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Chapter 8: research agenda
No full textThis book illustrates the applications of mobile robot systems in warehouse operations with an integrated decision framework for their selection and application. Mobile robot systems are an automation solution in warehouses that make order fulfillment agile, flexible and scalable to cope with the increasing volume and complexity of customer orders. Compared with manual operations, they combine higher productivity and throughput with lower operating costs. As the practical use of mobile robot systems is increasing, decision-makers are confronted with a plethora of decisions. Still, research is lagging in providing the needed academic insights and managerial guidance. The lack of a structured decision framework tailored for mobile robot system applications in warehouses increases the probability of problems when choosing automation systems. This book demonstrates the characteristics of mobile robot systems which reinforce warehouse managers in identifying, evaluating and choosing candidate systems through multiple criteria. Furthermore, the managerial decision framework covering decisions at strategic, tactical and operational levels in detail helps decision-makers to implement a mobile robot solution step-by-step. This book puts special emphasis on change management and operational control of mobile robots using path planning and task allocation algorithms. The book also introduces focus areas that require particular attention to aid the efficiency and practical application of these systems, such as facility layout planning, robot fleet sizing, and human-robot interaction. It will be essential reading for academics and students working on digital warehousing and logistics, as well as practitioners in warehouses looking to make informed decisions
Automated columnar microstructure analysis using CoCo (Column Counter): insights from EB-PVD TBCs
Get PDFThermal barrier coatings (TBCs) are essential for protecting gas turbine components from extreme heat. The columnar microstructures produced by conventional electron beam physical vapour deposition (EB-PVD) provide pathways for the transport of heat and molten calcium–magnesium–alumino–silicates (CMAS), compromising their insulation capability and durability. Modifications to the columnar grain morphology have been shown to improve the performance and durability of EB-PVD TBCs, but replicable quantification of these key morphologic parameters remains elusive. In the present work, we present an automated method for the measurement of column width, Column Counter (CoCo). This method is applied to characterize a wide array of microstructures produced by systematically varying substrate temperature (430–1030 °C) and rotation speed (1–8 rpm). The wide spectrum of novel microstructures produced, ranging from columns with periodic porosity bands to layered architectures, markedly diverge from standard columnar TBCs. The morphological analysis is complemented by advanced characterization via X-ray diffraction (XRD) and electron backscattered diffraction (EBSD), revealing how the deposition parameters control column width, crystallographic texture strength and grain multiplicity within columns. Lower temperatures and slower rotations promote finer, less strongly textured coatings with reduced intercolumnar pathways. The results obtained through CoCo showcase the potential of automated morphological analysis in the tailored design of TBCs for improved performance and durability.The author acknowledges the support from the EPSRC (United Kingdom) grant EP/L016389/1Surface and Coatings Technolog
Melt pool geometry control of Ti-6Al-4V utilizing multi-energy source laser-arc + wire directed energy deposition
Get PDFThis study investigates the applicability of a novel laser-arc multi-energy deposition of Ti-6Al-4V with independent control of bead geometry and thermal input. A plasma transferred arc is used to generate an initial melt pool and melt wire feedstock, before controlled lateral elongation of the melt pool via a fiber laser and galvo scanner. The applicability to Ti-6Al-4V was first investigated using deposition parameters previously identified. Once successful bead geometry control was achieved, process parameters more conducive to wire directed energy deposition were investigated. This included investigation of the energy per unit area required to achieve accurate deposition of Ti-6Al-4V with minimal penetration and investigation into scanning strategy. In each case, optical microscopy was conducted and analysis of the bead geometry, penetration and heat-affected zone considered to determine the effect of each parameter change. The results demonstrated that independent control of bead geometry and thermal input could be achieved, allowing deposition of Ti-6Al-4V at a desired scan width and layer height and providing a framework for future multi-energy source directed energy deposition of Ti-6Al-4V.The authors would like to express their gratitude to BAE Systems and the Engineering and Physical Science Research Council (EPSRC) for supporting this research via NEWAM [grant number: EP/R027218/1]CIRP Journal of Manufacturing Science and Technolog
The attribution of expertise: modelling relational and organisational factors
No full textThe term ‘expert’ is frequently encountered both in the management literature and in the common parlance of business. However, the relational dimension of ‘expertise’ has received little academic attention and lacks clear theoretical underpinning. This study addresses this gap through an exploration of how sources of expertise are identified and utilised in a UK Government Department. A series of semi-structured interviews were used to explore the activities and experiences of 19 staff. The study identifies the complex interactions among institutional, personal and task-related factors. From this, it develops a comprehensive model of the attribution of expertise. This model could be used by organisations to develop appropriate strategies for the management of expert resources and decision making. This study addresses the paucity of empirical research that examines the relational dimensions of the attribution of expertise.International Journal of Management and Decision Makin
The lean and green imperative of manufacturing data
Get PDFThis study introduces a stochastic model-based framework for the prediction and measurement of the environmental impact of manufacturing systems’ digitalization. Utilising a Monte Carlo simulation experimental framework, this paper forecasts the CO2e emissions from the entire lifecycle of manufacturing data over long-term time horizon under different scenarios. The analysis proceeds to estimate the maximum, average, and minimum potential CO2e emissions, under different growth models. Findings reveal that, with the current exponential growth of data that exceeds data centres’ efficiency improvements and carbon intensity decay rates, the environmental footprint associated with the entire lifecycle of data can have a potential adverse impact on the realisation of net-zero goals. The proposed approach provides a viable pathway for manufacturing enterprises aiming to align their data management practices with environmental sustainability and operational efficiency.20th Global Conference on Sustainable Manufacturing (GCSM 2024)Lecture Notes in Mechanical Engineerin
Cost Optimisation to determine ship maintenance schedules for improved operational availability
Get PDFComplex port maintenance operations face significant challenges due to the dynamic nature of port resource availability, variable task urgency, and downtimes having different priorities. This study proposes a dynamic scheduling approach for ship maintenance that integrates agent-based modelling with multi-objective optimisation. By optimising port resource allocation and reducing ship idle costs, the approach significantly enhances operational efficiency in maritime logistics. Utilising a hybrid simulation-optimisation framework, the proposed method adapts downtime priorities and resource allocations rules arising due to classes of ship and their compatibility with the port resources, and their downtimes. Agent-based modelling simulates interactions between ships, port assets, and maintenance activities while Discrete Event Simulation captures the stages of maintenance process. The model re-evaluates the ship maintenance schedules and facility resource downtime schedules to minimise idle time and maximise efficiency. Comparative analyses reveal improvements over static methods, including an average 45% reduction in idle costs of ship due to unavailable resources, with marginal changes in maintenance costs. This approach not only enhances port operational efficiency but also reduces costs associated with ship waiting times, demonstrating its potential application to other complex industrial scheduling problems requiring adaptive solutions.58th CIRP Conference on Manufacturing Systems 2025Procedia CIR
Routine replication and embodying process: an ethnographic study on the impact of the body in routine replication in the Royal Air Force
Get PDFWe examine the relationship between routine replication and embodiment by studying how the Royal Air Force replicated an arduous loaded march in its Initial Officer Training programme from its Ground Combat Training programme. The routine (also called ‘tabbing’) was adapted to fit its new context, as the replication was affected by the differences in the trainees’ bodies, but it was kept recognisable as the same routine in both settings. Using qualitative methods and 30 months of data collection, this ethnographic case study involves a novel methodology in which we collected data through an enactive ethnography. Our research advances the study of Routine Dynamics, more specifically routine replication and embodiment, in two ways. First, we show how routine participants’ bodies play an important role within routine replication process and how they impact its dynamics. To deal with the ‘replication dilemma’, a constant interplay between flexibility and recognisability occurs through three overarching bodily mechanisms, namely, ‘playing with rhythm’, ‘coping with injuries’, and ‘dealing with emotions’. Our research adds to the scarce body of research on the role of embodiment in routine replication. Second, we contribute by introducing a novel way of conducting an ethnography. The first author not only observed the phenomena but also participated in the loaded marches together with the other officer cadets physically experiencing the routine performing and patterning. This study hence responds to recent calls to explore novel, seldom-used methodologies and uses enactive ethnography to study embodiment in practice.41st EGOS (European Group for Organization Studies) Colloquiu
Data-driven vehicle modeling for path tracking based on the Combination of a Neural Network and Kinematics Model
Get PDFAutonomous driving systems must safely navigate in increasingly diverse and challenging conditions, which necessitate the incorporation of vehicle dynamic models capable of accurately capturing a vehicle's behavior in diverse conditions. Moreover, these models need to be easily and rapidly developed to meet the needs of rapid autonomous driving software updates. Currently used models have limited accuracy, require extensive parameter tuning, and cannot meet these demands. This paper introduces the Combination of Neural Network and Kinematics Model (CNKM). A neural network is utilized to model the nonlinear characteristics of vehicle subsystems (powertrain, braking, steering, tires) and various unknown factors. It ultimately outputs accelerations that are fed into a planar kinematics model to derive the vehicle states. The neural network is trained using a dataset collected from natural driving. A weighting formula suitable for natural driving data is proposed to mitigate the impact of an uneven dataset distribution. This model is compared with commonly used models under typical and high lateral acceleration scenarios, and the position and heading errors of CNKM are 15.34% and 14.71% of those of the nonlinear dynamic model, respectively.National Natural Science Foundation of China; 52394261. Science and Technology Development Project of Jilin Province; 202302013. Ministry of Education industry-university cooperative education project; 231007538181742. Key Laboratory of Automotive Power Train and Electronics of Hubei Province open fund project; ZDK12023A05.Automotive Innovatio
A common physical and control interface for ISAM operations
Get PDFThe Common Physical and Control Interface (CPCI) is a standardised, open-source solution to enhance interoperability in In-Orbit Servicing, Assembly, and Manufacturing (ISAM) operations. The absence of a universal interface in current space systems increases integration complexity, costs, and inefficiencies. CPCI leverages IEEE 802.3 Power over Ethernet (PoE) to enable simultaneous power and data exchange, providing a scalable and modular plug-and-play solution for future space missions.This work was performed under the Science and Technology Facilities Council (STFC) Cross-Cluster Proof of Concept Grant Pump-Priming Grant - In-Space Economy as part of United Kingdom Research and Innovation (UKRI).Orbit Servicing, Assembly & Manufacturing (ISAM) Conference 202
Intelligent manufacturing paradigms: linking design optimization and sustainability in large-area additive manufacturing
Get PDFThe next generation of computer-aided intelligent manufacturing systems must enable the exploration and exploitation of cause-and-effect relationships across multiple disciplines. This capability strengthens human decision-making and supports sustainability-by-design in digital design-to-manufacturing workflows. To enhance system intelligence, seamless integration is needed between material systems, design methods, manufacturing processes, and sustainability metrics. This study presents a case study on large-scale mold manufacturing using large area additive manufacturing. A multidisciplinary design optimization (MDO) framework combines parametric and generative design strategies with manufacturing process planning, material selection, and environmental impact analysis. The study examines the trade-offs between structural integrity, production efficiency, and ecological impact, focusing on two different short fiber-reinforced polymer materials. Empirical and model-driven analyses methods reveal a direct correlation between mass reduction and improved sustainability. While carbon fiber reinforcement offers better structural performance, it also increases the carbon and water footprints by approximately 400% and 100%, respectively, compared to glass fiber alternatives. The case study on wind turbine rotor blade mold manufacturing highlights how parametric and generative design approaches can produce both structurally sound and sustainable solutions. Future research should focus on improving the algorithmic transparency of commercial software, increased flexibility to add manufacturability constraints, and potentially including sustainability models to enhance the intelligence in design-to-manufacturing workflows. This study highlights the potential of intelligent manufacturing systems to drive cleaner, more efficient, and sustainable production processes.This work was supported by the project D2M (346874) Research Council of Finland - Academy Research Fellow.The International Journal of Advanced Manufacturing Technolog