1. Introduction
3D printing and additive manufacturing (AM) are techniques and technologies to manufacture or create physical objects out of a number of materials such as plastics, metals or ceramics from digital model files generatively without requiring special tools besides a 3D printer. This technology is currently highly researched, and developments have been made by public institutions and private entities. Data on the prevalence of certain technologies in general or the market value in individual countries is sparse. This dataset is compiled to provide a basis for further research, such as market analysis and capitalization analysis, in Germany. The list contains information about 284 companies, ranging from individual persons, acting as legal entities, to internationally-active corporations. Information on such entities can also be used to incorporate external services in cloud manufacturing systems or connected 3D printing services, as described in Baumann et al. [1]. Furthermore, this information can be used to help to identify stakeholders in resource description endeavors as described in Baumann and Roller [2]. This dataset enables research on company structure and historical development in the domain of AM. Furthermore, with this dataset, collaboration initiation and the opportunity for industrial interested parties are facilitated. Functioning as a basis for extension, the dataset can also be used to assess the impact of this technology on the national economy of Germany.
This work is structured as follows: Following Section 1 and Section 2 provides information on the method and sources used in this research for the data acquisition and compilation. Section 3 provides information on various sources used for the generation of this overview, on the motivation for the respective source selection and provides information on the scripts employed for automatic data acquisition in Section 3.2. Section 4 contains information on the dataset provided with this research as supplemental data, and Section 4.1 provides detailed information on the structure of the overview document containing all of the information on the companies, excluding the downloaded html files.
2. Data Acquisition
The compilation was performed via literature (see Fastermann [3]) and Internet-based research for certain keywords and phrases. As sources for the Internet research, the search engines Google [4] and Bing [5] were utilized. The search phrases include, as well as combinations thereof:
1. +“3D Druck” + Firma (engl.translation: 3D print + company)
2. +“3D Drucker” + Firma (engl. translation: 3D printer + company)
3. +“Additive Fertigung” + Unternehmen (engl. translation: additive manufacturing + company)
4. +“Generative Fertigung” + Unternehmen (engl. translation: generative manufacturing + company)
5. +“Rapid Manufacturing” + Unternehmen (engl. translation: rapid manufacturing + company)
The search phrases and keywords are presented here in their original German language, as the research is focused on Germany and the justification is that the companies sought address the German market in German. It was also argued that searching in this language will eliminate a large number of businesses that are out of scope, i.e., from other countries than Germany.
Furthermore, information was acquired indirectly via websites of federations or unions on AM-related topics.
For each company found, the respective website was visited, and the information of this site was extracted both manually and automatically, with the support of custom scripts (see Section 3.2). The German law dictates that every business operating in Germany and having a website must provide certain information in their imprint, such as the name, address and routing information. International companies with only German subsidiaries, such as Makerbot Deutschland, were not considered for this compilation. Furthermore, companies with only limited involvement in AM, such as Verbatim, who sells 3D printer filament, where apparent, were also excluded from consideration. Companies listed in association information, as described below, with apparent limited involvement in AM, such as companies offering photography services for 3D printing projects, were also excluded.
The list of excluded companies from the neighboring European and overseas American companies include:
1. Makerbot Deutschland https://eu.makerbot.com, subsidiary of Stratasys GmbH/Stratasys Ltd. (USA)
2. Stratasys Deutschland http://www.stratasys.com/de, subsidiary of Stratasys Ltd. (USA)
3. 3D Jake https://www.3djake.de, niceshops GmbH from Austria
4. PrintAbout GmbH http://printabout.de, distributor for PP3DP from The Netherlands
5. 1zu1 Prototypen GmbH & Co KG https://www.1zu1prototypen.com, from Austria
6. B&R Industrie-Elektronik GmbH http://www.br-automation.com, from Austria
7. robotmech Stössl GmbH https://www.robotmech.com, from Austria
8. 3d medical print KG http://www.3dmedicalprint.com, from Austria
9. ENVISIONTEC GMBH https://envisiontec.com, subsidiary of ENVISIONTEC, INC. (USA)
These companies are either subsidiaries of foreign companies, operate in Germany from abroad or are located in neighboring countries and are of similar legal standing as German companies, e.g., a GmbH, Gesellschaft mit beschränkter Haftung, engl. company with limited liability.
Companies were further identified from the following associations, unions and exhibition websites:
1. 3D-grenzenlos, 3D-Druck Magazin für Deutschland https://www.3d-grenzenlos.de/listen/3d-drucker-hersteller
2. 3Dnatives, 3D Druck und 3D Drucker: Beste Preise, Tests, News http://www.3dnatives.com/de/deutschland-hersteller-270420161
3. VDMA Verband Deutscher Maschinen- und Anlagenbau e.V. http://am.vdma.org/memberslist
4. Hannover Messe http://www.hannovermesse.de/de/news/top-themen/additive-manufacturing
5. ADDITIVE MANUFACTURING Forum https://additivemanufacturingforum.de/firmen
6. digifab, Netzwerk Digitale Fabrik e.V. http://www.digifab-ev.de/seiten/vorjahre.htm
7. M&T-Metallhandwerk http://www.mt-metallhandwerk.de/additive-fertigung-vom-prototyp-bis-zum-ersatzteil/150/44275
8. Das 3D-Netzwerk http://www.3dnetzwerk.com/en/3d-network
9. Verband 3DDruck e.V. http://www.verband3ddruck.berlin
10. 3D-Druck Netzwerk Berlin http://3d-druck-netzwerk.de
11. 3Printr.com https://www.3printr.com/serviceproviders
3. Results
For the compilation of the information on the companies, information from the following online sources was used. The relevance and information acquired is described after the list.
1. Bundesanzeiger/Federal Gazette [6] https://www.bundesanzeiger.de
2. Archive.org [7] http://web.archive.org
3. Xing [8] https://www.xing.com
4. Kununu [9] https://www.kununu.com
5. Geocode [10] https://geocode.xyz
6. Wer liefert was? [11] http://wlw.de
7. Bing https://bing.com
8. Handelsregister/Registry court [12] https://www.handelsregister.de
Information on the company was acquired primarily from the company website, which was identified by the means described herein. The Bundesanzeiger website was used to retrieve the latest balance sheets for the company where available. The latest balance sheets available were from the fiscal year 2015 for most companies. The information from Archive.org was used to assess the first and last archival dates for the website to estimate the popularity of the website (more popular websites are archived more often than less popular websites) and estimate the first appearance of the website on the Internet, which might coincide with the inception date of the company. Xing was used to acquire information on the company owner and might be used in later research to assess the company structure and employee qualification. Information from Kununu was used to assess a rating on the company from the viewpoint of its current and former employees and might be used in later research for qualitative dissemination. Geocode was used to map location information such as city to geo-information for display in digital maps; see Figure 1 for an example. The B2B marketplace Wer liefert was? (WLW) was used to provide additional information on the company such as inception date, categorization, description and contact information. Information on this website is provided by the company itself. The search engine Bing was used to provide information on the number of entries in the cache from the search engine with the motivation to assess the popularity of the website, with more popular websites having more entries in the search engine cache. Information from the registry courts was used to provide official information on the company address and status, as well as initiation documents, which are provided separately.
Enlarge this image.Figure 1. Geographical distribution of identified companies; created with https://geocode.xyz/batch.
After probing fifteen randomly-selected companies from the dataset without a single result, it was deemed that the LEI (legal entity identifier) from the Legal Entity Register, https://www.leireg.de, is insufficient to provide meaningful information to the data in its current state.
The list of all companies queried for and included in this study follows in Table 1:
[ Table omitted. See PDF. ]
3.1. Classification
The companies contained in the overview are first categorised into two categories describing the perceived orientation towards 3D printing. The first category is partial (PART, in the overview document) for companies that are involved in 3D printing, but also cater to some other forms of business, e.g., selling other kinds of machinery or providing other services than 3D printing. The second category is complete (COMPLETE, in the overview document), denoting businesses that are solely focused on 3D printing.
Further categorization is performed on the mode of business, with:
1. Sale or production of hardware, i.e., 3D printers (indicated as HW(P), in the overview document)
2. Sale or development of software, e.g., 3D printing simulation or other tools (indicated as SW, in the overview document)
3. Sale of supplementary material for 3D printers, e.g., filament, powder, or resin (indicated as HW(MAT), in the overview document); also development of 3D printing material
4. 3D printing service and other services, such as 3D printer rental, 3D model preparation or training (indicated as SERVICE, in the overview document)
3.2. Script-Based Information Retrieval
To facilitate efficient data acquisition and enrichment, a number of scripts were employed. The scripts are written in BASH [13] for the Linux platform. These scripts are detailed in the following Section 3.2.1, Section 3.2.2, Section 3.2.3, Section 3.2.4, Section 3.2.5, Section 3.2.6 and Section 3.2.7.
3.2.1. Registry Court Information
See Supplementary Material reg-ger-search.sh for the script that was used to acquire data from the central registry court information website. This script scrapes the website for the search term that is the company’s name and then downloads all associated publications and information for the respective company. A number of publications, such as historical records, must be purchased from the registry court website, and these publications are excluded from the download. The results were manually checked to eliminate false-positive results for companies with similar names.
3.2.2. Information from B2B Marketplace WLW
The script wlw-search.sh scrapes the B2B-marketplace Wer liefert was? (WLW) for information on the company in question. The script utilizes the central search function of the website and acquires the details present for the first company by the searched for name. Furthermore, this script extracts the html title of the associated company website to provide an automated way of capturing this information. The WLW website contains information provided by the businesses themselves. On this website, all registered companies are identified by an integer identifier.
3.2.3. Information on the Results from the Search Engine Bing
With the script bing-info.sh, information on the number of results in the search engine Bing’s cache is extracted, as well as information on how often the company URL is linked on other websites.
3.2.4. Information from the Internet Archive
The script archive-info.sh parses the information from the Internet Archive at https://www.archive.org for a specific URL, the company URL. Information is extracted on the first and last occurrence of the archival process, with the motivation that popular websites are being archived more often and, furthermore, to provide information on a possible company inception date. Information on the number of archival requests is also retrieved.
3.2.5. Wordcloud Generation from Website Data
The script website2wordcloud.sh extracts all visible and invisible links from the company website’s base URL and downloads every document linked to a temporary folder. From the downloaded files, only files that are html are further analyzed. The resulting files are parsed from html to text and aggregated in one single file for wordcloud processing. The wordcloud processing is performed with the software word_cloud [14] from https://github.com/amueller/word_cloud, and the most common words are placed on a digital canvas according to their occurrence and scaled accordingly. For further processing, the aggregated text file is separated into words and stored separately. An example for such a wordcloud is presented in Figure 2 from the company StaeGi GmbH with the URL http://www.staegi.de. A number of websites was not suitable for automatic parsing and acquisition due to heavy reliance on JavaScript, Flash or other technology that is not readily accessible with text-based tools. These websites are unfriendly to screen readers and other assistive technology and were excluded from further automated analysis.
3.2.6. Most Common Words on Website
The script most-common-words.sh analyzes the aggregated textual website data generated by the website2wordcloud.sh script for the ten most used words. The words are compared against a list of stop words (see Appendix A A1 Stop Word List), which are excluded from further consideration. The script produced a list of these common words, separated by commas, and each word prefixed with the number of occurrences. Furthermore, the script presents the total number of words (including the words contained on the stop word list) in the analyzed text file.
3.2.7. Overview Document
The script company-info-aggregate.sh was used to aggregate all information, both manually and automatically acquired, on the respective company and parse this information into a CSV (comma-separated value) file. The resulting overview file contains information on each of the companies identified, with information from the B2B-marketplace WLW, the registry court general information, the Internet Archive, the search engine Bing, geo-coded information on company location and information on the most common words from the company website, as described in Section 4.1. The geo-coded information is primarily based on the official address registered with the registry court and retrieved for the complete address, i.e., street name, number, zip code and city. As a compensation strategy, the address available on the respective website was used for the retrieval of the geo-coded information.
4. Dataset
The dataset presented in this work is composed of the following:
1. Documents from the registry court in supplemental data file reg_court.zip, with the files sorted into directories. Every directory is named after the md5 hash of the company name, present in Column 1 of the overview document. Files in each directory with the suffix “_vo_pub_X.htm” and “_vo_pub_X.txt” contain publications from the registry court where X is a number starting from zero; all publications available on the registry court website are presented in ascending order. The file with the ending txt is derived from the html version by parsing the information and is the textual representation. Files with the suffix “_ut.htm” contain the registry court information on the company, such as the official name and legal status.
2. Documents containing the latest balance sheets from the official Federal Gazette in ba.zip, with html documents for each company available. The files are named “BA_NUMBER_NAME_YEAR.htm”, where NUMBER is identical to the number in Column 2 of the overview document. NAME is an abbreviated name of the company, and YEAR identifies the year of the balance sheet. This information was acquired manually, as the Federal Gazette website uses captchas, which could not be circumvented.
3. Overview document as described in Section 4.1 as an Excel document. Automatically acquired data were manually checked for coherency and manually adapted where necessary.
4. Website information and complete, textual, websites for the respective company in file web.zip, with the individual files named “URL_accumulated.txt”, where URL is identical to the company’s URL.
5. Wordclouds for each respective company in the file wordclouds.zip with files named URL_wordcloud.png, where URL is the company’s URL with the prefix http:// or https:// removed.
A complete wordcloud of every downloaded website is depicted in Figure 3.
4.1. Structure of Data
The following list explains the data structure that is present in the company list. One example each, description or name, is provided for every column, starting from the first:
1. Cryptographic hash (md5) of the company name: “a6f2c37b03eb17751bdb1f03f4df581a”
2. Company number in list: “1”
3. Website title acquired from the respective website: “prontotype: 3D-Druck I 3D-Modeling I Rapid Prototyping I Hamburg”
4. URL of company website: “http://prontotype.de/”
5. Company name as presented on the company website: “prontotype e.K.”
6. Owner or chief executive of the company with the gender present in brackets: “Marc Zimmerer(m)”
7. Zip code and city of the company as presented on the company website: “22525 Hamburg”
8. Register court number: “HRA 116517”
9. VAT Id: “DE 295817576”
10. URL of Xing [8] profile of each executive, separated by comma; Order is identical to the ordering of the persons 5 columns prior with missing profiles identified by N/A: “https://www.xing.com/profile/Marc_Zimmerer”
11. URL of Kununu [9] of company: “https://www.kununu.com/de/trindo”
12. Kununu rating of the company where present: “3.82”
13. Indication if company is completely or partially focused on 3D printing: “COMPLETE”
14. Indication/classification on business area of company: “HW(MAT),SW”
15. Number of results from Bing search engine for the company URL: “51”
16. Number of results from Bing search engine for documents from the company’s domain: “43”
17. Date of the first entry for an archived version of the website in archive.org: “2014-Mar-09 19:31:07”
18. Date of the last entry for an archived version of the website in archive.org: “2017-Jan-10 13:22:02”
19. Number of archived versions of the website in archive.org: 27
20. Company name from WLW marketplace: “prontotype e.K.”
21. URL of company from WLW marketplace: “http://www.prontotype.de”
22. Zip code and city of company from WLW marketplace: “22525 Hamburg”
23. WLW internal ID for company: “1744235”
24. URL of company in WLW marketplace: “https://www.wlw.de/de/firma/prontotype-ek-1744235”
25. Number of employees from WLW marketplace: “1–4”
26. Contact email from WLW marketplace: “[email protected]”
27. Name of executive from WLW marketplace, gender present in brackets: “Malte Fuchs(m)”
28. Inception year according to WLW marketplace: “2011”
29. Company description present in WLW marketplace: “3D Druck und Rapid Prototyping Service. Wir erstellen 3D Modelle für Modellbau, Architektur, Bildung, Medizin, Kunst und Unterhaltung.”
30. Categories listed for the company in WLW marketplace, separated by comma: “3-D Druck, Rapid Prototyping”
31. Title of the website, extracted automatically: textbfprontotype: 3D-Druck
32. Register court for the company: “Amtsgericht Hamburg HRA 116517”
33. Legal form of company according to the register court: “Einzelkaufmann”
34. Initial capital entered into the company per information from the register court, value with denomination: “27000 EUR”
35. Date of entry into the registry court: “2013-10-30”
36. Date of deletion from the registry court, not present for active companies: “2014-10-30”
37. Company balance sheet from the registry court, data field is present in information from the registry court but none of the queried companies has any value set: “N/A”
38. Official name and address of company from the register court: “prontotype e.K., Kleine Bahnstr. 6, 22525 Hamburg”
39. Geo-coded city name of company: “Hamburg”
40. Geo-coded country name of company: “DE”
41. Latitude of company address: “53.56451”
42. Longitude of company address: “10.00739”
43. Confidence value for geo mapping of company address: “0.9”
44. Number of words found on website by web scraping: “1247”
45. And the following 10 columns contain the ten most common words from the website with the number of occurrences concatenated with the respective word: “41:prontotype”
5. Conclusions
The information presented in this study is intended to enable further research in the structure, distribution and nature of companies working in the area of AM in Germany. The companies in this dataset are of various natures and range from small, one-person companies to large corporations with a diverse business focus, ranging from hardware, to software, to 3D printing services.
Supplementary Materials
The following items are available online at www.mdpi.com/2306-5729/2/3/23/s1 as Supplemental Information and described in Section 3.2 for the supplemental scripts and Section 4 for the aggregated data.
Acknowledgments
This study is not funded by any third party.
Author Contributions
Felix W. Baumann conceived of the idea for this work and performed the data acquisition and compilation. Furthermore, Felix W. Baumann wrote the paper. Dieter Roller provided support in writing this paper.
Conflicts of Interest
The authors declare no conflict of interest.
Abbreviations
The following abbreviations are used in this manuscript:
AM Additive manufacturing
CSV Comma-separated value (file format)
ID Identifier
LEI Legal entity identifier
MD5 Message-digest hashing algorithm
URL Uniform resource locator
VAT Value-added tax
WLW Wer liefert was? (B2B-marketplace)
Appendix A. A1 Stop Word List
These words are excluded from counting towards the most common words on the respective website as they are identified as containing no valuable information for the purpose of this study.
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1Institut für Rechnergestützte Ingenieursysteme,Universität Stuttgart, 70569 Stuttgart, Germany
2TWT GmbH Science & Innovation, 70565 Stuttgart, Germany
*Author to whom correspondence should be addressed.
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