How Programmable Construction Can Shape the Future of Sustainable Building in Italy

Abstract

The construction industry has traditionally relied on labor-intensive methods, often resulting in inefficiencies, cost overruns, and extended project timelines. Despite advancements in automation and robotics, the potential of programmable construction to address these challenges remains underexplored, particularly in the context of small to medium-scale projects. This study investigates the impact of programmable construction on time, cost, and sustainability, using a detailed case study of a residential project in Italy. This research adopts a comparative approach, analyzing traditional construction techniques versus automated construction systems. Production rates from previous research and real-world applications are used to develop alternative schedules that reflect the efficiencies of these advanced technologies. The findings demonstrate that programmable construction can reduce project timelines by up to 82.6% and achieve cost savings of approximately 40.6%. Automated systems also offer significant environmental advantages, including a 70.25% reduction in carbon emissions and a 70% decrease in energy consumption in several tasks such as soil treatment. This study suggested that programmable construction sites can significantly shorten project timelines and reduce costs. The precision and speed of AI and robotics minimize reliance on human labor, streamline construction processes, and enhance project performance and work quality by reducing human error while promoting sustainability through reduced resource consumption and lower environmental impact.

1. Introduction

The construction industry is facing significant challenges due to an aging labor force and a scarcity of skilled workers, particularly in terms of the number of available laborers. This shortage has exacerbated issues related to project timelines, cost overruns, and maintaining safety standards. Historically, construction processes have been time-consuming, often requiring labor in adverse conditions, and have struggled with these efficiency and safety concerns. The major difficulties in recent years have centered around ensuring adequate competencies for laborers to manage project completion while respecting time, cost, and safety constraints.

To address these challenges, the industry has increasingly looked toward automation, with SMART systems emerging as a key solution. These systems have enabled significant advancements in construction processes, such as the use of pre-cast concrete floor planks, exterior and interior wall panels, and various unit installations. Through integrating automated construction systems [1,2,3,4,5,6,7,8], the industry has begun to harness the benefits of prefabrication and modular construction. These technologies allow for faster assembly and higher precision, reducing the time and labor required on-site [9,10,11,12,13,14,15].

SMART systems have laid the groundwork for the integration of more advanced technologies, including AI-powered machines and robotics. These technologies represent the next step in construction automation, offering real-time tracking, advanced information management, and logistical efficiencies that were first explored in the 1990s in countries like Korea and Japan [16]. Despite these early efforts, the widespread adoption of such technologies has been hindered by challenges related to cost, construction time, and the need for skilled operators. Additionally, the economic impact of Digital Fabrication (DFAB) on productivity and cost efficiency remains an area of ongoing research. Many studies have demonstrated higher production when digital construction techniques are applied to complex structures, indicating significant financial advantages [7,17,18,19,20,21].

However, further research is necessary to assess the broader economic effects of DFAB’s use in construction.

This paper aims to thoroughly investigate the potential of AI-driven programmable construction sites as a transformative solution to the current challenges faced by the construction industry. It explores how the integration of advanced AI technologies and robotics can effectively reduce project timelines, significantly lower costs, and enhance the overall quality of construction work [22].

2. Literature Review

2.1. Advancements and Challenges in Automation and Robotics Technology in the Construction Industry

The adoption of automation and robotics technology(A&RT) represents one of the most promising strategies for addressing challenges in the construction sector. Increasingly, the industry faces issues such as a declining interest from younger generations and a growing shortage of skilled workers, both of which have contributed to stagnating productivity levels in traditional construction methods [22]. These limitations have been compounded by the rise of megaprojects, including the construction of high-rise buildings and developments on artificial islands, which have driven a growing demand for advanced construction technologies. Studies indicate a significant correlation between advancements in robotics and automation and increased productivity in the construction sector [23].

Under the framework of “Industry 4.0”, strategies from the broader manufacturing sector have been adapted to enhance productivity in construction. However, until recently, construction has been one of the sectors with the least investment in research and development (R&D) related to A&RT. This is largely due to the industry’s complex and dynamic work environment, the involvement of multiple uncoordinated parties, and a general resistance to adopting cutting-edge technologies [24,25].

Despite these challenges, A&RT has seen successful applications within the construction industry, particularly as engineering and construction companies have begun to adopt automated and streamlined project management methods [26,27,28]. These developments have enhanced the understanding of A&RT’s potential benefits, as evidenced by various studies [24,27,28,29]. Analyzing the current research landscape and knowledge base in this field is crucial for identifying future research directions and areas where further R&D is necessary [3,10,25,28,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47].

To address issues such as hazardous working conditions and the lack of coordination among various stakeholders, the construction industry has focused on “hard robotics”, which involves developing new machines and automating existing equipment. Efforts have been made to automate tasks such as bricklaying, excavator control, interior finishing, and infrastructure assessment. Drawing inspiration from factory automation in the manufacturing sector, the construction industry has introduced fully automated systems, including SMART, ABCS, and Big Canopy, which have been extensively documented in the literature [10,25,36,48,49,50].

Recent advancements in hard robotics have also led to the development of wearable mechanical devices that enhance worker capabilities, as well as remote-controlled or autonomous machines designed for efficient and safe construction work in hazardous environments [7,51]. Examples of such technologies include autonomous dozers, digging machines, load carriers, and haul trucks, which are typically operated by remote control. The adoption of these technologies has led to the successful completion of numerous construction projects with high efficiency and without safety incidents, and their usage is expected to grow as technological advancements continue [52].

However, the high initial costs and performance limitations of these innovations pose significant challenges to their widespread adoption. In response, current research is increasingly focusing on “soft robotics”, which involves chip-based process control, image processing, and sensory data acquisition. The integration and coordination of hard and soft robotics are seen as crucial for the future development of advanced automation technologies in construction. As technology and the construction environment continue to evolve rapidly, it is essential to monitor trends in A&RT and AV to uncover new insights and opportunities [16,23,25,53,54]. Moreover, several researchers have employed expert assessments, obtained through questionnaire surveys and case studies, to create operational roadmaps for building automation [16,55,56].

2.2. Comparative Analysis of Robotic and Traditional Construction Methods in Italy and Europe

In recent years, there has been a growing body of research in Europe, particularly in Italy, focusing on the implementation of robotics in construction and its comparison to traditional construction methods. Given that the case study in this work is based in Italy, this review emphasizes studies conducted in Italy and other European countries. These studies have explored various aspects of robotic application, such as productivity, cost efficiency, safety, and the overall impact on project timelines. The adoption of robotic technologies in construction has been particularly significant in Italy, where numerous projects have provided robots for tasks ranging from bricklaying to concrete pouring. Comparative studies in Europe have shown that robotic methods often outperform traditional techniques in terms of precision, speed, and safety, although challenges related to the initial costs and integration with existing systems remain.

Table 1. Key studies on robotic vs. traditional construction methods in Italy and Europe.

Construction Task	Robot Type	Comparison Focus	Key Findings	Source	Reference
Concrete pouring	Robotic Concrete Pump	Precision, Safety	Enhanced precision, 30% reduction in accidents on-site	(Rashid, Abdullah, Ismail, & Saberi, 2019)	[43]
Structural assembly	Robotic Arm	Time, Cost	25% faster assembly, 10% cost savings	(Melenbrink, Werfel, & Menges, 2020)	[14]
Prefabricated wall installation	Mobile Robotic Crane	Efficiency, Integration	Increased efficiency, challenges in system integration	(Gharbia, Chang-Richards, Lu, Zhong, & Li, 2020)	[46]
Road construction	Autonomous Paver	Time, Labor	Reduced labor needs, 40% faster completion	(Delgado, et al., 2019)	[7]
Tunnel boring	Robotic TBM	Safety, Time	Significant safety improvements, 35% faster boring process	(Xiao, Chen, & Yin, 2022)	[19]
Facade construction	Robotic Scaffold	Safety, Precision	Improved precision, 25% reduction in on-site injuries	(Gharbia, Chang-Richards, Lu, Zhong, & Li, 2020)	[46]
Concrete wall fabrication	Robotic Wall Builder	Cost, Productivity	18% reduction in costs, 22% increase in productivity	(Pan, Linner, Pan, Cheng, & Bock, 2018)	[30]
Various (Collaborative Robotics)	Collaborative Robots	Safety, Robustness, Interactivity	Evolution from pure automation to collaborative and adaptive robotics in construction	(Parascho, 2023)	[57]
Concrete Printing	Robotic Concrete Printer	Feasibility, Design Innovation	Discusses the potential of robotic concrete printing in large-scale construction	(Codarin, 2023)	[58]
Various (Robotic and Sensor-Based Technologies)	Robotic Systems	Quality, Efficiency, Safety	Reviews advancements in robotics and sensor technologies in construction	(Nath, 2022)	[59]
Sustainability in Construction	Construction Robotics	Sustainability, Efficiency	Proposes a system for measuring sustainability efficiency of construction robotics	(Younis, 2022)	[60]
Timber Construction	Robotic Construction Systems	Efficiency, Accuracy	Evaluates robotic construction of timber buildings, highlighting improvements in efficiency	(Wang, Naito, Leng, Fukuda, & Zhang, 2022)	[61]
AEC Industry	Automation in AEC	Productivity, Management	Maps the state of automation in AEC, identifying key technological frontiers	(Klarin & Xiao, 2023)	[62]

summarizes key studies from Italy and other European countries that have contributed to this field.

2.3. Gap and Research Scope

Despite the growing interest in automation and robotics within the construction industry, particularly in Europe and Italy, there remains a significant gap in understanding how these technologies impact time and cost in specific project contexts. While many studies have highlighted the potential benefits of automation, such as increased productivity, enhanced safety, and reduced labor costs, there is a lack of detailed, case-specific analyses that explore these impacts in real-world scenarios. Existing research often focuses on industry-wide trends or isolated technological applications, leaving a critical need for in-depth research that examines the integration of automated machines within specific projects.

This study addresses this gap by examining a construction project in Italy, where the adoption of automated machines is analyzed to understand its effects on project timelines and costs. The research aims to provide practical insights into the benefits associated with integrating robotic technologies in construction. Understanding how automation influences the efficiency and economic outcomes of a real-world project in Italy will contribute significantly to the broader knowledge base on construction automation, particularly within the Italian context.

The scope of this research includes a comparative analysis of traditional construction methods versus those that incorporate automated technologies, such as autonomous bricklayers, robotic concrete pumps, and other advanced machines. The study will evaluate the impact of these technologies on project duration and budget, offering concrete evidence of their potential to improve construction practices.

3. Methodology

3.1. Research Design

The research focused on examining the market availability of automated machines for construction, specifically evaluating their potential applications in a selected case study to assess the time and cost implications in a real-world context. The case study involved the construction of a small family house designed for small couples or single occupants, completed during 2022–2023.

The research methodology involved a detailed analysis of the residential unit’s characteristics, including identifying the construction phases, grouping the sequence of works, and calculating execution times. This was performed to facilitate a comparison between traditional construction methods and the potential use of automated machines. Based on insights from the literature review and research findings, a selection of automated machines was identified, targeting those that could be feasibly applied to the specific tasks involved in constructing the residential unit.

The most advanced and suitable automated machines available on the market were identified for analysis, focusing on their time and cost efficiency in production. The selection criteria prioritized machines with the highest productivity rates for the relevant construction tasks. A theoretical application of these automated machines was then simulated to estimate their impact on the construction process.

Figure 1 illustrates the research methodology framework, including the key phases of research design, data collection, and analytical framework. Each component is color-coded to differentiate between the design, data collection, and analysis phases, showing the flow and connections between different parts of the research process.

3.2. Data Collection

Research comprehensive review was conducted to gather relevant research and insights on the adoption of automated machines in construction, with a particular focus on their application in small residential projects. The review was carried out using a variety of academic databases, including Scopus, IEEE Xplore, websites, and Google Scholar, to ensure a broad and inclusive search of the available literature.

The search strategy involved the use of specific keywords and phrases to capture a wide range of studies related to the research topic. Keywords such as “construction automation”, “robotic construction”, “automated construction machines”, “residential construction automation”, “productivity in construction robotics”, and “cost analysis of construction automation” were employed to locate relevant articles, conference papers, and technical reports.

The initial search yielded a large number of studies, which were then screened for relevance based on their titles and abstracts. The inclusion criteria focused on studies that addressed the implementation and impact of automated machines, specifically in the context of small to medium-sized residential construction projects. Studies that discussed broader industrial or commercial applications were included only if they provided insights that could be applicable or adaptable to residential construction.

Additionally, the review prioritized studies that included empirical data, case studies, or comparative analyses between automated and traditional construction methods. This approach ensured that the selected studies not only offered theoretical perspectives but also provided practical, evidence-based insights that could inform the research.

Further refinement of the selected sources involved a detailed review of the full texts, focusing on studies that provided quantitative data on productivity, cost, and time efficiency associated with the use of automated machines. The review also included an examination of reports and papers that discussed the challenges and limitations of adopting automation in construction, such as initial costs, integration with existing systems, and the availability of technology for specific construction tasks.

The final set of studies selected for inclusion in this research offered a comprehensive overview of the state of automation in construction, particularly within the European context. Special attention was given to research conducted in Italy and other European countries, aligning with the geographic focus of the case study. These studies provided critical insights into the potential benefits and challenges of automation in small residential projects, forming the basis for the subsequent analysis and simulation work conducted in this research.

3.2.1. Market Analysis

The market analysis focused on identifying and evaluating the availability of automated machines relevant to the construction industry, with an emphasis on their applicability to small residential projects. The analysis aimed to assess the current state of the market, including the range of technologies available, their capabilities, and their potential impact on construction time and cost.

The first step involved an extensive search of industry reports, manufacturer catalogs, and market databases to identify automated machines that are currently available for construction tasks.

Sources such as construction equipment manufacturer websites, industry publications, and market intelligence platforms like Statista and IBISWorld were consulted to gather data on the latest advancements in construction automation technologies.

A key part of the market analysis was the identification of automated machines that could be applied to the specific tasks involved in the case study, namely the construction of a small family house. The analysis focused on machines designed for tasks such as bricklaying, concrete pouring, structural assembly, and finishing work, which are common in residential construction. The criteria for selecting these machines included their productivity rates, cost-efficiency, ease of integration with existing construction practices, and their adaptability to small-scale projects.

To ensure a comprehensive understanding of the market, the analysis also considered the geographic availability of these machines, particularly in Europe and Italy. This was important to align with the case study’s context and to assess the feasibility of adopting these technologies in the Italian construction industry. The availability of local suppliers, maintenance services, and technical support were also factors taken into account during the selection process.

The machines identified through this process were then categorized based on their applicability to different phases of the construction process. A comparative analysis was performed to evaluate the selected machines against traditional construction methods, focusing on key performance indicators such as time savings, cost reductions, and improvements in work quality.

One of the critical challenges encountered during the market analysis was the limited availability of automated machines for certain specialized construction tasks, such as mechanical, electrical, and finishing work. This limitation highlighted the current gaps in the market and underscored the need for further development and innovation in construction automation technologies.

3.2.2. Case Study Data

The selected case study focuses on a small residential unit constructed using traditional methods and techniques in Italy, specifically in the Veneto Region on the northeastern side of the country. This house, built during 2022–23, was designed for a small family or a single occupant, with a total area of approximately 100 square meters. The project offers a standard example of residential construction in a European context, making it suitable for evaluating the potential application of automated machines across similar projects in other countries with comparable conditions.

The residential unit (Figure 2) comprises a front porch, a double-height entrance, a living room, a kitchen, a dining room, and a bathroom on the ground floor, with a double bedroom located upstairs (Figure 3). The porch serves a dual purpose, allowing for vehicle parking and functioning as an outdoor sitting space (Figure 4). The internal layout is simple and straightforward, which makes it an ideal candidate for exploring the integration of automated construction technologies.

Several key parameters were considered in selecting this case study:

• Site Selection: The project is situated in Italy under standard European conditions, characterized by a residential independent unit located in a flat area, making it representative of typical construction sites in the European Union.
• Climate and Soil: The house is located in a climate and soil context typical of many European countries, ensuring the findings are broadly applicable across the region.
• Logistics and Accessibility: The site offers easy accessibility for the logistics and storage of materials, which is critical for the smooth operation of automated machines.
• Affordability: The house was constructed with a budget appropriate for average economic conditions, using traditional techniques and an average investment of resources and manpower. This aspect is important for evaluating the cost-effectiveness of introducing automation.
• Construction Timeline: The project timeline was unaffected by delays or issues from the construction company, providing a reliable baseline for comparing traditional and automated construction methods.
• Construction Period: The construction period was typical for a residential unit of this size and complexity, allowing for meaningful comparisons between the actual time taken and the potential time savings offered by automation.
• Layout Simplicity: The villa’s straightforward internal layout allows for the potential application of automated machines without significant limitations that could affect cost and time efficiency.
• Material and Finishing: The house was built using traditional materials and standard finishing, ensuring that any automation applied would be relevant and easily integrated into similar projects.

Data for the case study were thoroughly collected from various sources. The primary data were derived from project documentation provided by the construction company, including architectural plans, construction schedules, and detailed cost breakdowns. These documents offered essential insights into the building’s design, construction phases, and financial aspects, providing a solid foundation for the subsequent analysis.

3.3. Analytical Framework

3.3.1. Construction and Plan Phase Analysis-Cost and Time

The construction of the residential house in Dalle Fratte—Arqua Petrarca was a project that involved detailed planning and execution across various phases. The project emphasized the importance of proper storage and logistics, ensuring that materials and tools were delivered to the right location at the right time. This initial phase (

Table 2. Comparison of planned vs. executed costs, time, and production rates for various construction.

Item	Unit	Planned Cost (€)	Planned Days	Cost/Day (€)	Planned Production Rate	Executed Cost (€)	Executed Days	Production Rate	Executed Production Rate
Storage and logistics of materials	sqm	4411.76	12	367.65	2.083	6250	17	mq/day	1.47
Excavation	sqm	3579.23	9	397.69	12.22	5170	13	mq/day	8.46
Scaffolding installation	sqm	5280	7	754.29	34.28	5280	7	mq/day	34.28
Rck 250 Concrete Installation	mc	9750	13	750	3.84	13,500	18	mc/day	2.77
Elevated external masonry	sqm	6540.8	12	545.07	6.08	8176	15	mq/day	4.86
Inclined timber roof	sqm	14021.05	16	876.32	5.62	16,650	19	mq/day	4.73
Internal gypsum wall partition	sqm	3220	14	230	1.64	3220	14	mq/day	1.64
Roof tiles installation	sqm	8224.62	11	747.69	8.18	9720	13	mq/day	6.92
External civil plaster	sqm	2463.16	13	189.47	6.15	3600	19	mq/day	4.21
Internal civil plaster	sqm	3000	8	375	12.5	3000	8	mq/day	12.5
Floor ceramic tiles	sqm	5246	5	1049.2	17.2	5246	5	mq/day	17.2
White laminated PVC doors and windows	sqm	9720	7	1388.57	3.24	9720	10	mq/day	2.27
High-quality interior painting	sqm	1800	5	360	20	3600	10	mq/day	10
High-quality exterior painting	sqm	3584	8	448	10	4480	10	mq/day	8
Site cleaning and closure	sqm	2249.78	5	449.96	20.2	4499.55	10	mq/day	10.1
Scaffolding dismantling	sqm	1499.85	5	299.97	20.2	2999.7	10	mq/day	10.1
Total		84,590.25				105,111.3

), which included transportation, stock control, and warehousing, was planned with a budget of €4411.76 over 12 days. However, the actual cost rose to €6250.00, and the duration extended to 17 days.

As the project moved into the more intensive phases of construction, including excavation and structural works, further cost increases and time extensions were observed. The excavation of the site, which involved mechanical excavation and potential rock demolition, was originally planned at a cost of €3579.23 over 9 days. However, the executed cost escalated to €5170.00, requiring an additional 4 days. Similarly, the installation of Rck 250 concrete for the foundation slabs, which was critical for ensuring the structural integrity of the house, saw a significant rise in cost from the planned €9750.00 to €13,500.00, with the duration extending from 13 to 18 days. These increases likely reflect unforeseen complexities in the ground conditions and additional reinforcement requirements, which are common challenges in construction projects of this scale.

The project also included detailed work on masonry, roofing, and internal and external finishes, all of which required careful attention to detail and quality. The external masonry, made of modular brickwork, and the inclined timber roof were both areas where the project experienced cost overruns and extended timelines. The masonry work, initially budgeted at €6540.80, ended up costing €8176.00, and the roofing work increased from €14,021.05 to €16,650.00. These phases were critical to the overall stability and esthetic of the house, and the increases in time and cost were necessary to ensure that the work met the high standards required. Similarly, the internal and external plastering and painting phases saw cost increases, reflecting the effort required to achieve a flawless finish that would meet the client’s expectations.

The final stages of the project, including the installation of flooring, doors, windows, and the final site cleaning and closure, also experienced variations between the planned and executed costs. While the tiling and the installation of white laminated PVC doors and windows were completed largely within budget and time, the painting phases saw significant cost increases, with the interior painting costs doubling from €1800.00 to €3600.00. The project’s conclusion, which involved thorough site cleaning and closure, also exceeded the initial budget, reflecting the meticulous work required to prepare the property for handover. Overall, the total cost of the project increased from the planned €84,590.25 to €105,111.25, highlighting the inherent challenges of managing a construction project of this complexity and the importance of allowing for flexibility and contingency planning to accommodate unforeseen circumstances.

3.3.2. Traditional Methodologies for Construction

The analysis of the constructed residential unit involved an examination of the project’s various phases and work sequences. The construction process was systematically divided into distinct phases, each representing a critical set of activities necessary for the successful completion of the project. To ensure a thorough evaluation, these phases were further categorized into key interventions, which served as parameters for comparison when considering the potential for automation. These categories included mobilization and logistics, soil excavation and treatment, structural elements, brick walls, ceiling installation, timber roofing, plastering, painting, tiling and finishing, and a multitask survey.

The mobilization and logistics phase encompassed the setup and organization of the construction site, focusing on the efficient transportation and storage of materials and tools. This was important for preventing delays and ensuring that all resources were available when needed. Soil excavation and treatment involved preparing the building site through mechanical excavation and soil stabilization, forming the foundation for the structure. The construction of the building’s core structural elements, such as foundations, columns, and beams, was another critical phase. These elements were analyzed to determine whether tasks like concrete pouring and reinforcement installation could be automated.

Brick wall construction was a key phase where the automation potential was significant, particularly with the use of robotic bricklaying machines. The ceiling installation phase involved tasks such as the placement of support beams and panels, which were assessed for potential time savings and precision improvements through automation. The construction of the timber roof required the assembly of trusses and the installation of roofing materials. Automation in this phase could ensure consistent quality and reduce the labor intensity of these tasks.

Plastering was analyzed for efficiency improvements through automated plastering systems, which could apply plaster to walls and ceilings more uniformly and quickly than manual labor. The painting phase was evaluated for its potential to be automated, particularly in large surface areas where robotic painting systems could enhance speed and ensure uniform coverage. The tiling and finishing phase included the installation of tiles and other final touches, where automation could lead to precise placement and consistent quality. Lastly, the multitask survey involved assessing the potential for automated machines to handle multiple construction tasks simultaneously, which could significantly enhance overall project efficiency and reduce timelines.

Each of these categories was analyzed to identify critical tasks that could benefit from automation, aiming to streamline the construction process and improve overall efficiency.

3.3.3. Automated Machines for Construction

In the mobilization and logistics phase of construction, the adoption of autonomous systems like the Autonomous Excavator System (AES) and the Volvo HX2 load carrier has shown significant promise in increasing efficiency, reducing dependency on human labor, and minimizing environmental impacts. These advancements are further enhanced by ROBO’s suite of autonomous heavy equipment, including bulldozers, excavators, and wheel loaders tailored for soil treatment, grading, and material-handling tasks.

The AES excels in material loading and soil excavation, handling 36.25 cubic meters per hour with a 6.5-ton excavator and completing up to 145 excavation and dumping operations per hour. The Volvo HX2 load carrier, with a 15-tonne capacity, has been integral in reducing carbon emissions by 98% and cutting energy costs by 70%, as demonstrated in the Electric Site project. Additionally, ROBO’s autonomous machinery has increased productivity by 63% over traditional methods and saved approximately $65,450 per machine annually through continuous 24 h operation and optimized fuel consumption.

In the structural phase, automation is rapidly advancing with technologies like 3D printing. The PassivDom 3D Printing Robot can construct a 410-square-foot building in about 8 h, utilizing materials such as carbon fibers, polyurethane, and fiberglass. Similarly, the ICON 3D Printing Robot, which constructs a 650-square-foot building in around 12 h using concrete, offers a practical solution to the global affordable housing crisis. This technology enables quick, cost-effective construction, as demonstrated by ICON’s partnership with New Story to build homes in El Salvador.

In reinforcing structures, the TyBOT and IronBot robots are revolutionizing rebar installation. TyBOT ties up to 1100 intersections per hour, significantly accelerating the process and reducing labor costs. IronBot complements this by carrying and placing rebar bundles weighing up to 5000 pounds, increasing productivity by 250%. Together, these robots provide 50% schedule savings in rebar installation, enhancing both efficiency and safety on construction sites.

The Hadrian X bricklaying robot marks a significant leap in masonry automation, laying up to 1000 bricks per hour. This technology reduces construction time, improves accuracy, and lowers costs by minimizing human intervention. Similarly, the Hilti Jaibot drilling robot streamlines ceiling installations by automating drilling tasks, working for up to 8 h per charge, and integrating digital plans for precise execution.

Timber construction has also benefited from automation with the WoodFlex 56 gantry robot, which handles complex tasks, such as cutting, milling, and nailing large timber boards. The robot’s direct integration with CAD data ensures seamless and accurate timber construction, reducing errors and increasing productivity.

In the finishing stages, the Acme Plastering Robot can perform the work of up to eight workers, ensuring consistent and high-quality plastering over large surfaces. Similarly, the Okibo robot triples the speed of painting and plastering tasks compared to traditional methods, while the Dusty Robotics Field Printer revolutionizes field layout by translating digital models into full-scale floor layouts 10 times faster than conventional methods.

Tile placement has also been optimized with a robot developed by Future Cities Laboratory, capable of setting tiles twice as fast as human workers. The Baubot Multi-Task Construction Robot offers a versatile solution for various tasks, including 3D printing, concrete drilling, and painting, enhancing productivity across multiple construction phases.

Finally, the Phantom 4 RTK Drone by DJI provides precise 3D mapping and surveying capabilities, with centimeter-level accuracy in positioning data. This drone is essential for detailed site planning and monitoring, ensuring that construction projects are executed with precision and efficiency.

3.3.4. Theoretical Simulation

The theoretical simulation of automation in construction serves as a critical tool in evaluating the potential benefits of integrating advanced technologies into traditional workflows. This simulation process involves comparing the productivity, cost savings, and environmental impact of automated systems against conventional construction methods, providing a comprehensive understanding of how automation can transform the industry.

To begin the simulation, we carefully selected a range of automated machines based on their relevance to specific construction tasks and their proven capabilities in enhancing efficiency (

Table 3. Application of autonomous systems in construction.

SCOPE	Type	Product Name	Job	Productivity Rate	Source	Reference
Mobilization and Logistics	Autonomous Excavator	Autonomous Excavator System	Material loading and soil excavation	The system can continuously operate for 24 h without any human assistance. The amount of material handled per hour is closely equivalent to that of an experienced human operator.	(Zhao, et al., 2020)	[52]
Loading and Hauling	Autonomous Load Carrier	Volvo HX2	Loading and hauling materials	The Volvo HX2 has a 15-tonne hauling capacity, with a load capacity to machine weight ratio twice as high as a standard load carrier. It achieved a 40% reduction in operator costs and a 70% cut in energy costs.	(Ltd., QMJ Group., 2019)	[63]
Soil Treatment	Autonomous Bulldozers, Excavators, and Wheel Loaders	ROBO Heavy Equipment	Soil treatment, grading, and material handling	ROBO’s autonomous heavy equipment increases productivity by 63% compared to standard equipment. The system also allows for 24 h continuous operation, resulting in $65,450 in annual savings per machine.	(Inc., Robo Industries., 2024)	[64]
Soil Compacting	Autonomous Compacting Roller	ROBOMAG	Soil compacting	The ROBOMAG system is equipped with GPS, Lidar, and advanced position sensors to perform fully autonomous soil compaction, offering increased safety and comprehensive compaction documentation via ASPHALT MANAGER 2.	(BOMAG GmbH., n.d.)	[65]
Structure Reinforcement	3D Printer	PassivDom 3D Printing Robot	Building the structural elements of the superstructure	The PassivDom 3D Printing Robot can construct a one-story building of 410 square feet in about 8 h, using materials like carbon fibers, polyurethane, and fiberglass.	(Garfield, A robot can print this $64,000 house in as few as 8 h—, 2017)	[66]
Structure Reinforcement	3D Printer	ICON 3D Printing Robot	Building the structural elements of the superstructure	The ICON 3D Printing Robot can construct a one-story building of 650 square feet in approximately 12 h, using concrete for the walls, roof, and floor.	(Garfield, A Robot Can Build This $10,000 House Within 12 h—, 2018)	[66]
Structure Reinforcement	Rebar Tying Robot	TyBOT	Tying rebar intersections	The TyBOT rebar tying robot ties up to 1100 intersections per hour, significantly speeding up the rebar installation process and reducing labor costs.	(Advanced Construction Robotics, Innovating Infrastructure: Modern Equipment for Modern Crews, 2023)	[67]
Structure Reinforcement	Rebar Placing Robot	IronBot	Carrying and placing rebar	The IronBot can carry up to 5000-pound bundles of rebar, increasing productivity by 250% compared to traditional methods.	(Advanced Construction Robotics, Key Features of IronBOT, 2023)	[68]
Walls (External and Partitions)	Bricklaying Robot	Hadrian X	Bricklaying	The Hadrian X bricklaying robot lays up to 1000 bricks per hour, equivalent to the daily output of two human bricklayers.	(Fastbrick to Build Its Second Bricklaying Robot, 2017)	[69]
Ceiling Installation	Drilling Robot	Hilti Jaibot	Ceiling drilling for installations	The Hilti Jaibot works for 8 h per charge, improving efficiency, reducing on-site issues, and optimizing system design with increased accuracy.	(Hilti, 2023)	[70]
Timber Roof Construction	Gantry Robot	WoodFlex 56	Timber handling and assembly	The WoodFlex 56 robot, equipped with a tool-changing system, performs various tasks such as handling large timber boards, shooting nails, and cutting, leading to efficient and precise timber roof construction.	(AG, 2023)	[71]
Plastering	Plastering Robot	Acme Plastering Robot	Plastering	The Acme Plastering Robot can take on the job of up to eight workers, ensuring efficient and consistent application of plaster with reduced manual labor.	(Ltd, ACME Equipment Pte, 2023)	[72]
Painting (Outdoor and Indoor)	Painting and Plastering Robot	Okibo	Painting and plastering	The Okibo robot is 3 times faster than traditional methods, capable of performing both painting and plastering tasks efficiently.	(Smart Robotics for Construction Sites, 2021)	[73]
Field Layout	Field Printer	Dusty Robotics Field Printer	Layout of engineering drawings	The Dusty Robotics Field Printer can lay out engineering drawings and models on-site up to 10 times faster than traditional methods, turning digital designs into full-scale layouts.	(BIM-Driven Layout: Only From Dusty Robotics, 2024)	[74]
Tile Placement	Tile Placement Robot	Future Cities Laboratory/ROB Technologies AG Robot	Tile placement	The tile placement robot can set field tiles twice as fast as a human, though it requires a human tender to mix mortar, grout, and cut and install anything that is not a full tile.	(Frane, 2017)	[75]
Multi-Tasking	Multi-Task Construction Robot	Baubot	Supports several construction applications including concrete 3D printing, reinforced concrete drilling, formwork milling, micro-trenching, plasma cutting, sanding, and painting	Boosts the efficiency and productivity in several construction tasks by automating a wide range of operations.	(Zhao, et al., 2020)	[76]
Surveying	Drone	Phantom 4 RTK	3D mapping	The Phantom 4 RTK drone is equipped with a centimeter-level accurate RTK module and TimeSync system, capturing precise 3D mapping data with an accuracy of up to 1 cm horizontally and 1.5 cm vertically.	(Ltd., QMJ Group, 2019)	[77]

). Among the machines chosen were the Autonomous Excavator System (AES), which can continuously perform material-loading and soil excavation tasks, and the Volvo HX2 load carrier, known for its impressive 98% reduction in carbon emissions. Additionally, advanced systems like ROBO’s autonomous heavy equipment, including bulldozers and excavators, were considered for their ability to increase productivity by up to 63% compared to standard machinery.

The simulation methodology involved several key steps: First, we calculated the productivity rates for each selected machine and compared them to traditional methods. For instance, while traditional excavators typically handle 15–20 cubic meters of material per hour, the AES demonstrated a remarkable capacity of 36.25 cubic meters per hour. This comparison was extended across various tasks, such as soil treatment, bricklaying, and rebar placement, with automated systems consistently showing superior performance.

In addition to productivity, we estimated cost savings by examining the reduction in labor, time, and operational expenses associated with automated systems. ROBO’s autonomous equipment, for example, was projected to save approximately $65,450 per machine annually, primarily through optimized fuel consumption and reduced reliance on human labor. These savings were a significant factor in the overall economic assessment of automation.

Environmental impact was another crucial aspect of the simulation. We assessed the reduction in carbon emissions and energy consumption achieved by using automated systems. The Volvo HX2 load carrier’s 98% reduction in carbon emissions, coupled with a 70% cut in energy costs, exemplified the substantial environmental benefits that automation can bring to construction projects.

3.3.5. Environmental Impact Assessment

The environmental impact of both traditional and automated construction methods was assessed using a combination of empirical data and standardized calculation methodologies. For traditional methods, baseline environmental data were derived from project documentation, industry benchmarks, and relevant literature. For automated systems, data were gathered from real-world case studies and manufacturer specifications, such as the Volvo HX2’s energy and emission metrics.

The calculation of carbon emissions followed a standardized approach using emission factors, which relate the amount of greenhouse gasses emitted to specific energy consumption levels. For example, emissions from diesel-powered equipment were estimated using conversion factors, such as kilograms of CO₂ per liter of diesel burned. Automated systems powered by electricity were assessed using energy consumption data and the carbon intensity of the electricity grid in the study area. Energy consumption reductions were calculated as the difference between the energy used by automated equipment and the average energy required by traditional methods for similar tasks.

Additional environmental benefits, such as reductions in material waste, were integrated into the assessment by quantifying the impact of increased precision and reduced rework in automated systems. For example, automated bricklaying machines, which minimize material wastage through accurate placement, were modeled to estimate the reduction in raw material requirements compared to traditional bricklaying methods. Environmental metrics for each construction phase were normalized per cubic meter or square meter to allow direct comparison and ensure consistency across activities.

3.3.6. Safety Analysis

The safety analysis quantified the reduction in risk exposure achieved through the adoption of automated construction technologies. This analysis was based on historical safety data for traditional methods and performance specifications of automated systems. The number of reported incidents for specific tasks, such as rebar placement, roofing, and painting, was used as a baseline to estimate the likelihood of accidents under traditional construction practices.

For automated systems, safety improvements were calculated by evaluating features like obstacle detection, geofencing, and automated emergency stops. For instance, the use of LiDAR and sensor-based systems in automated excavators was shown to reduce collision risks, while geofencing ensured machines operated only in designated safe zones. Risk reduction was quantified as the percentage decrease in the number of workers exposed to hazardous tasks. For example, automated systems replacing manual labor in high-risk activities like roofing were modeled to estimate the reduction in worker exposure and the corresponding decrease in potential injuries.

The improvements were calculated as a percentage reduction in incident rates by comparing task-specific risks in traditional methods with those in automated operations. These calculations were validated using data from field implementations and manufacturer reports. To ensure accuracy, this study incorporated variations in task complexity and site conditions, providing a comprehensive framework for assessing safety enhancements.

4. Results and Discussion

The integration of automated systems into various construction tasks has led to remarkable improvements in productivity compared to traditional methods. The analysis of productivity across different construction activities reveals the substantial efficiency gains achieved through the deployment of advanced robotics and automation technologies.

In the mobilization and logistics phase, the introduction of autonomous systems such as the Autonomous Excavator System (AES) and Volvo HX2 load carrier has resulted in a significant doubling of productivity compared to traditional methods (Figure 5). Although this phase typically exhibits low productivity rates, the implementation of automation has notably reduced project timelines and labor requirements, making the process more efficient and cost-effective.

For soil treatment, the adoption of ROBO’s autonomous heavy equipment has led to a 63% increase in productivity over traditional methods. These autonomous machines can perform soil treatment tasks with greater speed and precision, which not only enhances overall efficiency but also contributes to a more streamlined construction process. When it comes to structural elements, the use of 3D printing technology, particularly through the ICON and PassivDom 3D Printing Robots, has revolutionized the construction of building structures. These automated systems can rapidly construct basic building structures within hours, a significant improvement over manual method.

In the bricklaying sector, the Hadrian X robot stands out by achieving the daily output of two skilled bricklayers in just one hour. This remarkable feat demonstrates the potential of automation to drastically speed up masonry work while maintaining a high level of accuracy. For rebar placement, the introduction of TyBOT and IronBot robots has led to a dramatic increase in productivity. TyBOT, capable of tying up to 1100 intersections per hour, and IronBot, which increases rebar placement productivity by 250%, have collectively transformed this traditionally labor-intensive task.

The comparison of cost savings and environmental impact between traditional and automated construction systems reveals significant benefits in favor of automation (Figure 6). The integration of automated technologies across various construction tasks reduces costs and minimizes the environmental footprint of construction projects.

In terms of cost savings, the deployment of automated systems in tasks such as rebar placement and bricklaying demonstrates the highest financial benefits. For instance, automation in bricklaying resulted in cost savings of approximately $12,000, primarily due to the drastic reduction in labor costs and increased efficiency. Similarly, rebar placement automation with robots like TyBOT and IronBot has led to substantial savings of around $8000. These savings are primarily attributed to the robots’ ability to perform tasks at a much faster rate and with higher precision, reducing the need for rework and the associated labor costs. Soil treatment also benefits significantly from automation, with cost savings reaching around $3500.

The environmental impact of automated systems is equally impressive, particularly in the soil treatment phase, where a 63% reduction in environmental impact was observed. This reduction is largely due to the decreased fuel consumption and lower emissions from autonomous equipment like the Volvo HX2 load carrier, which demonstrates a 98% reduction in carbon emissions. Additionally, timber roof construction automation through systems like the WoodFlex 56 robot has led to a 50% reduction in environmental impact, emphasizing the eco-friendly advantages of integrating robotics into construction.

The comparison of time savings between traditional and automated construction systems further underscores the advantages of automation in enhancing the efficiency of construction projects (Figure 7). The analysis reveals that the use of automated systems significantly reduces the time required to complete various construction tasks, leading to faster project completion, increased productivity, and a reduction in indirect costs.

For example, the bricklaying task, traditionally requiring up to 20 days to complete, can be drastically reduced to approximately 10 days using automated systems such as the Hadrian X bricklaying robot. This halving of the time required demonstrates the immense efficiency of automation, where the robot can lay up to 1000 bricks per hour, a rate equivalent to the daily output of two skilled human bricklayers.

Similarly, rebar placement sees a substantial reduction in time from 15 days traditionally to just 7 days with the use of robots like TyBOT and IronBot. These robots not only speed up the process but also ensure consistent and accurate placement, which is critical for maintaining the structural integrity of the construction.

Soil treatment is another area where automation proves highly effective, reducing the time required from 10 days traditionally to just 5 days when using autonomous equipment like bulldozers and excavators. The continuous operation capability of these machines, coupled with advanced AI systems, allows for a significant acceleration of the soil treatment process.

In tasks such as painting and plastering, the use of robots like Okibo and Acme plastering robots reduces the time required by approximately 50%, highlighting the efficiency gains in finishing tasks as well. The Okibo robot, for instance, can perform these tasks three times faster than traditional methods, ensuring that large surfaces are covered quickly and uniformly.

The data in Figure 8 illustrate that the number of workers needed is cut by more than half in tasks such as rebar placement, bricklaying, and plastering when automated systems are utilized. For example, rebar placement, which typically requires eighteen workers using traditional methods, can be handled by just five workers when using robots like TyBOT and IronBOT.

One of the most critical benefits of adopting automated systems in construction is the improvement in safety (Figure 9). Automated systems like those developed by ROBO Industries and others incorporate advanced safety features such as obstacle sensing, geofencing, and wireless emergency stops, which significantly reduce the risk of accidents on-site. The data show a marked improvement in safety across all tasks, with some tasks, like painting and timber roof work, showing up to 80% improvement in safety conditions. This enhanced safety protects workers and contributes to a more reliable and stable working environment, further justifying the investment in automation technologies.

Figure 10 illustrates the multi-tasking capabilities of various automated systems, highlighting their ability to handle multiple construction tasks simultaneously. Baubot, leading the chart, can handle up to ten different tasks at the same time, showcasing its versatility and efficiency in managing diverse construction operations. Tasks performed by Baubot include bricklaying, welding, material handling, mortar application, cutting, drilling, screwing and bolting, surface preparation, inspection, and cleaning. This broad range of tasks underlines Baubot’s adaptability and comprehensive functionality on construction sites.

Following closely is the WoodFlex 56, capable of managing eight tasks simultaneously, which emphasizes its advanced functionality in timber construction. The tasks it can perform include cutting, milling, drilling, nail shooting, and other operations specific to timber processing and assembly.

The Okibo robot, primarily designed for painting and plastering tasks, can manage seven different tasks, making it a versatile tool for both indoor and outdoor applications. Its tasks encompass surface preparation, paint or plaster application, and various finishing processes.

The TyBot, known for its rebar-tying capabilities, can handle six tasks, including rebar tying, cutting, bending, and other related operations. The IronBot, which focuses on rebar placement, can manage five tasks, such as positioning and securing rebar, along with additional supporting functions.

These multi-tasking capabilities of automated systems significantly enhance productivity and efficiency on construction sites, reducing the need for multiple specialized machines and minimizing the time required to switch between tasks.

5. Conclusions

The results of this study provide compelling evidence for the transformative impact of automation on the construction industry, demonstrating that for the case shown in this study, automated systems outperform traditional methods across multiple metrics, including productivity, cost savings, environmental impact, time savings, labor requirements, and safety improvements.

The productivity analysis clearly shows that automated systems offer substantial improvements over traditional methods, with an average productivity increase of 82.6%. For example, the Hadrian X bricklaying robot and ROBO’s autonomous heavy equipment significantly increase the speed and efficiency of construction tasks. Automated systems perform these tasks faster and with greater precision, reducing errors and the need for rework. This enhanced productivity is critical in an industry where time is often equated with cost, making automation an attractive option for large-scale construction projects.

The financial benefits of automation are evident, with significant cost savings averaging 40.6%, achieved through reduced labor and operational expenses. For instance, ROBO’s autonomous machinery saves approximately $65,450 per machine annually, while the Volvo HX2 load carrier achieves a 70% reduction in energy costs. Additionally, automation contributes to substantial environmental benefits, with an average 70.25% reduction in carbon emissions and energy consumption. This dual impact of cost and environmental efficiency positions automated systems as not only economically viable but also aligned with global sustainability goals.

The time savings associated with automated systems are particularly noteworthy, with an average reduction of 51% in project timelines. Tasks that traditionally take days to complete can be conducted in a fraction of the time, as evidenced by the efficiency of robots like IronBot and Hadrian X in rebar placement and bricklaying, respectively. This rapid completion of tasks accelerates project timelines and frees up human workers to focus on more complex and less physically demanding roles. The reduced labor requirement, in turn, helps address the growing labor shortages in the construction industry and improves overall job satisfaction.

One of the most significant advantages of automation is the improvement in worker safety. Automated systems minimize human exposure to hazardous tasks, resulting in marked improvements in safety outcomes, with reductions in risk exposure exceeding 70% on average. For example, ROBO’s equipment offers a 99% improvement in safety over traditional methods due to advanced features such as obstacle sensing, geofencing, and emergency stops. Furthermore, the multi-tasking capabilities of systems like Baubot and WoodFlex 56 highlight their versatility, allowing them to handle various tasks simultaneously and optimize resources on construction sites.

The integration of automation in construction represents a critical step toward achieving higher productivity, cost efficiency, sustainability, and safety. The findings from this study underscore the superiority of automated systems over traditional methods in addressing the key challenges facing the construction industry today, such as labor shortages, increasing project complexity, and the need for environmental sustainability.

As the industry continues to evolve, the adoption of advanced robotics and automation technologies is not just beneficial but necessary. These technologies offer a clear path to revolutionizing construction practices, making them more efficient, safer, and environmentally friendly. In conclusion, embracing automation will be key to the future success and competitiveness of the construction industry, ensuring that it meets the demands of a rapidly changing world.

6. Limitations and Future Studies

• This study focuses on a single case study in Italy, which limits the generalizability of findings to other regions or larger, more complex construction projects.
• This research assumes optimal performance of automated systems under ideal conditions without addressing real-world challenges such as technical malfunctions, site constraints, or learning curves for operators.
• The socio-economic impacts of automation on labor markets, including job displacement and the need for reskilling, shall be one of the main topics for future studies.
• Future studies should explore global comparative case studies to understand automation’s impact in varying economic, regulatory, and cultural contexts.
• Detailed lifecycle cost and environmental assessments of automated systems would provide a more comprehensive view of their long-term economic and ecological impacts.
• Investigating automation’s scalability to large-scale infrastructure projects, such as highways or commercial complexes, could demonstrate its broader applicability.
• Studying the resilience of automated systems under challenging conditions, such as extreme weather or uneven terrain, would improve their design and deployment strategies.