Volume 8
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The demand for construction continues to grow year after year, putting more pressure on the global value chain. Construction labor shortages worldwide, even across OEMs and Integrators that supply construction, makes us question if modular and off-site construction are really solving the manpower issue or just moving it somewhere else. Compounding this situation, and knowingly or unknowingly, the ongoing advocacy of project and construction management practices has pushed project practitioners, as well as many educational institutions, to maintain a strong focus on project administration (e.g., submittals, request for information, progress reporting and forecasting, etc.), creating a significant gap in how even experienced project teams engineer their production processes and operations.
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Beyond Subsidies: Creating Competitive Clean Energy Solutions by Rethinking Design and Delivery Through the Application of First Principles Thinking and Project Production Management
The global transition to net-zero emissions demands clean energy technologies that can operate at scale and cost parity with fossil fuels. However, most clean energy projects suffer from commercial unviability, technological inefficiencies, and geopolitical supply chain complexities, resulting in failures at Final Investment Decision (FID) gates. This paper examines how First Principles Thinking (FPT), combined with Project Production Management (PPM) and Operations Science (OS), can address these challenges by reengineering core assumptions and developing cost-effective, scalable solutions combined with a purpose-built delivery system that optimizes cost and schedule and improves delivery predictability.
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Addressing society’s evolving needs requires tackling interconnected issues – climate change, resource depletion, pollution, and biodiversity loss – simultaneously. The built environment’s longevity and interdependence demand strategic, long-term, and integrated governance. Yet siloed structures in government, regulation, and industry, along with fragmented data, hinder progress and obscure the insights needed to improve outcomes. Without urgent action, we risk cascading system failures, economic harm, and widespread hardship. To create better outcomes where people and nature thrive, planners must understand the system of systems we rely on.
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A good project plan is not a guarantee for success, but a bad project plan is always a guarantee for failure. Effective project planning relies on a combination of activity-based (work breakdown structures, critical path analyses, etc.) and object-based (flow, critical chain, advanced work packaging, etc.) approaches. However, a critical yet often-overlooked challenge in either approach is the inherent estimation error, which leads to flawed models, unrealistic schedules, and erratic workflows. Systematically, we underestimate both task durations and the variability of those durations, resulting in overly optimistic projections that fail to capture the complexities of the real world.
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As the construction industry faces compounded challenges—labor shortages, rising material costs, inefficient supply chains, and the climate crisis—mass timber emerges as a compelling solution. Mass timber, as a forestry product, provides a sustainable solution to supply chain challenges and tariff impacts in construction. Produced off-site, it reduces labor, shortens construction time, and decreases transportation costs. Local sourcing strengthens supply chain resilience and reduces emissions. Mass timber offers an alternative to imported materials like steel and concrete, mitigating tariff-induced cost increases. As a renewable resource, mass timber also reduces the carbon footprint of construction, offering a durable, fire-resistant, and environmentally friendly option, fostering building projects’ circularity.
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An Operations Science and Production System Optimization-Based Approach to Evaluate Implementation of Robotic Wastewater Testing Platform in China
Timely and accurate wastewater chemical testing in wastewater treatment plants is essential to confirm compliance with environmental standards and to correct operational problems. In China, trained laboratory analysts manually perform the sampling and testing tasks required by regulations. However, with increasingly stringent environmental regulations and growing complexity in testing protocols, laboratories in these facilities are experiencing capacity constraints. While switching to robotic testing solutions present a promising solution to augment laboratory analysts’ capacity, plant managers face challenges in quantifying its benefits on daily operations to justify the upfront investment.
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Capital projects consistently underperform despite advancements in planning, digital tools, and enterprise reporting. One key contributor is the continued reliance of conventional metrics, originally designed for administrative oversight, to manage and control production. These metrics fail to reflect the true nature of execution: variability, flow, bottlenecks, and system dynamics. This paper proposes an alternative measurement framework based on Operations Science (OS). Drawing from proven principles in manufacturing and complex project delivery, the framework emphasizes leading, prescriptive, and production-oriented metrics. It presents an approach for metric selection, analysis, and control supported by digital modeling tools that enables teams to predict, visualize, and optimize project production behavior in real time. This framework empowers capital project teams to transition from reactive management to proactive control, improving performance, reducing risk, and enabling better outcomes.
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Effect of Variable-Scope Work Packages on Project Contingencies and Other Production-Related Risk Indicators
This paper investigates how variability in the scope of construction work packages—particularly size-based differences in arrival and service times—affects project performance metrics like completion time, work-in-process (WIP), and cycle time (CT). Using discrete event simulation (DES), the study compares traditional M/M/1 queue behavior with more realistic production systems exhibiting scope-induced correlations with the goal of delivering analytical heuristics for DES results. Due to the transitory nature of construction projects, discrete event simulation is more appropriate than analytical methods. The findings reveal that even with equal average arrival and service rates, variability in scope introduces nonlinear effects on project duration and throughput due to correlations and sequencing. Managerial strategies like scope normalization, sequencing, and buffered releases are recommended to mitigate these impacts and reduce rework risks.
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Industrialized construction (IC) means many things to many people. It is a concept that has been rediscovered time and again. In recent years, interest in IC has been sparked anew thanks to the promise of increasingly affordable automation, readily available cloud computing, and AI driving innovation in our industry. While jumping on the bandwagon now may be more tempting than ever, individual companies—producers or investors—will want to articulate their rationale for moving towards IC.
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Capital projects often suffer from significant cost overruns and schedule delays. These issues are frequently caused by poor early alignment, fragmented communication, and a lack of understanding of how production flows impact project performance, leading to high-stress environments and jeopardized profits. Therefore, this study showcases how a Hospital project in California can overcome these industry challenges through a pioneering blend of Operations Science (OS) and the Last Planner System® (LPS). By leveraging proven metrics—Work in Process (WIP), Cycle Time (CT), and Throughput (TH)—the team systematically mapped design, permitting, fabrication, and installation into cohesive production flows. This fusion of OS insights with LPS’s collaborative planning identified a potential five-month reduction in the structural steel phase. The result of this study shows how OS reframes design and construction as integrated production systems, enabling real-time data analysis that goes beyond “complete or incomplete.” The team’s visual dashboards and weekly pull sessions improve alignment, drive early decision-making, and continuously adjust for fluctuations in demand, resulting in more predictable outcomes, less stress, and fewer cost overruns. Expected outcomes include bridging the gap by integrating OS metrics into LPS to drive better decision-making, accelerating schedules by applying OS concepts to structural steel, fostering proactive alignment through early cross-functional collaboration and real-time data insights, and providing scalable practices for future projects. The findings aim to advance the field of Project Production Management (PPM) by providing actionable insights and future academic and industry work.
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The construction industry faces a growing labor shortage, particularly in skilled trades, leading to increased costs and operational risks. Raise Robotics addresses this challenge with a modular robotic platform designed to automate high-risk, repetitive tasks on construction sites. By initially focusing on building envelope construction, the company demonstrated the value of its system in reducing schedule delays, cost overruns, and safety risks. Real-world deployments have validated its approach, with measurable time and cost savings reported by early partners like JR Butler. Built on a hardware-agnostic, perception-driven architecture, Raise’s platform supports a range of applications including layout, drilling, and fastening, with future expansions planned. This approach enables contractors to adopt automation without disrupting workflows, offering a scalable solution to workforce shortages while enhancing quality and safety across construction environments.
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Current construction management techniques center around the ‘iron triangle’ of scope/quality, schedule, and resource use, with the common understanding that only two of these three aspects can be optimized in a project. On the other hand, the Project Production Institute (PPI) advocates an Operations Science-based approach to managing projects using five levers invalidating the iron triangle. Those levers are product design, process design, capacity, inventory, and variability. Current methods available for analyzing these levers include Building Information Modeling (BIM) used for product design in the built environment, and operation science concepts and techniques like Little’s Law and Discrete Event Simulation (DES) for the other four levers.
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Computer Vision Model to Extract Production Data for Slab Concrete Pouring from Site Video Using YOLOv8
Construction teams in fast-cycle cast-in-place concrete work currently lack access to real-time and automated raw production data, including start and end time, the number and location of labor and equipment as resources, limiting their ability to efficiently and effectively model and control production. Without such data, construction teams are unable to make real-time decisions such as identifying delays and bottlenecks, creating and adjusting the best possible composition of the crews to maximize resource utilization and meet the target completion dates for activities, and efficiently reallocating labor and equipment during dynamic site operations. This research proposes a vision-based model that extracts raw production data (start and end time) from video footage to support real-time, data-driven production system modeling and control in cast-in-place concrete work.
Other Perspectives
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From Complexity To An Industrialized And Structured Production System: A Case Study On Takt Planning And Control
Construction projects frequently begin under conditions of high uncertainty, leading to complex situations in which both the final product and the execution process are not fully defined. Drawing on the Stacey Matrix [1], agile methods such as the Last Planner® System (LPS) [2] or Design Thinking [3] prove effective in initially navigating complexity through the integration of transparency and preventing the slide into chaos.
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Engineering Automation in Interception and Diversion Design: A Production Management Approach Using an Excel-Based Tool
Automation in early-stage infrastructure design remains limited in public sector contexts, where high-end digital tools are often inaccessible. In wastewater management, particularly Interception and Diversion (I&D) works, design workflows are still predominantly manual, leading to inconsistencies, delays, and suboptimal coordination across stakeholders.
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The engineering and construction industry is undergoing a transformative shift with the adoption of innovative practices aimed at enhancing project performance and competitiveness. Among others, Industrialized Construction has been utilized mainly in Europe and North America for over two decades. Based on a framework developed for IC housing projects, IC encompasses a broader approach that integrates nine components: planning and control of processes, developed technical systems, prefabrication, long-term relations, logistics, use of ICT, re-use of experience and measurements, customer and market focus, and continuous improvement.