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Manuel Woschank
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A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics
M Woschank, E Rauch, H Zsifkovits
Sustainability 12 (9), 3760, 2020
2552020
Industry 4.0 for SMEs: Challenges, opportunities and requirements
DT Matt, V Modrák, H Zsifkovits
Springer Nature, 2020
2482020
A maturity level-based assessment tool to enhance the implementation of industry 4.0 in small and medium-sized enterprises
E Rauch, M Unterhofer, RA Rojas, L Gualtieri, M Woschank, DT Matt
Sustainability 12 (9), 3559, 2020
1152020
A framework of measures to mitigate greenhouse gas emissions in freight transport: systematic literature review from a Manufacturer's perspective
P Miklautsch, M Woschank
Journal of Cleaner Production 366, 132883, 2022
572022
Requirement analysis for the design of smart logistics in SMEs
P Dallasega, M Woschank, H Zsifkovits, K Tippayawong, CA Brown
Industry 4.0 for SMEs: Challenges, opportunities and requirements, 147-162, 2020
502020
Reference architecture for an integrated and synergetic use of digital tools in education 4.0
T Goldin, E Rauch, C Pacher, M Woschank
Procedia Computer Science 200, 407-417, 2022
472022
Field study to identify requirements for smart logistics of European, US and Asian SMEs
P Dallasega, M Woschank, S Ramingwong, KY Tippayawong, ...
Proceedings of the International Conference on Industrial Engineering and …, 2019
432019
State of the art and future directions of digital twins for production logistics: a systematic literature review
A Kaiblinger, M Woschank
Applied Sciences 12 (2), 669, 2022
412022
Smart Logistics—Technology Concepts and Potentials
H Zsifkovits, M Woschank
BHM Berg-und Hüttenmännische Monatshefte 164, 42-45, 2019
392019
Industry 4.0—Awareness in South India
L Safar, J Sopko, D Dancakova, M Woschank
Sustainability 12 (8), 3207, 2020
372020
Organizational innovation implications for manufacturing SMEs: Findings from an empirical study
I Baumane-Vītoliņa, M Woschank, M Apsalone, Ē Šumilo, C Pacher
Procedia computer science 200, 738-747, 2022
322022
Teaching and learning methods in the context of industrial logistics engineering education
M Woschank, C Pacher
Procedia Manufacturing 51, 1709-1716, 2020
322020
Requirement analysis for SMART supply chain management for SMEs
P Chaopaisarn, M Woschank
Proceedings of the International Conference on Industrial Engineering and …, 2019
282019
Digitalization in industrial logistics: Contemporary evidence and future directions
M Woschank, A Kaiblinger, P Miklautsch
Proceedings of the International Conference on Industrial Engineering and …, 2021
262021
A holistic didactical approach for industrial logistics engineering education in the LOGILAB at the Montanuniversitaet Leoben
M Woschank, C Pacher
Procedia Manufacturing 51, 1814-1818, 2020
252020
A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics. Sustainability (Switzerland), 12 (9)
M Woschank, E Rauch, H Zsifkovits
242020
Big data in the metal processing value chain: a systematic digitalization approach under special consideration of standardization and SMEs
M Sorger, BJ Ralph, K Hartl, M Woschank, M Stockinger
Applied Sciences 11 (19), 9021, 2021
222021
Evidence-based redesign of engineering education lectures: Theoretical framework and preliminary empirical evidence
BJ Ralph, M Woschank, C Pacher, M Murphy
European Journal of Engineering Education 47 (4), 636-663, 2022
182022
Implementing Industry 4.0 in SMEs: Concepts, Examples and Applications
DT Matt, V Modrák, H Zsifkovits
Springer Nature, 2021
182021
Logistics 4.0 measurement model: empirical validation based on an international survey
P Dallasega, M Woschank, J Sarkis, KY Tippayawong
Industrial management & data systems 122 (5), 1384-1409, 2022
172022
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