The research, led by Laoise Reynolds with Omid Sam-Daliri, Yadong Jiang and Pouyan Ghabezi, was motivated by a persistent problem in modern manufacturing. Conventional assembly relies on adhesives, mechanical fasteners or metallurgical joining, all of which carry inherent drawbacks. Adhesive bonds can trap voids and microcracks during manufacture, degrade under moisture, corrosive agents and temperature swings, and demand meticulous surface preparation. Fasteners and welds add weight, create stress concentrations, complicate recycling and make disassembly difficult. As industries push toward modular, repairable and environmentally responsible design, the researchers saw an opportunity in Sashimono, the traditional Japanese woodworking technique that achieves precise, load-bearing assembly with no extra joining elements at all.

Rather than copying traditional wooden joints exactly, the team designed three Japanese-joinery-inspired configurations suited to thermoplastic parts: a Dovetail joint, a T joint and a C joint. Each was printed in polylactic acid, or PLA, a biodegradable thermoplastic derived from plant sugars that is a staple of fused deposition modelling, the most widely used form of 3D printing. PLA offers a low processing temperature, good dimensional stability and a strong sustainability profile, making it an ideal candidate for prototyping interlocking concepts aimed at low-to-medium load-bearing applications. The parts were printed flat on a Prusa MK4 printer with a 0.4 mm nozzle, a 0.2 mm layer height, 100 percent infill and a plus-or-minus 45 degree raster orientation, with a dimensional tolerance of 0.05 mm on the interlocking features so the components could be pressed together by hand with a secure fit.

The experimental campaign was exhaustive. For each joint family, the researchers varied three geometric parameters: neck thickness, a shape-specific feature such as the dovetail angle, the C-joint radius or the T-joint neck length, and the number of interlocking notches, from one to three. Five specimens were printed and tested for every parameter combination, amounting to 270 printed pieces and 135 completed assemblies, roughly 40 hours of printing time. Standard dog-bone specimens were also printed as a continuous reference. Every assembly was pulled to failure on an Instron 4467 universal testing machine at a crosshead speed of 2 mm per minute, while a stereo camera system running GOM ARAMIS digital image correlation captured full-field strain maps on the specimen surface every two seconds, revealing exactly where deformation concentrated and where cracks began.

The continuous printed PLA reference achieved an ultimate tensile strength of 44.4 plus or minus 2.5 MPa with an effective elastic modulus of 2511 MPa, failing in a brittle manner from a localised strain zone that peaked near 20 percent. The interlocking joints, by contrast, reached only a fraction of that strength, a result the authors stress is expected for a proof-of-concept mechanical screening of geometric interlocks. The best performer was the C joint with a 5 mm neck thickness and a single notch, which achieved about 7 MPa, roughly 84 percent below the solid reference but the highest of all tested configurations. Notably, the C joint with a 3 mm neck was far weaker at 4.6 MPa, while thickening the neck to 7 mm also reduced strength to 5.0 MPa, showing that more material does not automatically mean better performance.

Digital image correlation explained why. In the thin-necked C joint, strain concentrated between 6 and 12 percent around the narrow neck, which snapped off in a sudden brittle fracture. The 5 mm version spread strain more evenly, reached about 15 percent local strain and failed progressively with only partial detachment of the neck. The 7 mm joint deformed the most of all, with recorded strains up to 37 percent, absorbing energy through plastic deformation before large chunks of material finally separated. Radius played its own role: increasing the C-joint radius from 3 mm to 5 mm boosted tensile strength by about 31 percent, but the joints also failed more abruptly, while the smallest radius allowed extensive plastic deformation without any visible cracking.

The number of notches produced opposite effects in different joint families, one of the study’s most intriguing findings. In the C joint, adding notches reduced tensile strength, from 5.8 MPa with one notch to 4.9 MPa with three, a drop of nearly 16 percent, while stiffness climbed sharply, with the effective elastic modulus rising about 66 percent. More notches restricted deformation, making the joint appear stiffer but weaker. The Dovetail joint behaved in exactly the reverse manner: three notches delivered 6.1 MPa, a 27.6 percent improvement over a single notch, with stiffness nearly doubling. DIC imaging showed the three-notch dovetail redistributing load after the first crack formed, sustaining additional force before a second brittle fracture appeared, a progressive failure pattern that contrasts with the single catastrophic break of simpler designs.

Dovetail geometry itself proved sensitive to angle and thickness in unexpected ways. Increasing the dovetail angle from 55 to 62.5 degrees raised tensile strength by about 21 percent, yet further thickening the neck from 5 mm to 10 mm cut strength by 38 percent while more than tripling the strain at break, from 1.7 to 5.3 percent. Thicker dovetails absorbed far more deformation, with local strains reaching 64 percent before damage spread, but they did so at lower overall strength and stiffness. The T joint emerged as the weakest family, with its single-notch configuration managing only 2.0 MPa, though adding notches transformed it dramatically: three notches lifted strength to 5.9 MPa, a 188 percent improvement, and produced the highest effective elastic modulus of any configuration at 1350 MPa. DIC revealed the middle notch bearing the brunt of the load, cracking first and then transferring strain to the remaining notches in a staged, progressive collapse.

The authors are careful to frame the scope of their conclusions. The study sits within a Design for Assembly context but did not measure quantitative DFA metrics such as assembly time, assembly force, disassembly cycles, wear or manufacturing cost, and the reported comparisons are descriptive rather than statistically tested. The findings apply specifically to PLA, the tested geometries and static tensile loading. Even so, the message is striking: centuries-old joinery wisdom, translated into printed thermoplastic, can produce tool-free, adhesive-free, fully reversible connections whose strength and failure mode can be tuned almost at will through geometry. A designer can now choose a configuration that prioritises strength, like the multi-notch dovetail, or one that maximises stiffness, like the three-notch T joint, simply by adjusting parameters that a desktop printer can produce overnight.

That tunability is precisely what makes the work resonate beyond the laboratory. In an era of circular-economy targets, products that snap together, come apart cleanly and can be repaired or reconfigured component by component represent a genuine alternative to glued and bolted construction. The Irish team’s demonstration that digital image correlation can pinpoint exactly where printed interlocks concentrate strain gives future designers a practical map of weak points to avoid. The C joint, with its combination of the highest tensile strength and progressive, deformation-tolerant failure, is flagged as the most promising candidate for further development. If subsequent studies confirm that these printed joints survive repeated assembly cycles and real-world loading, the ancient art of Sashimono may find an unlikely second life inside everything from flat-pack furniture to modular drone frames, all built without a screw, a rivet or a bead of glue.

Subject of Research: Mechanical performance of 3D-printed PLA interlocking joints inspired by traditional Japanese joinery

Article Title: Design for assembly of 3D-printed structures using joinery-inspired interlocking joints

Article References: Reynolds, L., Sam-Daliri, O., Jiang, Y., & Ghabezi, P. (2026). Design for assembly of 3D-printed structures using joinery-inspired interlocking joints. Results in Engineering, 32, Article 113437. https://doi.org/10.1016/j.rineng.2026.113437

Image Credits: AI Generated

DOI: 10.1016/j.rineng.2026.113437

Keywords: 3D printing, Japanese joinery, PLA, interlocking joints, dovetail joint, digital image correlation, design for assembly, tensile testing, additive manufacturing, fused deposition modelling, sustainable design, mechanical testing

The carbon footprint concept emerged in the early 2000s as a practical way to link products, processes, and organizations to their greenhouse gas emissions, expressed in carbon dioxide equivalents. It was quickly institutionalized through two landmark frameworks. The Greenhouse Gas Protocol, published in 2004 by the World Resources Institute and the World Business Council for Sustainable Development, introduced the now-ubiquitous classification of emissions into Scope 1, Scope 2, and Scope 3 – direct emissions, purchased energy, and value-chain emissions respectively. Meanwhile, the ISO 14040 and 14044 standards formalized Life Cycle Assessment, or LCA, the rigorous methodology that tallies environmental burdens from raw material extraction through manufacturing, use, and disposal. Together these frameworks gave companies a common language for identifying emission hotspots, benchmarking performance, and setting reduction targets, and they now feed into national climate commitments, ESG reporting, and consumer carbon labels.

But the review identifies a persistent structural problem: the landscape is methodologically fragmented. Analysts must choose among process-based LCA, which offers detailed product-level accounting but suffers from truncation errors that omit indirect upstream emissions; input-output analysis, which captures economy-wide supply chains but relies on coarse sector averages; and hybrid models that combine both but demand intensive data and modeling effort. Newer variants push further – dynamic LCA incorporates time-dependent emission factors that track decarbonizing electricity grids, while spatially resolved methods capture regional differences in energy mixes. Each approach embodies a trade-off between specificity, completeness, data availability, and computational effort, and no single method dominates across all manufacturing contexts.

The consequences of this fragmentation are quantifiable. Differences in system boundaries, allocation rules for co-products, functional units, and emission-factor databases such as Ecoinvent, GaBi, and GREET can produce substantially different results for similar products. Sensitivity studies compiled in the review illustrate the scale of the problem: variability in the energy mix has driven differences of up to 50 percent in food-product footprints, while choices of allocation method alone shifted industrial results by as much as 40 percent. Uncertainty treatment compounds the issue. Simple one-at-a-time sensitivity analysis, widely used because it is cheap and intuitive, cannot capture interactions between variables. Monte Carlo simulation propagates uncertainty across thousands of scenarios but depends heavily on the quality of input distributions. Global sensitivity methods such as Sobol indices and the Morris method reveal which parameters and interactions actually drive variability, yet their computational demands limit routine industrial use. Critically, the review notes, uncertainty is usually assessed only after a footprint model has been built, rather than being woven into data selection and boundary definition from the start.

Scope 3 emissions present perhaps the thorniest challenge. For many organizations, value-chain emissions dominate the total footprint, yet they are the hardest to quantify because supply chains are complex, geographically dispersed, and data-poor. The review highlights a particularly troubling blind spot in battery manufacturing: conventional factory-level assessments frequently account for on-site cell assembly and pack integration while excluding the embodied carbon of cathode and anode active materials sourced from other countries – precisely the components that dominate a battery’s total emissions. The result is a systematic underestimation of the true carbon burden, obscured further by static, historical data that fail to reflect evolving energy systems and technological change.

The authors’ proposed remedy comes from an unexpected direction: the world of digital engineering. Model-Based Definition, or MBD, transforms the 3D CAD model into the authoritative digital representation of a product, embedding geometry, tolerances, materials, and manufacturing process metadata directly within the model as machine-readable information. Unlike traditional 2D drawings, an MBD model can be automatically interpreted by downstream applications – and, crucially, by LCA tools. When a designer changes a material, a tolerance, or a manufacturing feature, the associated metadata can instantly update the corresponding life cycle inventory entries and recalculate the footprint. In this vision, the product model becomes a digital carrier of sustainability data, bridging the long-standing disconnect between engineering design and environmental analysis.

The review situates MBD within a broader model-based ecosystem. Model-Based Systems Engineering formalizes system requirements and architecture, allowing environmental constraints such as emission targets and recyclability to be treated as design requirements subject to early trade-off analysis. The Model-Based Enterprise extends product data across the organization through standards like STEP AP242 and the Quality Information Framework, enabling a continuous digital thread from design intent to factory execution. Commercial tools such as SolidWorks Sustainability and Autodesk Insight already perform on-the-fly carbon estimates from model metadata, and academic workflows have predicted emissions for welded assemblies and machined parts with minimal manual intervention. In construction, Building Information Modeling systems similarly derive embodied-carbon inventories automatically, demonstrating the transferability of the approach.

To illustrate the potential, the authors sketch a hierarchical, bottom-up carbon-accounting framework for battery production. Each component – cathode, anode, electrolyte, separator, casing – is defined through MBD with embedded material and process metadata linked to life cycle inventory databases. Emissions roll up through assembly stages, then to the factory, the industrial zone, the city, and the national sector, preserving traceability at every level. In a worked example, the MBD-driven approach yields a cradle-to-grave footprint of roughly 88 kilograms of CO2-equivalent per kilowatt-hour of cell capacity for an NMC battery line – about 80 kilograms from materials plus 18 kilograms from process electricity – corresponding to approximately 17,600 tonnes of CO2-equivalent per year for a facility producing 200 megawatt-hours of cells. Conventional top-down estimates for comparable facilities, built from aggregated electricity, fuel, and waste statistics, typically report substantially lower values because they truncate upstream material production. The authors stress the MBD figure is not an upper bound but a physically grounded reconstruction of the true carbon burden.

The authors are careful to position the framework as a future research direction rather than a mature industrial system. MBD cannot resolve methodological choices such as system boundaries, allocation rules, or emission-factor selection – those remain matters of expert judgment. Significant obstacles remain, including semantic misalignment between CAD and LCA ontologies, boundary inconsistencies between design models and life cycle scopes, and the need for versioned, traceable emission-factor metadata. Fully automated inventory generation, AI-driven emission prediction, and continuously updated digital carbon twins all require further validation. The review calls for minimum machine-readable data requirements, standardized mapping mechanisms between product attributes and inventory flows, improved environmental-data traceability, and industrial case studies comparing MBD-enabled and conventional workflows.

If the vision matures, the implications extend well beyond compliance dashboards. A manufacturing world in which every design decision – a cathode chemistry swap, a more efficient drying oven, an optimized formation protocol – propagates instantly through a traceable digital hierarchy would transform carbon accounting from retrospective reporting into proactive, model-driven management. Designers could visualize trade-offs among performance, cost, and carbon intensity during the earliest phases of product development, when decisions carry the greatest leverage. Regulators would gain auditable, consistent data pipelines across supply chains. And the persistent, credibility-eroding discrepancies that have plagued carbon footprinting for two decades could finally give way to numbers that engineers, policymakers, and consumers can all trust – because they were built from the same digital truth as the product itself.

Subject of Research: Methodological limitations of carbon footprint assessment in manufacturing and a proposed model-based digital framework for design-integrated carbon accounting

Article Title: Carbon footprint assessment in manufacturing: Methodologies, limitations, and a future MBD-enabled digital framework

Article References: Yassine Sibai, D., Kassab, A., Pannier, C., Ayoub, G. Y., & Mohanty, P. (2026). Carbon footprint assessment in manufacturing: Methodologies, limitations, and a future MBD-enabled digital framework. Cleaner Engineering and Technology, 34, Article 101325. https://doi.org/10.1016/j.clet.2026.101325

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101325

Keywords: carbon footprint, manufacturing, life cycle assessment, GHG Protocol, Model-Based Definition, digital thread, Scope 3 emissions, uncertainty analysis, sensitivity analysis, battery manufacturing, sustainable design, digital twins