Abstract

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. However, E&C industry practitioners often equate IC with offsite construction or “prefab,” overlooking its broader scope. This paper shifts focus to analyze how production systems provide a production-centric layer in an IC context, emphasizing the levers of production system optimization: process design, product design, variability, inventory and capacity. By examining the impact of these elements on the nine components, standardization, modularization, and physical decoupling, this study demonstrates how Project Production Management can facilitate the integration of these components in an IC context, by aligning them towards a common production goal and improving project performance.

Keywords: Project Production Management; Industrialized Construction; Operations Science; Production Systems; Integration.

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Introduction

The engineering and construction (E&C) industry continues to face significant challenges in terms of productivity, cost overruns, and schedule delays [1]. In response, the industry has embraced various innovative approaches for the last 30 years to improve project performance. One of these approaches is Industrialized Construction (IC), which offers a comprehensive framework for transforming traditional construction practices. While IC has been implemented across Europe and North America for over two decades [2], its full potential remains largely untapped due to misconceptions about its scope and application. A critical issue within the E&C industry is the common misconception that equates IC with merely offsite construction (or prefabrication), despite several authors defining IC as an integrated process that includes more components than prefab [2, 3, 4, 5, 6]. This reductionist view fails to capture the comprehensive nature of IC, and as a result, many IC initiatives fall short of achieving their intended benefits because they focus exclusively on prefabrication while neglecting other critical aspects of IC.

This paper addresses this problem by examining how Project Production Management (PPM), and its foundation of Operations Science (OS), can enable the integration of IC components. While previous studies have examined individual aspects of IC or PPM to specific construction challenges [7, 8, 9], there is limited research on how PPM can holistically enable the effective implementation of IC. This paper addresses the research question: How can PPM enable the effective integration of IC components? By leveraging the five levers of production system optimization (PSO) as an analytical framework, this study examines their role in harmonizing IC’s nine components from a production system perspective. Consequently, the objective of this paper is to develop the foundations of a coherent framework to demonstrate how PPM facilitates the systematic integration of IC practices beyond mere prefabrication.

Industrialized Construction

IC has evolved since its inception, yet its definition varies across literature. Qi et al. [10] states that IC involves a set of construction methods that advances the process from design through construction by employing intelligent manufacturing, automation, and digital techniques. UC Berkeley’s P2SL [11] defines IC as the fabrication of building components and systems by employing digital tools in a factory setting. PPI defines IC as “The application and use of high-volume manufacturing methods and technologies to the delivery of capital projects, including the use of product development, flow-based production processes and automation [13].” For clarity, this paper adopts the definition provided by Lessing & Berge [2], which states that IC represents “a systematic, controlled, and standardized production process of well-defined elements and building systems, which facilitates the collection of experiences from the design, production, and assembly of the building system as a basis for continuous improvements.” The selection of this definition is deliberate as it aligns with the integrative nature of IC that this paper seeks to explore. Figure 1 displays the nine components of the IC framework.

Building on Lessing’s conceptual framework, the IC approach presents a comprehensive system with nine integrated components. The framework emphasizes that IC extends beyond mere prefabrication, requiring a strategic focus that transcends singular projects. Within this framework [12], supply chain integration occurs across three dimensions: vertical integration (connecting phases from design through manufacturing to on-site assembly), horizontal integration (coordinating across different disciplines and trades), and longitudinal integration (transferring knowledge between projects over time). This multi-dimensional integration establishes a hierarchical approach where business strategy informs platform development, which then shapes production system design. The business strategy determines market positioning and customer segments, the platform strategy establishes the degree of standardization and customization, and the production system design implements the physical manifestation of these strategies through specific processes, technologies, and organizational structures. For more in-depth insights into this IC framework, go to [2, 3, 12].

Project Production Management

OS is defined by the PPI as “the study of the transformation of resources to create and distribute goods and services” [13], focusing on the interaction between demand and production, variability, and the buffers required to synchronize them. PPM is the development and application of modern production theories, principles and methods to better understand, control and improve project delivery, including OS, digital and autonomous technologies. PPM is particularly relevant to IC as it focuses on how production systems are designed and controlled to achieve project objectives efficiently [13]. Unlike traditional project management’s focus on schedules (what should happen), OS and PPM provide a technical construct to examines how production systems behave and how they should behave to effectively achieve certain objective. Central to PPM are the five levers of PSO: product design (standardization, modularization, and interface mechanisms), process design (operation sequences and work execution methods), capacity (maximum flow rate through a system), inventory (accumulated entities within or between processes), and variability (dissimilarities between operations or demand) [17]. These levers are interdependent—decisions about one impact the others, and this scientific approach provides mathematical relationships like Little’s Law, and Variability-Utilization-Time (VUT) equation to enable precise optimization beyond what traditional project management approaches can achieve. Furthermore, the design and optimization of production systems is a major focus of OS and PPM, making it applicable to IC, which emphasizes systematic and controlled production processes. This also includes the understanding of standardization, modularization, and customer order decoupling point (CODP) to control the production system behavior.

Previous literature provides information about the means in which Lean Construction methods and tools interact with PPM to enhance project performance. While Lean Construction provides practical implementation tools, PPM offers the mathematical foundation for understanding production system behavior through time, inventory, and capacity buffers [14], addressing the critical limitation identified by Zabelle & Arbulu [15] that ” by using traditional project management techniques, the resulting production system cannot satisfy the schedule demand.” Previous research has laid the groundwork for integrating OS with IC. Studies by Prado [8, 18], and Zhang et al. [9] demonstrated OS applications in both on-site and off-site construction. Prado’s healthcare building case study [18] revealed how OS principles provide more accurate prediction of construction performance, while Zhang’s research [9] in modular bathroom pod manufacturing showed significant reductions in inventory investment while maintaining high fill rates. These studies consistently demonstrate that OS provides practical tools for reducing production variability and optimizing resource allocation. However, most research has focused on isolated aspects of IC rather than examining holistic integration across all nine components [12]. Furthermore, Zabelle [19] positions OS as the technical foundation for construction modernization, emphasizing the need to implement production-based approaches, which is also the vision of PPI.

Method

This research employs a qualitative theoretical analysis to examine how PPM (as part of OS) enables the integration of IC components. This approach is appropriate for addressing this paper’s research objective as it allows for an in-depth exploration of the complex relationships between five PSO levers and IC components without requiring extensive empirical data collection, which would be premature given the nascent state of research in this area. These are the two key steps:

1. Conceptual Framework and Production System Analysis: Examining how OS and PPM explain key production system behaviors in IC contexts – specifically standardization, modularization, and CODP positioning. This approach includes mapping production systems to visualize material and information flows, critical interfaces, and control points that demonstrate how PSO levers influence IC implementation.
2. Lever-Component Mapping: Creating a structured analysis of how each PSO lever influences and enables specific IC components.

The analysis draws on theoretical literature, established PPM methods, and industry practices in IC implementation, which provides context-rich insights that support theory development while maintaining analytical rigor.

Research Findings

Conceptual Framework And Production System Analysis

Figure 2 presents a production system map for a typical IC project (using PPI’s Process Mapper), showing the key production operations, material and information flows (the 4 verbs), which will be helpful to show the interfaces with the nine IC components. The map highlights how the PSO levers influence the network of production systems of the project and reveals several key insights into how PPM enables IC:

1. Process interconnections: The map shows how processes across design, manufacturing, logistics, and assembly are interconnected, emphasizing the need for integration beyond mere prefabrication.
2. Information flow dependencies: The map highlights critical information flows that enable coordination between different participants in the IC project.
3. CODP points: The map highlights key CODP where the PSO levers influence project outcomes depending on the type of component used in the IC project.
4. Integration opportunities: The map reveals opportunities for integrating IC components through shared production objectives, as the TH of each stream needs to align with the capacity in the project site for a JIT delivery and assembly.

The production system perspective showed in figure 2, grounded in PPM, provides a powerful framework for integrating the nine components of IC.

1. PPM enables planning and control by providing mathematical models to analyze workflow decisions (i.e., onsite or offsite), establish appropriate buffers (capacity, inventory, time), among other production-related methods. These models help determine optimal batch sizes, sequence work to minimize waiting time, and set production rates that align with project objectives.
2. PPM informs technical system development by quantifying how design decisions impact production system behavior. By analyzing process variability and throughput capabilities, OS helps optimize technical interfaces between systems and standardize components appropriately for production efficiency. This enables designs that balance customization with production constraints and identify where technical standardization provides the greatest system-wide benefits.
3. PPM positions prefabrication strategically within the overall production flow by identifying optimal CODPs. This determines what should be prefabricated, if any, when, and in what quantities based on demand variability and production capabilities. OS enables calculation of optimal WIP levels between manufacturing and site assembly, ensuring synchronized workflow and minimizing inventory costs.
4. By measuring how partner consistency impacts production metrics (throughput, cycle time, capacity utilization), PPM creates economic justification for long-term relationships. This enables better capacity planning across organizational boundaries and shared investment in variability reduction.
5. PPM transforms logistics from a support function to a core production activity by modeling material flows as integral to the system. It identifies where logistics operations connect with manufacturing and site assembly, enabling JIT delivery systems synchronized with production demand signals.
6. PPM identifies critical information flows and control points where ICT investments provide maximum value. By modeling information transfer as part of the production system, OS enables data-driven production control and real-time decision-making, like BIM to support production.
7. PPM establishes consistent, quantifiable production metrics (TH, CT, WIP) that enable meaningful performance comparison across projects. This creates a systematic framework for capturing and applying lessons learned.
8. PPM helps identify CODPs that balance customization with production efficiency. Through variability analysis, PPM determines which product elements can be standardized with minimal customer impact and where customization creates the greatest value.
9. PPM provides a scientific basis for continuous improvement by identifying bottlenecks, variability sources, and buffer requirements in the production system. This enables targeted improvement initiatives with measurable impact on system performance.

This production system analysis provides a common language and visual framework that helps stakeholders see how their specific IC component connects to the larger system. Instead of optimizing components in isolation, the OS approach reveals interdependencies that require coordination across all nine components.

PSO Levers and IC Components: Lever-component mapping

This subsection presents the interrelation between PSO levers and the IC framework components. Please note that all levers affect all IC components at different levels, which table 1 present. In the following paragraphs, this study will mention how each lever interacts with each IC component.

Process Design

1. Planning and Control of Processes: Enables planning and control by establishing the work sequences, batch sizes, takt times, and control points such as pull and CONWIP signals. It creates standardized work instructions and visual aids that make processes predictable and controllable.
2. Developed Technical Systems: Establishes operation sequences that leverage technical capabilities, defines quality gates between systems, and creates standardized interfaces. It ensures that technical systems work as an integrated whole rather than isolated islands.
3. Prefabrication: Makes fundamental decisions about work allocation between factory and site, determining prefabrication scope and integration methods. It establishes assembly sequences, quality verification protocols, and handoff procedures. The process flow directly determines what can be effectively prefabricated versus what must remain site-built.
4. Long-term Relations: Create predictable interaction patterns that facilitate partnerships, but don’t fundamentally require them.
5. Logistics: Transforms logistics from reactive material movement to integrated production flow by establishing milk runs, point-of-use delivery, and kitting strategies. Pull signals trigger logistics operations, creating synchronization with production demand.
6. Use of ICT: Identifies critical information flows and decision points where digital tools add maximum value – not digitization for its own sake. ICT requirements emerge from process needs: where does information originate, who needs it when, etc.?
7. Re-use of Experience: Create comparable data sets and statistical process control, enabling meaningful project analysis and systematic improvement.
8. Customer Focus: Process design has limited impact on customer focus, mainly supporting it indirectly through delivery reliability and quality consistency.
9. Continuous Improvement: Enable systematic improvement by creating stable baselines for measurement and comparison.

Product Design

1. Planning and Control of Processes: Standardized and modular products simplify planning complexity by reducing unique configurations from thousands to manageable sets. Configuration rules replace custom engineering timelines, allowing rapid and reliable planning cycles.
2. Developed Technical Systems: Standardized product interfaces enable plug-and-play technical components, creating libraries of proven solutions. The product platform strategy directly shapes the technical platform strategy.
3. Prefabrication: Product modularity and standardization are prerequisites for effective prefabrication – without DfMA principles, factory production offers little advantage.
4. Long-term Relations: Stable product platforms enable suppliers to invest in specialized capabilities, equipment, and training that wouldn’t be justified for one-off projects.
5. Logistics: Product dimensions, weight, and modularity directly determine logistics feasibility – designs must consider trailer sizes, crane capacities, and route constraints. Packaging and protection requirements shape handling procedures.
6. Use of ICT: Enable powerful ICT applications like BIM, and automated design tools. Digital product libraries capture design rules and enable rapid configuration.
7. Re-use of Experience: Product platforms accumulate performance data and improvement opportunities across multiple implementations. Standardized products create larger sample sizes for statistical analysis than one-off custom designs.
8. Customer Focus: It constantly balances standardization efficiency with customer customization demands (fundamental tension in IC). Customer feedback directly shapes product evolution and configuration options.
9. Continuous Improvement: Product platforms evolve through systematic incorporation of lessons learned across implementations. Performance data guides design improvements in future platforms.

Variability

1. Planning and Control of Processes: Understanding variability sources (demand fluctuations, quality issues, etc.) enables planners to allocate appropriate buffers. Statistical data informs realistic planning assumptions, while variability reduction efforts directly improve planning reliability.
2. Developed Technical Systems: Variability analysis identifies where technical standardization provides maximum value but doesn’t determine them. Technical systems can accommodate various variability levels through different configurations.
3. Prefabrication: Controlling variability is essential for prefabrication economics – high demand variability forces excess inventory or capacity, while process variability creates quality issues and rework. Standardization and repetition in controlled environments reduce variability.
4. Long-term Relations: Partners who demonstrably reduce system variability become invaluable, creating objective performance criteria for relationship decisions. Variability metrics (on-time delivery, quality consistency, demand stability) support transparency.
5. Logistics: Reduced variability in both demand and supply enables JIT delivery without excessive stock. Predictable production rates allow optimized transport scheduling and equipment utilization.
6. Use of ICT: Enables real-time monitoring and rapid response to variability through dashboard visibility and exception alerts. Predictive analytics identifies variability patterns before they impact production. Digital systems can dynamically adjust plans, redirect resources, etc.
7. Re-use of Experience: Historical variability data improves future predictions and buffer allocation. Databases of variability sources and impacts guide risk management strategies.
8. Customer Focus: Managing the balance between beneficial customer-driven variability (customization) and detrimental production variability requires sophisticated understanding, which must align with production capabilities.
9. Continuous Improvement: Variability sources become explicit improvement targets with clear metrics. Root cause analysis of variability drives systematic problem-solving.

Inventory

1. Planning and Control of Processes: Inventory placement and WIP limits shape planning approaches – pull systems triggered by inventory levels replace complex push schedules. The choice of where to hold inventory (raw materials, WIP, etc.) determines planning horizons and flexibility.
2. Developed Technical Systems: Some technical systems may require specific inventory handling capabilities (refrigeration, hazmat), but they rarely drive technical system selection.
3. Prefabrication: The prefabrication-to-site interface is fundamentally an inventory management challenge – too much inventory ties up capital and space, too little causes work stoppage. Matching factory output and site consumption enables flow synchronization.
4. Long-term Relations: Shared inventory strategies and risk-pooling arrangements can strengthen partnerships, but aren’t fundamental to relationships.
5. Logistics: Shapes logistics patterns – centralized hubs versus distributed storage, high-frequency small batches versus low-frequency large shipments, where to store, etc.
6. Use of ICT: Digital tracking transforms inventory from static counts to dynamic optimization through real-time visibility across the supply network (i.e., RFID and IoT sensors).
7. Re-use of Experience: Historical carrying costs, stockout frequencies, etc., guide inventory policies. However, each project’s unique characteristics limit direct transferability.
8. Customer Focus: Inventory strategies have minimal direct impact on customer focus beyond service level impacts, like safety stock.
9. Continuous Improvement: Inventory metrics (turns, carrying costs, service levels) provide clear improvement targets, though improvements often come from addressing other levers.

Capacity

1. Planning and Control of Processes: Capacity constraints define the realistic planning envelope. Capacity buffers at critical points enable absorption of variability without system-wide disruption.
2. Developed Technical Systems: Capacity constraints ensure technical systems are designed in alignment with production rates, changeover times, and maintenance windows.
3. Prefabrication: Determines optimal prefabrication scope, as pushing too much work off-site can overwhelm either factory or logistics capacity.
4. Long-term Relations: Synchronized capacity planning across the supply network requires long-term commitment to shared utilization goals. Capacity-related agreements formalize these relationships, creating mutual dependencies that encourage collaboration.
5. Logistics: Peak capacity requirements drive equipment investment decisions, and these resources must match production flow requirements or become bottlenecks.
6. Use of ICT: Optimizes capacity utilization through dynamic scheduling, automated resource allocation, and workload balancing. Real-time performance monitoring identifies underutilized resources for redeployment.
7. Re-use of Experience: Capacity utilization data accumulated across projects reveals true production rates versus theoretical capacity. Bottleneck patterns identify systematic capacity constraints requiring strategic resolution rather than project-specific workarounds.
8. Customer Focus: Capacity determines what can be promised to customers – delivery times, customization options, and volume flexibility, to prevent overcommitment.
9. Continuous Improvement: Capacity utilization data objectively provides improvement priorities. Capacity additions through improvement (vs capital) often give a better ROI.

Discussion

This study contributes to the theoretical understanding of IC by demonstrating how PPM facilitates systematic integration of IC components using PSO levers. The findings extend beyond the conventional view of IC as merely offsite construction toward understanding IC as an integrated production system, aligning with Lessing’s comprehensive definition while providing the scientific foundation to operationalize it. The production system map developed provides a visualization tool that reveals interconnections between seemingly disparate IC components, making the dependencies requiring coordination for successful implementation visible. This addresses the fundamental challenge that many IC initiatives fail to achieve their intended benefits by focusing exclusively on prefabrication while neglecting other critical aspects. The lever-component mapping analysis demonstrates that PPM serves as a comprehensive framework for implementing IC by providing production-related metrics to analyze production system behavior and establish an extra layer for analyzing the IC components. While earlier studies demonstrated OS value in specific construction scenarios, this research shows how the five PSO levers enable all nine IC components, addressing the fragmented application of IC practices identified in the research problem.

From the 45 interactions between the 5 PSO levers and the 9 IC components, 37 were directly enabling, 5 moderately direct relationship, and 3 indirect relationship, proving a most enabling nature of the interactions between the levers and the components. It seems that product design and capacity are the most enabling levers for IC, and the inventory lever seems to have a less direct relationship than the other levers. However, the interconnecting nature of the 5 levers also plays a role in the interactions with IC components, and avoiding one of these levers can create unintended consequences of an IC endeavor (i.e., bad positioning of an CODP for an prefabricated element). This study demonstrates that successful implementation requires attention to all nine components within a production system framework. The production system map serves as an adaptable template for visualizing crucial flows, while the PSO levers framework offers systematic guidance for analyzing IC components as part of a network of production systems, following the PPI vision of projects and how to improve them. Moreover, it’s important to acknowledge the limitations of this study, such as the chosen IC framework, the type of infrastructure (buildings), the focus on the production system side of IC, and only using PSO levers from PPM and OS.

Conclusion

This study has addressed the research question: How can PPM enable the effective integration of IC? Through systematic analysis of the PSO levers and their relationship to the nine IC components, this research demonstrates that PPM provides a scientific foundation that transforms IC from separate practices into an integrated network of production system. The findings reveal that PPM enables IC integration through three key mechanisms: mathematical foundation for understanding production system behavior through models like Little’s Law and VUT equation, a common production-focused language bridging traditionally separate domains, and production-based decisions, such as CODP positioning, buffer allocation, modularization level, etc. This research contributes to construction engineering and management practices by providing a production-centered lens for analyzing IC implementation that goes beyond traditional project management approaches. The mapping of PSO levers to IC components creates a coherent framework that explains why certain IC practices are effective and under what conditions they produce optimal results. This study offers a structured approach for designing and optimizing IC production systems, with the production system map serving as an adaptable template and the PSO levers framework providing systematic guidance for analysis and improvement. The integration of PPM with established construction practices creates practical implementation pathways that combine theoretical rigor with operational applicability.

Future research should empirically validate the proposed framework through case studies, extend the analysis to other OS-based frameworks (not only the PSO), using different IC frameworks and different types of infrastructure, and address the other limitations of this study. PPM enables construction organizations to move beyond fragmented applications to achieve the full potential of IC, ultimately improving project outcomes through enhanced productivity, reduced costs, and more reliable schedules.

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