger
I
Abstract (English)
The repair of worn or damaged components is becoming more attractive to manufac-turers, since it enables them to save resources, like raw material and energy. With that costs can be reduced, and profit can be maximised. When enabling the re-use of components, the lifetime of a component can be extended, which leads to improved sustainability measures. However, repair is not applied widely, mainly because costs of repairing are overreaching the costs of purchasing a new component.
One of the biggest expense factors of repairing a metal component is the labour-intense part of identifying and quantifying worn or damages areas with the use of various external measurement systems. An automated measuring process would re-duce application cost significantly and allow the applications to less cost intense component.
To automate the repair process, in a one-machine solution, it is prerequisite that a measuring device is included in the machine enclosure. For that, different measuring solutions are being assessed towards applicability on the “Trumpf TruLaser Cell 3000 Series”. A machine that uses the Laser Metal Deposition (LMD) technology to print, respectively weld, metal on a target surface.
After a theoretical analysis of different solutions, the most sufficient solution is being validated by applying to the machine. During the validation a surface models from a test-component is generated. The result is used to determine the capability of detect-ing worn areas by dodetect-ing an automated target-actual comparison with a specialised CAM program. By verifying the capability of detecting worn areas and executing a successful repair, the fundamentals of a fully automated repair process can be proven as possible in a one-machine solution.
Key Words:
Florian Säger
II
Abstrakt (Svenska)
Tillverkare har börjat se stora möjligheter i att reparera slitna eller skadade kompo-nenter som ett sätt att spara resurser, så som råmaterial och energi. Med den bespa-ringen minskar kostnaderna och vinsten kan således maximeras. Reparation möjlig-gör även återanvändning av komponenter, vilket förlänger komponentens livslängd och leder till förbättrade hållbarhetsåtgärder. Dock tillämpas reparation inte i någon stor utsträckning i nuläget, främst eftersom kostnaderna för reparation överstiger kostnaderna för att köpa en ny komponent.
En av de största kostnaderna för att reparera en metallkomponent är att identifiera och kvantifiera slitna eller skadade områden med hjälp av olika externa mätsystem, som är en väldigt arbetsintensiv process. En automatiserad mätprocess skulle minska avsökningskostnaden avsevärt och således reducera den totala kostnaden för kompo-nenten.
För att möjliggöra en automatiserad reparationsprocess i en enda maskinlösning är det en förutsättning att en mätanordning ingår i maskinhöljet. Därför har olika mät-ningslösningar utvärderats med avseende på användbarhet i "TRUMPF TruLaser Cell 3000 Series", vilket är en maskin som använder Laser Metall Deposition-teknik (LMD-teknik) för att skriva ut och svetsa metall på en definierad yta.
En teoretisk analys av olika lösningar har utförts, där den teoretiskt mest lämpliga lösningen validerades genom att appliceras till maskinen. Valideringen genererade en modell av ytan av en testkomponent. Sedan utfördes en automatiserad, målrelaterad jämförelse med ett specialiserat CAM-program baserat på modellresultatet, för att bestämma möjligheten att upptäcka slitna områden. Genom att verifiera förmågan att upptäcka slitna områden samt genomförandet av en lyckad reparation kan grunden för en helt automatiserad reparationsprocess bevisas som möjlig i en enda maskin-lösning.
Key ords:
Florian Säger
III
Abstrakt (Deutsch)
Das reparieren von abgenutzten oder beschädigten Komponenten wird immer attrak-tiver für Hersteller. Es ermöglicht es Ressourcen einzusparen wie beispielsweise Rohmaterial und Energie, was die Lebenszeit einer Komponente verlängert und da-mit die Nachhaltigkeit verbessert.
Allerdings ist Reparieren nach wie vor nicht weit verbreitet, hauptsächlich dadurch bedingt, dass die Reparaturkosten die Kosten für eine neue Komponente übersteigen.
Einer der größten Kostenfaktoren des reparieren einer Metallkomponente ist der Ar-beitsintensive Teil der Identifizierung und Quantifizierung des abgenutzten oder be-schädigten Bereichs mit verschiedensten externen Vermessung Systemen. Ein auto-matisierter Vermessungsprozess würde die Kosten signifikant reduzieren und neue Applikationen ermöglichen.
Das automatisieren der gesamte Prozesskette – in einer Single-Maschinenlösung – erfordert, dass eine Messeinrichtung im Bearbeitungsraum der Maschine angebracht wird. Dafür werden verschiedene Lösungen nach Anwendbarkeit an der Trumpf La-ser Cell 3000 Serie hin beurteilt. Eine Maschine, welche LaLa-ser Metal Deposition (LMD) als Technologie anwendet um Material auf Oberflächen aufzubringen.
Nach einer theoretischen Analyse verschiedener Lösungen wird die beste Lösung va durch anbringen an die Maschine validiert. Bei der Validierung wird ein Oberflä-chenmodel erzeugt. Das Ergebnis wird dann genutzt um die Fähigkeit zu belegen, dass beschädigte Stellen, durch einen Soll-Ist-Vergleich in einem speziellen CAM Programm, automatisch detektiert werden können. Basierend auf diesem Beleg und mit dem Ergebnis eine Komponente erfolgreich reparieren zu können, gilt die These eines automatisierten Reparaturprozesses in einer Single-Maschinenlösung als be-weisen.
Stichwörter:
Florian Säger
IV
Acknowledgment
I would like to credit some persons in particular, who helped me to accomplish this thesis in this way.
First of all, my supervisor at Trumpf in Sweden Hubert Wilbs, who gave me the opportunity to execute this project at his company and supported me with all needed resources and gave continues productive feedback when needed.
Sebastian Kaufmann, my supervisor at Trumpf in Germany who supported me
greatly with ideas and the right questions. He was also the one who made it possible that the solution could be validate on the machine. He further gathered experts in their filed in order to realise the test over the full process chain.
Further I would like to accredit Amir Rashid, my examiner at KTH who was inter-ested in this project from minute one and was in contact with me during the entire project to make the best outcome possible for this project. In the same way I would like to mention Xiaoyu Zhao, my supervisor at KTH. She ensured at all times that I am on the right track and I have all the information needed to make this thesis suc-cessful.
Another thank you is dedicated to the CAM expert Christian Walter from “Netvision
Datentechnik GmbH u. Co. KG”, who substantial contributed to the success with his knowledge and support during the validation and the post-calculation of the generat-ed CAM models. Without him the reverse engineering and with that, the entire vali-dation process wouldn’t have been possible.
In addition to that I would like to mention Lars Östergren form GKN Aerospace Sweden AB, who – as an important customer from Trump – enabled me to see how the LMD process is applied to real cases. He further made it possible for me to attend a CAM course.
Furthermore, I would like to mention Anna Bolay who helped me with all questions in the company and assistant greatly to the success of this thesis and even more im-portant made this thesis possible. She got me in contact with Mr. Wilbs after ap-proaching her with my idea. The same help was at all times made possible by Karin
Gustafsson, she ensured that I had all the information needed form the company to
accomplish this thesis work.
A truly unique “thank you” is dedicated to my family and my girlfriend. Thank you for the unlimited support along the entire way, I am grateful for your boundless en-couragement.
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Table of Content
I. List of Figures... VII
II. List of Tables ... IX
List of Abbreviations ... X
1 Introduction ... 1
1.1 Aim of this Thesis ... 2
1.2 Motivation for Optimising the Measuring Process ... 3
1.3 Structure of the Thesis ... 5
1.4 Research Question ... 6
1.5 Scope and Definition of the Thesis ... 7
1.6 Goal of the Thesis ... 7
1.7 The Company Trumpf ... 7
1.7.1 The Additive Manufacturing Products from Trumpf ... 9
2 Theory ... 11
2.1 Additive Manufacturing Processes ... 11
2.2 The Laser Metal Deposition (LMD) Process ... 12
2.2.1 Main Application Fields of LMD ... 15
2.3 The Repair Process using LMD ... 16
2.3.1 The Current Process of Repairing Components using LMD ... 17
2.3.2 The Future Process of Repairing ... 20
2.4 Sensor Systems for Surface Measurement ... 22
3 Methodology to Evaluate Feasible Measuring Solutions ... 26
3.1 Qualitative Assessment of the Measuring Solutions ... 28
3.2 Quantitative Evaluating of the Measuring Solutions ... 29
4 Analysis of Most Suitable Measuring Solutions for the Application ... 33
4.1 Possible Solution 1: Laser Line Sensor from Micro-Epsilon “LLT 2900-100” ... 33
4.2 Possible Solution 2: Laser Line Sensor from LMI Technologies “Gocator 2440” ... 38
4.3 Possible Solution 3: Stereo Camera from GOM “ATOS Core 200” ... 42
4.4 Result of Measuring Solution Analysis ... 46
VI
5.1 Validation Setup and used Equipment ... 49
5.2 The Validation Procedure ... 51
5.3 Validation Results ... 53
6 Identification of Future Work Packages based on Validation ... 54
7 Conclusion of the Work ... 56
III. References ... 58
VII
I. List of Figures
Figure 1 - The current and future LMD repair process in a simplified version. Showing the improvement aims, where blue colour represents process steps involving mainly manual work and green colour
representing automated process steps. ... 2 Figure 2 - Overview of the thesis structure in a flow diagram... 5 Figure 3 - Trumpf Logo. Source: (Trumpf Media Server 2018)... 8 Figure 4 - LMF process, where the laser currently melts a metal powder layer.
Source: (Trumpf Media Server 2018) ... 9 Figure 5 - The LMD process in action, here the nozzle can be seen during
processing metal powder onto a spinning metal disc. Source:
(Trumpf Media Server 2018) ... 10 Figure 6 – The nozzle of the LMD while the process is in work. The laser melts
the surface of the target and adds powder into the melt pool. The process is shileded by shiled gas. Source: (Petrat, Graf, Gumenyuk,
& Rethmeier, 2016, p. 762) ... 12 Figure 7 – A macro caption of the nozzle with active powder feed. (1) indicates
the intersection of the powder outlets and the focus of the laser beam. This also defines the working distance to the target (D).
Source: (TRUMPF 2018c) ... 13 Figure 8 - The LMD nozzle Trumpf uses in golden/bronze colour. The
mechanics seen above are the optics for the laser focus and process
surveience. Source: (TRUMPF 2018c) ... 14 Figure 9 - The Trumpf TruLaser Cell 3000 Series. Source: (Trumpf Media
Server 2018) ... 15 Figure 10 - LMD process while working, done on a shaft (used as base material)
to create a helix. Further in golden colour the nozzle can be seen.
Source: (Trumpf Media Server 2018) ... 16 Figure 11 – Taxonomy of measuring principles ordered according to their
physical technique used. Own graphic, based on (Bellocchio,
Borghese, Ferrari, & Piuri, 2013, p. 21) ... 23 Figure 12 - PDCA (Plan-Do-Check-Act)-Cycle for Sensor Assessment ... 26 Figure 13 – A graphical representation of the methodology applied, to assess the
best measuring system. ... 27 Figure 14 - Micro-Epsilon laser line sensor. Source: (Micro Epsilon - Datasheet
2018, p. 3) ... 33 Figure 15 - Radar Chart for solution 1: The result of the Micro-Epsilon laser line
sensor shown in a graphical way, for all eight rated factors. ... 36 Figure 16 - LMI Gocator 2440 laser line sensor. Source: (LMI Gocator
Technical Specification 2018, p. 1) ... 38 Figure 17 - Radar Chart for solution 2: The result of the LMI laser line sensor
VIII
Figure 18 - GOM ATOS Core 200 sensor mounted on a tripod, with illustrated components being measured on the left side. Source: (GOM ATOS
Core Homepage 2018) ... 42 Figure 19 - Radar Chart for solution 3: The result of the GOM stereo camera
shown in a graphical way, for all eight rated factors. ... 44 Figure 20 - Overlay of all three rated solutions in one radar chart, ... 46 Figure 21 - The setup as used for the tests of the sensor. The sensor can be seen
attached to the machine head and connected to the computer. ... 49 Figure 22 - Three types of the demonstration parts used for the test. All made of
sheet metal and stapled together with welding spots, used for the validation. Left to right: 1) clear part, 2) LMD coated part
crosswise to the sheet metal layers, 3) chalk sprayed clear part ... 50 Figure 23 - Close caption of the sensor next to the machine head, mounted with
the magnetic arm. ... 51 Figure 24 - The result of scan number 17, viewed in Scan Control 3D Viewer
3.1. ... 52 Figure 25 - Blind spots during the measurements, as the angle towards the sensor
gets greater then 180 degrees. ... 52 Figure 26 - The scanned data imported to the ADEM CAM software (in green),
IX
II. List of Tables
Table 1 - Extract of the product portfolio of Trumpf (TRUMPF 2018d) ... 8 Table 2 - Detailed Process Steps of the process step as carried out at some
Trumpf customers (Source: In a less detailed version, form a
customer of Trumpf in Sweden, which wants to stay anonymous) ... 18 Table 3 - Rating and the respective justifications for each factor, to compare
possible solutions ... 30 Table 4 - Rating of Solution 1: Laser Line Sensor “LLT 2900-100” from
Micro-Epsilon ... 34 Table 5 - Rating of Solution 2: Laser Line Sensor "Gocator 2440" from LMI
X
List of Abbreviations
LMD Laser Metal Deposition LMF Laser Metal Fusion PLC Product Life Cycle GHG Greenhouse gases AM Additive Manufacturing CAD Computer-aided Design
CAM Computer-aided manufacturing NC Numerical Code
USP Unique Selling Proposition CMM Coordinate-Measruing Machine RQ Research Question
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1
Introduction
This thesis project was carried out together with Trumpf Maskin AB, who provided this pro-ject and all related equipment. The question under research arose from customer requests as well as by identifying market niches, who addressed this problem and the opportunity of sell-ing such product, to Trumpf.
The project deals with the additive manufacturing (AM) process “Laser Metal Deposition” (LMD), which can – among other application – be used to repair metal components. Worn or damaged surface areas and missing or destroyed features can be additively re-manufactured. This repairing option results ideally in a re-use of the component, which leads to an extension of the Product’s Life Cycle (PLC), respectively the use-phase of it. With that also the re-sources can be reduced, such as energy and material but also monetary assets. (Gao et al., 2015, p. 79)
In most cases, however, the overall costs of repairing are component are higher than the costs of a newly built part, due to the high costs of the repair process. It is a time-intense process which requires high investments into machinery and auxiliaries, investment in knowledge-building as well as a high demand of labour in several steps of the repairing phase (Zheng, Li, & Chen, 2006, p. 1062). To lower the cost of applying the LMD to repair components, the whole process chain of the repair needs to be examined to identify cost drivers and eliminate them.
As a main driver for costs, especially in labour expensive countries in Europe, labour can be identified among others in the forefront. That can be significantly reduced or even eliminated by applying concepts of automation to the process. As a result, the part repair is cheaper and can be applied profitable to other components.
It will further enable the digitalisation of the process over the full process chain, which opens the way for Industry 4.0. By storing the measurement data, quality control can be applied based on historical data and conclusions can be made by interpret the measurements.
As mentioned, the complete LMD repair process will be examined to identify improvement areas in terms of lowering costs of application. However, this thesis will focus on the en-hancement and automation of the measuring process. It evaluates the feasibility of applying such an automated measuring process to the Trumpf TruLaser Cell 3000 Series.
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1.1 Aim of this Thesis
The aim of the thesis work is to find a solution which allows to measure parts in three-dimensional space within the machine enclosure of the Trumpf TruLaser Cell 3000 Series. Adding a partly or fully automated measuring device to the machine, the repair process using Laser Metal Deposition (LMD) can be significantly simplified. That, in the context of the process chain of repairing a part, will reduce the cost of application by reducing throughput time, manual labour and investment in further measuring products.
Next to the reduced costs of application and simplification of the process, the automation en-ables for example a one-piece flow, where each part can be unique in its’ repair requirements. Additionally, another scan of the part in the post-process can be used to validate the repaired area and increase the quality assurance by allowing to analyse the result.
With a fully automated repair process using LMD, Trumpf would inaugurate a unique selling proposition (USP) to the market, since there is no similar product on the market today.
New customers can be reached which do not have other possibilities to measure a part in or-der to define areas for repair.
Figure 1 shows the repair process in a flow diagram, where blue colour indicates steps which mainly involve manual work and green mainly automated processes. The full process chain and its analysis can be found in section 2.3 “The Repair Process using LMD”.
Figure 1 - The current and future LMD repair process in a simplified version. Showing the im-provement aims, where blue colour represents process steps involving mainly manual work and
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Automation requires, to begin with a suitable measurement process which can be integrated into the machine environment. To this direction a solution shall be researched and combined with experimental work will contribute to ideally carrying out first trial measurements during this thesis project.
Based on that evaluation, first achievements can be mentioned and more important: future challenges can be identified and pointed out. This will overall clarify if such an application is feasible to develop. Further, it identifies the amount of resources needed to develop the pro-cess fully towards an automated solution at Trumpf.
It also demonstrates the ratio of the possibilities with the chosen measurement system or de-vice.
Summing up, the aim of the project and thus a strategic goal of Trumpf, is to offer a “one-machine” solution to its’ customers, with which a fully automated repair process can be car-ried out to almost any metal component.
1.2 Motivation for Optimising the Measuring Process
It is known that the use of material and energy resources on earth needs to decrease to ensure that the emissions of Greenhouse Gases (GHG), the main contributors to climate change, are reduced significantly in order to cap global warming. One of many technologies in industry, which seems to be a promising step towards decreasing these GHG, and the carbon footprint could be Additive Manufacturing (AM). That, together with other advantages AM has over classical machining processes, lead to an enormous trend in growth of this technology.
It is, however, controversially discussed if AM has the power to become the next industrial revolution, since it could be a game changer for the whole industry on how to manufacture components. Printed functional assemblies and whole products are possible to print directly from digital data.
Some studies have already researched the potential of LMD to reduce the carbon footprint and came up with the conclusion that the application of it to repair, can reduce the carbon foot-print and the material used the whole PLC : Morrow, Qi, Kim, Mazumder, and Skerlos (2007, p. 933) and Serres, Tidu, Sankare, and Hlawka (2011, p. 1123).
In addition to that, repairing of components is always a less resource intense process, since it focuses just on damaged areas not on creating an entire new part. A greener manufacturing environment could thus be enabled with this technology. (Liu et al., 2016, p. 1027)
Trumpf, does highly believe in the technology and AM and invests greatly into the develop-ment. Besides other solutions offered, one application of the technology is the repairing of metal components with Laser Metal Deposition. Where until today, the machine is mainly used to print, the rest of the repair process chain (measuring, quality control…) is done in other – external – machines.
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Trumpf can create a USP to its customers by offering an automated repair process, which can be executed on many metal parts without human interaction.
The cheaper repair could allow the application on cheaper components, where it was until now not cost efficient to apply a repair with LMD, because a newly built part was cheaper and less time intense to build.
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1.3 Structure of the Thesis
Figure 2 shows the structure of the thesis in a process diagram. The main parts are namely: introduction, theory, market survey & analysis and the validation are building the core of the work. Followed by the result of the work where all findings will be summarised briefly and in the next chapter discussed. In the “future work” paragraph, the results are being interpreted, and found challenges are being pointed out. Hence, further work steps can be derived from that, in order to perceive the magnitude of a future development project.
After introducing the project and its aim the whole process chain used to repair a component with the LMD process is described as it is carried out from some of Trumpf customers. Based on that, areas of improvement can be identified.
Based on these improvement areas, this thesis with its research questions can be derived. To-gether with the scope of the thesis work is clearly defined within given boundaries.
Introduction •Project introduction •Goal definition •Research Questions (RQ) Theory •State of the Technology •Measureing Systems Applied Methodo-logy •Sensor assessment •Comparison Validation •Experimental work •Result of Validation Future Work Discussion Result of Work
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The introduction will be finished with a brief explanation of the company Trumpf and their offered products. Followed by the theory regarding different available measuring and sensor systems, which could be applied to the stated engineering problem in this thesis.
The following chapter “Methodology to Evaluate ” outlines the methodology which was used to find the best suitable solution of sensor, which was then used together with the machine in order to measure parts within the machine enclosure. Here also the evaluated
1.4 Research Question
The overall strategic goal of Trumpf is to develop a process, which decreases the labour hours needed for process and likewise the human interaction with the process. This will result in a more automated and thus, user-friendlier application and equally important it would also de-crease the overall costs, as mentioned in the previous chapter.
The result: cheaper repair costs per component for the user, which will make the LMD and its machine more appealing to customers to purchase from Trumpf, with this USP. Since, Trumpf will be one of the first companies offering a “plug and play” (to a certain extend!) solution, to repair metal parts using the LMD process.
However, until today it is not defined what are the specifications and needs to develop such a solution, and accordingly, what challenges need to be faced.
Which is a reason why this thesis was set up: To research the feasibility of automating the
repair process. In this thesis in particular, focusing on the part of measuring compo-nents within the machine enclosure.
The research question(‘s) (RQ) this thesis aims to answer are the following ones:
RQ 1: Is it feasible to integrate a sensor system into the enclosure of the Trumpf TruLaser
Cell 3000 Series machine, to measure metal parts fully automated and detect worn/defect areas on them to use the machines’ LMD process to repair mentioned areas?
From this, sub-questions arise:
RQ 1.1: What will be the best measuring system for this purpose?
RQ1.2: What are biggest challenges to face when developing this solution entirely?
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1.5 Scope and Definition of the Thesis
The scope of the project at Trumpf initially was to create a ready-to-use “product”, which is capable to carry out a fully automated repair process, over the whole process chain. The rough idea was, to attach a measuring sensor to the machine and with some changes to the machine- and CAM software, repair components fully automated.
However, after formulating a first project draft and getting in contact with professors and ex-perienced engineers, it became clear that the scope for this thesis has to be narrowed down from these expectations.
Together with the KTH supervisor, Xiaoyu Zaho and in communication with the responsible persons from Trumpf, it was agreed to focus on finding a sensor system which then sets grounds for a complete process automation in a future development project.
Upon that, it was also agreed that a validation of the researched system will be carried out on a Trumpf TruLaser Cell 3000, in order to prove that correct measurements can be derived from the chosen system.
Based on both, the research for the best suitable sensor type and system and the executed val-idation with the chosen system, recommendation for sensory type or system can be given and future work packages can be suggested.
1.6 Goal of the Thesis
By lowering and reducing:
1) the overall costs of the process
replace (usually used) external measuring devices 2) the complexity of the process
abrogate the change of machines
adopt automatically to different components
simplify process (for end-user) to abrogate special knowledge
compare scan and original file automatically to identify worn areas 3) the time consumption of repairing overall
a) reduce of the throughput time 4) the manual work during the repair process
b) automate the process to best extend
The goal is to provide a sensor recommendation for Trumpf, which enables to measure parts of different sizes in the machine area of the Trumpf TruLaser Cell 3000. Further, the “one solution” shall be chosen and be validated towards the ability to create a point cloud of a component. The point cloud shall have a resolution, high enough, to ensure that worn areas on the component can be identified in a sufficient quality. This will be validated with tests and the CAM software of Net-Vision called ADEM, where path generation for repair needs to be successfully done.
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Trumpf is a family-owned-and-operated company with the headquarters in Ditzingen near Stuttgart in Germany. Besides the subsidiary Trumpf Maskin AB in Sweden, where this thesis was carried out, it has more than 70 further subsidiaries in the whole world, to provide all products, solution and services in close proximity to all their customers over the world. In addition, Trumpf is one of the world’s biggest providers of machines tools, with production facilities in Germany, China, France, Japan, Mexico, Switzerland and USA. (TRUMPF 2018b)
Trumpf is a high-tech company offering manufacturing solutions in seven different fields. Below, these mentioned fields and their core products are listed. However, this is just an ex-tract of the portfolio of Trumpf in total more variants of products and specialised solutions are offered to customers all over the world. (TRUMPF 2018d):
Table 1 - Extract of the product portfolio of Trumpf (TRUMPF 2018d)
- Machines & Systems
- Laser cutting machines - 3D laser cutting
- Laser welding machines - Marking systems - 3D printing systems - Punching machines - Bending machines - Automation - Lasers - Disk laser - Diode laser - Fiber laser - CO2 laser - Scientific laser - Power Electronics - Power Tools - Shear cutter - Seem locker - Drill driver - Smart Factory - Machine connections - Optimization - Software
- Specialised CAM software - Monitoring applications
- Services
- Financial service - Technical service
- Individual solution planning - Energy Storage Systems
9 - Induction Generators
Trumpf was founded in 1923, when Christian Trumpf together with two other persons ac-quired a company called “Julius Geiger GmbH”, which was located in Stuttgart, Germany. From that point onwards, the company evolved statically and has today as a yearly revenue of 3,11 billion € (2016/17) and 11.883 employees world-wide. (TRUMPF 2017) 1
Preliminary figures from a press release of 19.07.2018 even show an increase in sales to 3,6 billion € (2017/18), which is an increase by 15 % (TRUMPF 2018a).
Trumpf Maskin AB in Alingsås, Sweden is a subsidiary of Trumpf GmbH + Co. KG with its headquarters in Ditzingen, Germany.
The main function of the subsidiary in Sweden is to offer products and solutions from the Trumpf portfolio to customers in all the Nordic countries. Thus, Trumpf in Alingsås is re-sponsible for the markets in Sweden, Denmark (here only for lasers products), Iceland and Norway and Finland. Further the service business is offered to all its customers to ensure the highest availability of all machines and the best maintenance possible.
1.7.1 The Additive Manufacturing Products from Trumpf
Besides the mentioned products (see section 1.7) that Trumpf offers, the portfolio includes also products belonging to the category of additive manufacturing (AM)
Trumpf has – until today – two different machine types for AM in the portfolio: 1. Laser Metal Fusion (LMF)
This process uses a laser as energy source to melt metal powder in a bed, on desired points. Layer by layer metal powder is added and melted to form the part according to the CAD model.
The process belongs to the group of Powder Bed Fusion processes and is also referred to as: Selective Laser Melting, Selective Laser Sintering, Direct Metal Laser Sintering. The following picture illustrates the process.
1
Data form company report, as referenced, 16/17 with reporting date from 30. June 2017.
10 2. Laser Metal Deposition (LMD)
This process is among other applications, used to repair metal parts. It is further the process which is used in this thesis project and will thus be explained in detail in the following sub-section.
The process is also referred to as: Direct Laser Deposition, Direct Energy Deposition, Laser Cladding
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2
Theory
In this chapter the fundamental principles for this thesis work are mentioned and explained. The chapter is divided into four sections. The first part mentioned, and brief explained the different additive manufacturing (AM) methods. In the second section, the theory for the La-ser Metal Deposition (LMD) process itself is explained. The third section of this chapter ex-plains the repair process of metal parts, using the LMD process as it is applied by Trumpf customers. The last section focuses on measurement systems, here the applicable measuring techniques for measuring components in the machine enclosure are enumerated and elaborat-ed with their work principles.
2.1 Additive Manufacturing Processes
Additive Manufacturing Processes are being developed rapidly and thus new branding names are developed in the same pace, to differentiate the own product from the competitors. Never-theless, according to ASTM F2792 standard, all the AM processes unrelated to their marked and branded name can be distinguished between seven categories or families. The American Society for Testing and Materials (ASTM) shows so, in their standard “ASTM F2792. The seven families and the short description to each, according to ASTMInternational (2015; Standard Terminology for Additive Manufacturing Technologies) are listed below.
1) VAT Photopolymerization
A vat of liquid photopolymer resin is cured through selective exposure to light (via a laser or projector) which then initiates polymerization and coverts to exposed areas to a solid part.
2) Powder Bed Fusion (PBF)
Powdered materials are selectively consolidated by melting it together using a heat source such as a laser or elector beam. The powder surrounding the consolidated part acts as support material for overhanging features.
3) Binder Jetting
Liquid bonding agents are selectively applied onto thin layers of powdered material to build up layer by layer. The binders include organic and inorganic materials. Metal or ceramic powdered parts are typically fired in a furnace after they are printed.
4) Material Jetting
Droplets of material are deposited layer by layer to make parts. Common varieties in-clude jetting a photocurable resin and curing it with UV light, as well as jetting ther-mally molten materials that then solidify in ambient temperatures.
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Sheets of material are stacked and laminated together to form an object. The lamina-tion method can be adhesives chemical or similar. Unneeded regions are cut out layer by layer and removed after the object is built.
6) Material Extrusion
Material is extruded trough a nozzle in tracks or beads, which are often combined into multi-level layer models. Common varieties include heated thermoplastic extrusion, similar to a hot glue gun.
7) Directed Energy Deposition (DED)
Powder or wire is fed into a melt pool which has been generated on the surface of the part where it adheres to the underlying part of the layers by using an energy source such as a laser or elector beam.
8) Hybrid Processes
For example, laser metal deposition is combined with CNC machining, which allows additive manufacturing and subtractive machining to be performed in a single ma-chine, so that parts can utilize the strength of both processes.
2.2 The Laser Metal Deposition (LMD) Process
Laser Metal Deposition (LMD) is an Additive Manufacturing (AM) technology, however just one of many.
It belongs to the class of direct energy deposition AM technologies (Mahamood, 2018, p. 4). As the name indicated the process uses laser as the energy source to melt the raw material, which either is fed as powder (as used by Trumpf) or as a wire.
On the target the laser fuses the surface of the component and at the same time shots metal powder into this melt pool. The powder particles are being melted as well as they reach the melt pool. When the powder impinges onto the melt pool, the two materials (ground material and powder) are permanently bonded together in a metallurgical way. As the laser passes, the area solidifies again, since heat was just applied in a focused zone on the surface. The follow-ing graph illustrates this in a schematic way. (Mahamood, 2018)
Figure 6 – The nozzle of the LMD while the process is in work. The laser melts the surface of the target and adds powder into the melt pool. The process is shileded by shiled gas. Source:
(Petrat, Graf, Gumenyuk, & Rethmeier, 2016, p. 762)
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The illustration further indicates how the two process gases are used with LMD.
The shield or nozzle gas indicated in the picture in light blue is commonly argon. Its main purpose is to shield the target, in particular the molten pool to prevent the area from oxidation. The other, referred to as carrier gas (usually helium), is used to transport the powder from the powder container to the nozzle and the target area. With a change of the flow rate [l/m] the amount of powder transported from the container to the target can be adjusted. (TRUMPF 2018c, pp. 2-2)
The nozzle has a specific focus point, indicated by the (1) in Figure 7. Here, the powder from the different outlets meets and intersects with the laser focus. It defines also the working dis-tance to the target, so-called (D).
Technical specifications of the process, according to: (TRUMPF 2018c)
Nozzles available:
o Three-beam nozzle (usually: 3D processing) used for coating with different specifications available:
Powder focus diameter 2,5 – 4,0 mm Target distance approx.: 12 – 16 mm
o Coaxial nozzle (usually: 2D processing) with specification ranges: Powder focus diameter: 1 mm
Target distance approx.: 7 mm
Feed
The feed can basically be freely chosen and defines the thickness of the process. Less feed will add more material to a certain point and thus result in a thinner layer of ma-terial added and vis versa. It is however limited to the physical boundaries, where the powder will leave the focus due to the indolence of the metal powder.
Figure 7 – A macro caption of the nozzle with active powder feed. (1) indicates the intersec-tion of the powder outlets and the focus of the laser beam. This also defines the working
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Materials
Almost any metal, in form of powder can be processed. Alloys and a mix of different metal powders in the head are possible as well.
Gas used in the process
Carrier gas is commonly helium
Nozzle gas (also known as shield gas), commonly argon
The nozzle that Trumpf uses can be seen in Figure 8. It is indicated in golden/bronze colour, the mechanics above are the laser optics.
The basic principle of the process is thus very similar – and also related – to the welding pro-cess. Which is also why this technology can be called "Laser Cladding". Other names are: "Direct Energy Deposition". (ASTM International (Standard F2792-12a) 2015)
Depending on the application purpose and the material which will be manufactured, Trumpf offers a variety of laser sources (disk laser, CO2 laser, fiber laser,…) to its customers, special-ly customized to the specific requests.
The machine tool used for this thesis project is the Trumpf TruLaser Cell 3000. It is a univer-sal 3D multi-machine tool from Trumpf with which laser cutting and welding can be per-formed as well as the mentioned Laser Metal Deposition process can be executed. The ma-chine can be seen in Figure 9. To do so, some peripheries needs to be added to the mama-chine environment, such as the metal powder feeder (also called powder conveyor) and the process nozzle for the LMD, available in a coaxial or three-beam variant. The details of the LMD pro-cess however will be explained in sub-section 2.3 “The Repair Propro-cess using LMD”.
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The LMD process can be ordered from Trumpf with the "TruLaser Cell 3000" and "TruLaser Cell 7000" and also with the robot-based "TruLaser Weld" system. Further, a so-called OEM package can be ordered from Trumpf, which makes it possible to add the LMD externalities to other laser-based machines, to perform LMD. The package includes the powder feeder unit and the nozzle head.
2.2.1 Main Application Fields of LMD
The LMD technology has several application fields, from which four main categories can be identified:
1. Repairing
Mainly expensive parts where wear, changes or defects occur. Further many custom-ers use the TruLaser Cell 3000 and 7000 to coat surfaces. The repair function of the LMD is used for expensive part for the bare fact that the process itself is costly due to two factors.
First, the machine is a high-end precision machine due to precise measuring internals Further, the process for repair involves a lot of pre- and post-processing for compo-nents. Here comes the critical part in: This involves a lot of manual work which makes the process expensive for users. Especially in high-salary countries like Sweden. The entire process of repairing is shown and explained in sub-section 2.3.1.
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2. Coating
The coating of surfaces or parts of a component is another common application. Espe-cially when special requirements are needed, such as hardness, heat resistance or pure aesthetic needs this can be a good solution.
3. Joining and local material adding
Where complex and thin parts with gaps need to be welded together this process can be applied. With its precision and the readability, the process can in combination with an automated feeding also be added into a serial production
4. Part generation
It can also be used for part generation in general, where the whole component is creat-ed. Here the commonly referred layer manufacturing applies, where the part is created by 2D layer "printing" and the third dimension is added by moving stepwise in Z-direction upwards.
2.3 The Repair Process using LMD
The repair process, using the LMD, can be described in the same way the LMD is used for creating parts. The difference is the specific purpose of its use and the area where material is added, which is limited to worn or destroyed areas of a component. Correspondingly, this means that the printing is executed on the component itself and not a usually used base plate. The process during execution is illustrated in Figure 10.
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In the following two sub-sections the repair process is explained in more in detail. First the process is explained as it is applied at Trumpf customers today. The second sub-section, start-ing on page 20, is dedicated to the future repair process. Here the future process is explained as it shall be developed. It includes the preferences of customers and the expertise of several Trumpf engineers.
2.3.1 The Current Process of Repairing Components using LMD
In this sub-section the repair process is explained, as customers of Trumpf are using them today to repair parts. This is also how Trumpf executes the process according to internal doc-uments.
Since this thesis requires a holistic view on the process to ensure an integrated solution devel-opment, detailed data related to process parameters or setup parameters are not mentioned.
Initiating the LMD process, a quick overview
Three important LMD process parameters, which vary according to used materials and appli-cation use, are:
1. feed (machine head) [Millimetres/Minute], 2. laser energy [Watts] and
3. feed rate (powder supply)
Depending on the feeder: [% of max. amplitude] or [revolutions/minute].
Until today, there is no table of parameters available were process parameters can be looked up according to used material, feed etc. Consequently, most of the machining parameters de-pend on the experience of the user and are researched together with the customer for each application. Trumpf and its sub-suppliers are currently working on creating such a process parameter table, to overcome this boundary for the customers and users.
When the mentioned process parameters and all other necessary parameters are set, the nozzle is placed near the ventilation flue, behind the working area, on the bottom of the machine, so that the powder flow can be filtered after exiting the nozzle.
The pre-flow of metal powder is done to ensure a continues and stable supply of powder. Due to a very varying powder supply at the first few seconds, due to powder still in the pipes when the carrier gas was shut off after the last use. The run-up for this takes about 10-30 seconds.
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The process steps of repairing with LMD
In the following table the LMD repair process is shown in a stepwise order. It represents the process as it was expressed to the writer from Trumpf. The users of the process are several customers using the LMD to repair parts, which want to stay anonymous.
In the left column of Table 2, the steps can be seen as they are carried out in a sequence. In some cases, different attempts are possible, which then is shown in the right column in the alternative steps, with the respective alternative process step number.
The working steps which involve manual work or partly manual work, are marked in blue colour in the table 2.
Table 2 - Detailed Process Steps of the process step as carried out at some Trumpf customers (Source: In a less detailed version, form a customer of Trumpf in Sweden, which wants to stay anonymous)
Process Steps Alternative Process Step
1. Place component onto measuring ta-ble
a. Secure component 2. Execute measuring
a. Find measuring program b. Execute measuring program
automatic or manual 3. Create 3D-point cloud
a. Stitching of a 3D point cloud out of several scans
b. Feasible export format needs to be found
4. Generate surface model
a. Generate a meshed surface model
5. Import files
a. Find original CAD file from component
b. Load both: scanned model and original CAD model 6. Extract delta
a. Locate worn areas/missing features
7. Set printing strategy
a. Slice delta areas for print b. Find print method (circle,
zigzag,...)
2. Execute measuring
a. Create measuring program b. Validate measuring program c. Execute measuring program
automatic or manual 3. Create 3D point cloud
a. Point need to be exported in-to CAD/CAM
b. Point cloud need to be
stitched together from several measuring turns to a con-sistent 3D cloud manually 4. Generate surface model
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8. Prepare part on LMD machine a. Move part to LMD machine b. Secure part on part-holder c. Find reference point to print
defined areas 9. Prepare print
a. Load print
b. Check program on dry run manually to avoid e.g. colli-sions
10. Execute print
a. Print missing features 11. Post print
a. Check success of print b. Move part to post machining 12. Post machining
a. Part needs to be checked for machining needs
b. Machining needs to be pro-grammed/adopted
c. Manual measuring to locate machining necessary items d. Execute post-machining
As one can observe, it can be read in the table and it was also briefly mentioned in the intro-duction part, a lot of manual work is involved in the repair process today.
Given these points, this resolves in a high amount of labour hours and accordingly in a high amount of costs. This increases extra, when special knowledge is necessary like it is when a special trained person is needed for measuring of parts or carrying out a manual programming of the process. Additionally, if the process is carried out in high-labour cost countries in Eu-rope the costs increase further as well.
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2.3.2 The Future Process of Repairing
In contradiction to the previous sub-section, the focus in this part is to describe the ideal fu-ture process from today’s view on the application.
The general aim – as described in section 1.1 – is, to reduce: 1) the overall costs,
2) the throughput time of the repair,
3) the human labour needed for executing the process and 4) the complexity of applying the process
on worn or damaged components, for the end-user.
As it was demonstrated in the previous sub-section 2.3.1, the current repair process is notably labour intense. This is mainly because, several machines are needed to repair a component. The components need to be moved thru the different machines during the process. Namely a CMM can be mentioned here, where the part is moved for measuring and quality control. As a result, that makes the process– above all – cost intense and economically applicable just for expensive components. Especially in labour intense countries like Sweden and Germany the costs are a big aspect to consider when the process is labour intense.
Thus, as a first step and as one solution, to reduce the mentioned factors the measurement process can be optimised labour hours and at the same time reduce investment costs, the measurement process shall be optimized.
As one possible solution the measurement system shall be integrated into the machine envi-ronment, to enable a measuring of a worn component without moving the component. Further by replacing e.g. a CMM machine with alternative measurement system, the measuring pro-cess can be made significantly faster, cheaper and can be automated.
Henceforth, the first step is to find soultions to meet these demands of an integrated measuring system. A suitable solution, shall be researched, analysed and if possible suggested for application in this thesis. This will open new possibilities of the process towards Industry 4.0 and digitalisation of the full processes chain.
Possible future aims to be realised
In future the machine shall also be include into the Industry 4.0 environments and use these standards. Hence an automatic recognition of the insert component could be developed. This could enable repairing, without any interaction. The machine could access a database of the companies’ CAD files, where a match can be performed measurement. It will to perform a target/actual comparison and thus define worn areas fully automatically.
Additionally, less part handling between different machines shall reduce the overall needed interaction with human which results in reduced overall costs. Consequently, loading and un-loading could be done with a robot.
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Similar implemented ideas available in industry:
During the research phase of this thesis, to shape the state-of-the-technology part, three simi-lar solutions or attempts to solve a very simisimi-lar problem were found.
1. A solution from Zhang, Li, Cui, and Liou (2018), where a structure light scanner was used to measure turbine blades in order to detect worn areas on the blade. However, the focus here is on the measuring itself and on how to improve the measured data.
2. A solution from Wimpenny (2012) where the general process was analysed, and the same conclusions were pointed out as in this paper. Measurement was however still carried out in a CMM externally to the print process
3. A solution from Zheng et al. (2006) where the measurement process also was pointed out as a labour intense process. Alternative methods were presented and elaborated of their applicability. The paper done in 2006 however indicated that the solutions avail-able back then were not avail-able to offer the same possibilities in terms of accuracy etc.
4. Last mentioned solution is from the company (Lunovu 2018) which presents a very similar approach to the one Trumpf will de-velop, however no detailed specification could be accessed or pub-lications were found. A YouTube link was found after deeper re-search which shows the setup and execution of the process:
https://www.youtube.com/watch?v=1u_oDjcrlXA&vl=en
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2.4 Sensor Systems for Surface Measurement
In this chapter the different possible sensors and sensor systems, which can be applied to measure components in the machine working area, are introduced and their working principle is described briefly.
The process of measuring a component and feedback that data into a computer usable format, is referred to as reverse engineer.
Reverse engineering usually follows the steps of gathering data, filtering data, computing a near-shape model and combining with further input like colour appearance or texture of the surface.
The data collection of a surface shape and dimension can be done by the use of several differ-ent techniques, a taxonomy can be seen in Figure 11. After filtering the data, the near-shape model is usually computed as a triangulated or meshed model out of a point-cloud. (Bagci, 2009, p. 408)
The process of collects and produces data from the real object is commonly referred to as scanning Depending on the used system this can be done automatically or semi-automatic. In some cases, the component has to be moved or manipulated in a dedicated direction, in others the scanning system itself has to be moved. (Bellocchio et al., 2013, p. 6)
If neither can be done, e.g. to scan objects bigger then the “view” of the system, in most cases several scans have to be carried out. These scans then can be added in one combined scan in a dedicated software in the post-process or sometimes even done by the sensor post-processing itself.
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The process of digitalising a real-world component can be done in several ways, they can be categorised for example in the way, Bellocchio et al. (2013, p. 21) suggested in his taxonomy:
For the purpose of this project, not all in Figure 11 mentioned measuring principles are appli-cable. For a 3D surface scan in particular, even less are appliappli-cable. In the following part, fea-sible solutions are mentioned, and their working principle is briefly explained:
Contact Destructive Slicing Non-destructive CMM Non-contatct Tras-missive Computer Tomography Reflective Optical Sonar Mircowave Radar Optical Passive Shape from Silhouettes Shape from Defocus Active Time of Flight Active Triangulation Photometric Stereo Inter-ferometry
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The following list is acquired with information from Corner, D' Apuzzo, Li, and Tocheri (2006), Chen, Brown, and Song (1999) and Zhang et al. (2018)
1. Coordinate-Measuring Machine CMM a. Touch Trigger Probe
A probe is attached to a NC-driven machine head and with moved towards the part, as soon as the probe gets in contact with the surface it triggers the meas-urement and writes the current position into the measuring log.
b. Scanning Probe
A probe, usually spherical is continuously moved along the surface and in set time spans writes the current position in a log.
2. Time of Flight a. Laser Point
The laser point sensor creates a laser light, which is sent out of the sensors in pulses. When getting in contact with reflective material it will reflect towards the sensor and the time between sending the laser pulse and receiving it back allows to recalculate the distance from the sensor to the reflected material.
3. Active Triangulation a. Laser Line
The laser line sensor sends laser light in a line towards the pointed surface, when reaching a reflective object, the light is reflected back to the sensor. In a defined distance from the laser source a diode detects the reflected light and with the principle of triangulation the distance from the reflected surface to the sensor is acquired.
b. Coded Light Projection
This technology works with light or code patterns which are projected on the surface, usually in several different patterns in sequences. The pattern is cap-tured by one or more cameras and with triangulation, as explained before, measured. With this system bigger areas with several million points can be measured in several seconds.
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Reverse Engineering
Reverse engineering is the process, where a real-world object, or in this case a metal compo-nent, is copied into a digital world, for example into a Computer-aided design (CAD) soft-ware. There it can be used for further processing or in turn to shape a real-world object again, with machining for example. (Romero-Carrillo, Lopez-Alba, Dorado, & Diaz-Garrido, 2012, p. 91)
Since all real objects are measured in three dimensions (3D), this has to be done in reverse engineering for most of the applications as well.
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3
Methodology to Evaluate Feasible Measuring Solutions
The scientific methodology used to assess all sensors or sensor systems in this thesis is de-scribed briefly below.
The assessing is necessary, since from a system perspective, different kinds of techniques can be applied to measure a surface of a component. However, due to restrictions (e.g. the overall allowed size of the measuring system), the “best solution” has to be researched which then can be tested and if necessary, changed. The following graph shows the PDCA-cycle for that continues improvement process, to ensure the right sensor used within the system.
The methodology is split into two parts:
1) Qualitative rating of measuring technologies, to measure and reverse engineer a sur-face
2) Quantitative rating of sensors, which are applicable for the specific needs of the ap-plication and to the boundaries given by the machine
To ensure finding the best solution, first all different technologies to measure a surface are presented in section 2.4, followed by a quick assessment of which technologies seem feasible to apply to the needs of this project. Additionally, the left-over sensors are being evaluated more in detail with a rating scheme. Likewise, this ensures a transparent and traceable evalua-tion of soluevalua-tions.
It also guarantees, that changes in the application or in the specification sheet for the sensor can be implemented in the presented evaluation table in chapter Fel! Hittar inte
referens-Plan:
Implementing the right sensor, which fulfills all
specifications! Do: Researching on solutions possible. Assess solutions towards "best fit". Check: Are all specifications fullfiled? Will sensor also fit all other (forseeable) purposes? Act: Implement changes to new specifications. Change specifiactions if attributes failed.
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källa. on page Fel! Bokmärket är inte definierat., to find the best solution fitting to the new
needs.
The following graph illustrates the methodology, how the best of solutions of measuring sys-tem is determined.
This methodology applied, ensures that the chosen solution is not just valid from a monetary viewpoint, it is valid from a variety of perspectives, which will empower a broader view on each reviewed solution. Additional to that, it enables an integral developed solution.
1 - 2 - 3 - All available
solutions
Filter out solutions which do not fit to the need (Qualitative research)
Determine best solution, thru as-sessing.
(Quantita-tive research)
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3.1 Qualitative Assessment of the Measuring Solutions
In this section reason will be given why some measuring solutions might be better and others are less appropriate to be applied to the machine, to form a suitable solution.
1. Coordinate-Measruing Machine (CMM)
a. Touch Trigger Probe
Can easily fit into the machine environment, also the Trumpf TruLaser Cell 3000 would be applicable for this solution. A back draw is, that the accuracy is quite limited to the probe head size.
b. Scanning Probe
The acquired data is very precise, however – as mentioned previously – limited in ac-curacy. It can easily be integrated into a machine like the TruLaser Cell 3000, where it can use the internal NC-drive systems to read its current position.
2. Time of Flight
a. Laser Point
This method is very accurate and simple to apply to the machine environment. Here also the NC-drive of the machine would be used to log the current position of the la-ser point and with adding the distance measured by the sensor, the position of the surface in relation to the machine origin can be calculated.
However, the measuring in a sufficient resolution over the whole surface of a part will be time consuming, since point by point a measurement has to be made. Further shiny surfaces can lead to measuring errors, due to deflection of the light.
3. Active Triangulation
a. Laser Line
An accurate solution, which could be attached to the machine without much effort. The principle of how this sensor measures 3D, is similar to the mentioned laser point sensor. The internal NC-controller would be used to calculate the surface po-sition in relation to the machine origin. A back draw could be given when surfaces are very shiny and deflect the light in to many directions, which resolves in meas-uring errors.
b. Coded Light Projection
The coded light sensors have a really big advantage against the other techniques: They cover a large 2D area at once and thus get results in few seconds for big parts. On the other hand, the systems are usually rather big and sensitive to their environment in terms of heat, splashes and dust. Which makes them usually hard to integrate into the process flow of machining methods.
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3.2 Quantitative Evaluating of the Measuring Solutions
For the assessment, a process needs to be introduced which allows to quantify each solution on a given ordinal scale. Only then a comparison based on differences will be allowed.
Sensors were researched and then assessed with the following 8 features:
1. Size (Volume) 2. Cost
3. Accuracy 4. Repeatability 5. Scan speed
6. Rigidity of the system
7. Possibility for similar application use 8. Integration feasibility
The following table shows all factors which are being used to evaluate the best solution to be applied to the Trumpf TruLaser Cell 3000 Series in order to measure parts in its enclosure. The rating scale is from “0” = unknown specification (which will not be shown in the table) till “10” = excellent fulfilment of the specifications.
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Table 3 - Rating and the respective justifications for each factor, to compare possible solu-tions
Factor Rating Justification
1) Size (Volume) 1 > 720 (ex.: 12,0 * 12,0 * 5,0 cm) in cm3 2 - 5 720 – 591 6 - 9 590 – 128 10 < 128 (ex.: 8,0 * 8,0 * 2,0 cm) 2) Cost 1 > 250.000 in SEK 2 - 5 250.000 – 150.001 6 - 9 150.000 – 50.000 Sensor only 10 < 50.000 3) Accuracy 1 > 20 in M 2 - 5 20 – 13 6 - 9 12 – 6
Max. possible of system 10 < 6
4) Repeatability 1 > 1,6 in M 2 - 5 1,6 – 1,1 6 - 9 1,0 – 0,5 10 < 0,5 5) Scan speed 1 - 3 > 60 in sec. 4 - 6 60 – 20
Time to measure a are of
100cm2 (10 * 10 cm) 7 - 9 < 20
6) Rigidity of the system 1 - 3 Very delicate system whose
environ-ment must be controlled
IP X Classifications2
4 - 6 IP X classification, however, to some extend careful handling necessary 7 - 9 IP X classifications and shock
ap-proved as well as housing available
7) Possibility for similar
ap-plication use 1 - 3 Not feasible at all – maybe possible
4 – 6 Possible with some extend 7 - 9 Possible – Some Exceptions
8) Integration feasibility 1 - 3 The implementation into the current
repair process seems complex 4 - 6 The integration is possible with some changes to the process
2 IP X codes derive from the standardisation publication of the European CEN: EN 60529. Which rates and
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7 - 9 Integration is fairly simple
The factors in detail used in the rating
In the following the all factors from
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Table 3 are presented and a reasoning is given for each:
1) Size (Volume)
The size of the measuring system, in particular the sensor is a crucial part since it will limit the working space of the machine and could lead to restrictions of the freedom of movement of the machine. Consequently, the sensor itself, has to be as small as possi-ble. The whole system, if outside of the machine can however be bigger and is not considered in the rating.
2) Cost
The costs always need to be considered in business decisions, which is why it needs to be included as a factor. However, costs should be looked at in a relation to the related output.
3) Accuracy
Accuracy plays a crucial role for the application of the sensor, since it is the technical specification which gives an answer to the detail which worn areas on the surface can be detected.
Further, if the rule of thumb for the accuracy is applied, backwards, the nozzles’ min-imal processing size gives explanation to the necessary figures.
The nozzle of the LMD process, as explained in chapter 2.2, has a maximal accuracy of less than 1 mm in diameter.
4) Repeatability
This is in particular important for the quality of a series of measurements, the higher the rating, the closer the results are to each other. Which would resolve in a steady and stable process is given.
5) Scan speed
Gives answer on how fast a whole component can be scanned. This factor will have direct influence on the throughput time, the faster the part can be scanned, the less downtime has the additive machining.
6) Rigidity of the system
Gives explanation on how sensitive the system is to external factors like dust, splashes and heat. The system can have IPX standards applied which gives detailed information about the resistance against such factors.
7) Possibility for similar application use
Represents an indication on how open the system is towards other application. Is the system dedicated for one use only, it will be hard to come up with new ideas on how to further develop the application. This does not mean use in another context, but re-fers to use in the same context with other focus.
8) Integration feasibility
Facilitates the need of integrating the process directly into the work flow without inter-rupting it, for example: to initiate the system, load data or similar. The easier the sen-sor can be used without pre-work and with software etc. provided, the better for the project.
The rating procedure
33 “0” = unknown specification, over
“1” = insufficient, till “10” = excellent
and is justified with a minimum specification a solution has to have, to get rated accordingly. If the specification is in-between two numbers, due to the specifications in-between two rat-ings, the nearest difference will decide on the rating.
