Peeking into the void: Digital twins for construction site logistics
Introduction
Significant improvements in information and communication technologies (ICT) including cloud computing, Internet of Things (IoT), as well as artificial intelligence (AI), have already disrupted many sectors (Drucker, 2017). Drawing on these technological innovations the digital twin concept – a digital representation of a physical object of interest – has recently emerged as a particularly attractive use case across various industries (Cimino et al., 2019). The investment in digital twins is expected to be offset by increased productivity through predictive analytics (Lee et al., 2013) or the provision of value-added services (Tao et al., 2018). However, oftentimes these goals cannot be achieved by mere data collection but necessitate the adoption of data-driven decision-making (Davenport and Harris, 2007, Brynjolfsson et al., 2011).
Such solutions already create significant business value (Cimino et al., 2019, Cearley et al., 2016, Boschert and Rosen, 2016). Current applications share the fact that they are typically deployed in technology-oriented industries where companies are used to operate on the front-line of innovation. In contrast, “low-tech” industries are much less frequently leveraging the potentials of digital transformation. At the same time, these industries are of great importance to any developed economy (Hirsch-Kreinsen et al., 2006).
A case in point is the construction industry which is frequently listed among the least digital industries (Leviäkangas et al., 2017). Yet, digital transformation is expected to significantly reshape this industry in the years to come (Oesterreich and Teuteberg, 2016). Currently, many players in construction are pushing forward digital representations of buildings to facilitate easier management, maintenance and upgrading (Song et al., 2012, Khajavi et al., 2019). However, construction site processes remain distinctly non-digital characterized by unclear responsibilities, printed plans and opaque inventories. In such environments efficient planning procedures are difficult to implement.
In collaboration with a leading supplier of building materials, we explore the opportunities for construction site logistics offered by establishing digital twins for bulk silos. We are interested in the potential business value of continuous silo fill level monitoring and tracking. This seemingly small technological innovation offers several opportunities for improving current and introducing new business processes.
This paper is structured as follows. In Section 2, the supply process is described, followed by the shortcomings of the status quo. Section 3 will elaborate on the related work. Then in Section 4 the business value opportunities of this nascent information system are presented. In Section 5 the process transformation is presented, followed by Section 6, where the decision support system (DSS) used to tap into these transformational benefits and its results are discussed. The final section concludes and provides an outlook for future research.
Section snippets
Problem description
Bulk materials constitute the largest element of the construction supply chain (Lundesjö, 2015a). The storage of these materials needs to be cost-effective, safe, and systems should be easy to integrate into operational processes. Bulk silos have established themselves to be particularly suitable for mobile bulk storage applications in construction and agriculture. This is also the case for the industrial partner we collaborated with in this research.
Related work
The advances in information and communication technologies lead to the integration of more and more functions into supply chains. Consequently, supply chains and logistics systems become more comprehensive in the practical and theoretical world. Being concerned with digital innovation for construction site logistics, we investigate three research strands: Trends in the construction industry, digital twin strategies as well as vehicle and inventory routing problems.
Digital supply chain
Having outlined the status quo, we next want to explore how the company's business operations may benefit from expanding the digital representation of their silos. Currently, the company tracks for each of its silos the type (size, dispenser system), the material currently filled in, and the position (based on order status). To achieve a complete digital representation—a proper digital twin of the silo—one needs to be able to access the silo's current fill level. Clearly, the integration of
Process transformation
Utilizing the available data allows us to break up the existing silo supply and replenishment processes described in Section 2. In contrast to the old plant–site–plant movement patterns, the additional available information allows to move silos directly between construction sites, see Fig. 2.
Results
Due to the large number of decision variables and constraints, the complexity of the new integrated process may easily overwhelm a human decision-maker. We seek to design a suitable DSS to leverage the transformational benefits of smart silos and support planners in their operational and strategical decision making. Subsequently, we exploit the prototype DSS to perform extensive simulations.
Conclusion and outlook
Our research does not simply explore the potentials of digital twins within a low-tech industry, it also sheds light on how that value is provided through intelligent decision support. With the limitation that our findings rest on a single case company. By transforming “dumb” silos into smart data processing units a new logistics system can be established which can directly reduce costs. Also, every kilometer saved has a positive effect on the development of CO emissions (Léonardi and
CRediT author statement
Greif, Toni: Writing—Original Draft, Software, Visualization, Writing – Review & Editing, Conceptualization, Validation.
Stein, Nikolai: Writing–Reviewing and Editing, Conceptualization, Methodology, Validation.
Flath, Christoph M.: Writing–Reviewing and Editing, Conceptualization, Methodology, Validation.
References (60)
- et al.
Digital supply chain: literature review and a proposed framework for future research
Comput. Ind.
(2018) - et al.
3PL service improvement opportunities in transport companies
Procedia Eng.
(2017) - et al.
Review of digital twin applications in manufacturing
Comput. Ind.
(2019) - et al.
The petrol station replenishment problem with time windows
Comput. Oper. Res.
(2009) - et al.
Industry 4.0 as an enabler of proximity for construction supply chains: a systematic literature review
Comput. Ind.
(2018) - et al.
Towards a data science toolbox for industrial analytics applications
Comput. Ind.
(2018) - et al.
The multi-commodity one-to-one pickup-and-delivery traveling salesman problem
Eur. J. Oper. Res.
(2009) - et al.
Applying autonomous sensor systems in logistics – combining sensor networks, RFIDs and software agents
Sens. Actuators A: Phys.
(2006) - et al.
Business models for industrial smart services-the example of a digital twin for a product-service-system for potato harvesting
Procedia CIRP
(2019) - et al.
Integrating the digital twin of the manufacturing system into a decision support system for improving the order management process
Procedia CIRP
(2018)
CO2 efficiency in road freight transportation: status quo, measures and potential
Transp. Res. Part D: Transp. Environ.
Recent advances and trends in predictive manufacturing systems in big data environment
Manuf. Lett.
Keeping up with the pace of digitization: the case of the Australian construction industry
Technol. Soc.
A review of the roles of digital twin in cps-based production systems
Procedia Manuf.
Understanding the implications of digitisation and automation in the context of industry 4.0: a triangulation approach and elements of a research agenda for the construction industry
Comput. Ind.
About the importance of autonomy and digital twins for the future of manufacturing
IFAC-PapersOnLine
Development of a BIM-based structural framework optimization and simulation system for building construction
Comput. Ind.
A system engineering perspective to knowledge transfer: a case study approach of BIM adoption
Virt. Real.-Hum. Comput. Interact.
Static pickup and delivery problems: a classification scheme and survey
Top
Digital Twin – The Simulation Aspect
Mechatronic Futures
Strength in Numbers: How Does Data-Driven Decision-Making Affect Firm Performance?
Top 10 strategic technology trends for 2018
Top
Scheduling of vehicles from a central depot to a number of delivery points
Oper. Res.
Competing on Analytics: The New Science of Winning
Usage of optimization techniques in civil engineering during the last two decades
Curr. Trends Civ. Struct. Eng.
The Age of Discontinuity: Guidelines to Our Changing Society
The construction industry as a loosely coupled system: implications for productivity and innovation
Constr. Manag. Econ.
A generalized assignment heuristic for vehicle routing
Networks
The digital twin paradigm for future NASA and U.S. air force vehicles
53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA
Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems
Transdisciplinary Perspectives on Complex Systems
Cited by (96)
Digital twin technology for thermal comfort and energy efficiency in buildings: A state-of-the-art and future directions
2024, Energy and Built EnvironmentDigital twins in the built environment: Definition, applications, and challenges
2024, Automation in ConstructionDigital twinning of building construction processes. Case study: A reinforced concrete cast-in structure
2024, Journal of Building EngineeringDeveloping an integrative framework for digital twin applications in the building construction industry: A systematic literature review
2024, Advanced Engineering InformaticsEnergy Digital Twin applications: A review
2023, Renewable and Sustainable Energy Reviews