Search Results (33)

This study investigates the integration of finite capacity scheduling with POLCA-based workload control in high-mix, low-volume production environments. We propose a proactive scheduling approach that embeds POLCA constraints into a constraint programming (CP) model, aiming to reconcile the trade-offs between utilization efficiency and system responsiveness. The proposed methodology is evaluated in two phases. First, a simplified job shop simulation compares a traditional reactive POLCA implementation with the CP-based proactive approach under varying system configurations, demonstrating significant reductions in lead times, tardiness, and deadlock occurrences. Second, an industrial case study in an aerospace manufacturing firm validates the practical applicability of the approach by retrospectively comparing the CP model against an existing commercial scheduler. The results underscore that the integrated framework not only enhances scheduling performance through improved workload control but also provides a more stable operational environment. Full article

Micromixing is a crucial process in microfluidic systems. In biochemical and chemical analysis, the sample is usually tested with reagents. These solutions must be well mixed for the reaction to be possible, generally using micromixers manufactured with sophisticated and expensive technology. The present work shows the design and evaluation of micromixers fabricated with LTCC (low-temperature co-fired ceramics) and FDM (fused deposition modeling) technologies for the development of functional and complex geometries. Two-dimensional planar serpentine and 3D chaotic convection serpentine micromixers were manufactured and implemented in an automated microanalytical system using photometric methods. To evaluate the performance of the micromixers, flow, mixing and absorbance measurements were carried out. Green tape and PP materials were used and showed good resistance to the acidic chemical solutions. The devices presented achieved mixing times in seconds, a reduced dispersion due to their aspect ratio, high sensitivity, and precision in photometric measurement. The optical sensing cells stored sample volumes in a range of 10 to 600 µL, which allowed the reduction of reagent consumption and waste generation. These are ideal characteristics for in situ measurement, portable, and low-cost applications focused on green chemistry and biochemistry. Full article

Forecasting demand for newly introduced products presents substantial challenges within high-mix, low-volume manufacturing contexts, primarily due to cold-start conditions and unpredictable order behavior. This research proposes the Dynamic Dual-Phase Forecasting Framework (DDPFF) that amalgamates machine learning-based classification, similarity-driven analogous forecasting, ARMA-based residual compensation, and statistical process control for adaptive model refinement. The framework underwent evaluation through five real-world case studies conducted by a Taiwanese semiconductor tray manufacturer, encompassing a variety of scenarios characterized by high volatility, seasonality, and structural drift. The results indicate that DDPFF consistently outperformed conventional ARIMA and analogous forecasting methodologies, yielding an average reduction of 35.7% in mean absolute error and a 41.8% enhancement in residual stability across all examined cases. In one representative instance, the forecast error decreased by 44.9% compared to established benchmarks. These findings underscore the framework’s resilience in cold-start situations and its capacity to adapt to evolving demand patterns, providing a viable solution for data-scarce and dynamic manufacturing environments. Full article

Wire arc additive manufacturing (WAAM) with a special arc mode of cold metal transfer pulse advanced (CMT-PADV) is an ideal additive manufacturing process for fabricating aerospace components, primarily high-strength aluminum alloys, offering advantages such as high deposition rates and low cost. However, the numerical simulation of the CMT-PADV WAAM process has not been researched until now. In this study, we first developed a three-dimensional fluid dynamics model for the CMT-PADV WAAM of 7075 aluminum alloy, aiming at analyzing the droplet transition and molten pool flow. The results indicate that, under the CMT-PADV mode, droplet transition follows a mixed transition mode, combining short-circuiting and spray transition. The Direct Current Electrode Positive period of the arc accelerates droplet spray transition, significantly increasing molten pool flow. In contrast, the Direct Current Electrode Negative period of the arc predominantly features droplet short-circuiting transition with low heat input and a weak impact on the molten pool. The periodic switching of the current polarity of CMT-PADV mode results in periodic variations in molten pool size and volume, reducing heat input while maintaining high deposition quality. The revelation of this mechanism provides process-based guidance for low-defect, high-performance manufacturing of critical components. Full article

The intricate process of planning production, involving product life cycle management and the synthesis of manufacturing information, is crucial for coherence in manufacturing. Manufacturing companies, operating in a high-mix, low-volume production environment, integrate production planning with management to focus on production processes, emphasizing high-quality, rapid product delivery. This includes material item planning to anticipate future demands and ensure sufficient raw material and finished product quantities, considering purchasing, production, and sales capacities. This study explores the electro technical sector, specifically a manufacturing entity specializing in low-voltage plastic cable distribution boxes. It scrutinizes the vital role of seasonal data cleaning in optimizing production planning, with a targeted focus on three products. The implementation of a chase demand strategy is related to capacity planning, taking into account the change in production capacity linked to demand over time. The problem in implementing this strategy is related to the fluctuating level of quality due to changes in demand for specified products. Full article

Manufacturing companies characterized by high-mix and low-volume production exhibit distinct features that exert a significant influence on the product introduction process. The quality of information exchange between product design and production interfaces becomes paramount in low-volume manufacturing. Consequently, there is a pressing need to explore various methods for adapting and customizing management strategies to align with the unique characteristics of low-volume manufacturing and its associated product introduction processes. Although this knowledge is critical in low-volume manufacturing, most existing studies focus on the management aspects of high-volume manufacturing. Therefore, this study investigated the customization of management strategies for product introduction in low-volume manufacturing to enhance the quality of information content. Drawing upon a longitudinal analysis of new product introductions within a low-volume manufacturing company, this study identified four management strategies—namely, securing a production test and verification plan, revising the role of product introduction management, developing a formal design and production coordination plan, and developing lessons learned management plan. The paper explains how the examined company adapted and implemented product introduction management strategies to facilitate the enhancement of information content quality across three key stages: pre-implementation, post-implementation, and subsequent modification and refinement of strategies following the initial round of implementation. By shedding light on these strategies, this study offers a comprehensive understanding of management approaches for product introduction in low-volume manufacturing. The study makes a valuable contribution to the discourse on information quality management and design-production interface in the low-volume manufacturing and low-volume product introduction literature. Full article

Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot’s task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments. Full article

The growing consumer demand for unique products has made customization and personalization essential in manufacturing. This shift to low-volume, high-mix (LVHM) production challenges the traditional paradigms and creates difficulties for small and medium-sized enterprises (SMEs). Industry 5.0 emphasizes the importance of human workers and social sustainability in adapting to these changes. This study introduces a digital twin design tailored for LVHM production, focusing on the collaboration between human expertise and advanced technologies. The digital twin-based production optimization system (DTPOS) uses an intelligent simulation-based optimization model (ISOM) to balance productivity and social sustainability by optimizing job allocation and scheduling. The digital twin model fosters a symbiotic relationship between human workers and the production process, promoting operational excellence and social sustainability through local innovation and economic growth. A case study was conducted within the context of a printed circuit board assembly (PCBA) using surface mount technology to validate the digital twin model’s efficacy and performance. The proposed DTPOS significantly improved the performance metrics of small orders, reducing the average order processing time from 19 days to 9.59 days—an improvement of 52.63%. The average order-to-delivery time for small orders was 19.47 days, indicating timely completion. These findings highlight the successful transformation from mass production to mass personalization, enabling efficient production capacity utilization and improved job allocation and scheduling. By embracing the principles of Industry 5.0, the proposed digital twin model addresses the challenges of LVHM production, fostering a sustainable balance between productivity, human expertise, and social responsibility. Full article

In this paper, we address the most pressing challenges faced by the manufacturing sector, particularly the manufacturing of small and medium-sized enterprises (SMEs), where the transition towards high-mix low-volume production and the availability of cost-effective solutions are crucial. To overcome these challenges, this paper presents 14 innovative solutions that can be utilized to support the introduction of agile manufacturing processes in SMEs. These solutions encompass a wide range of key technologies, including reconfigurable fixtures, low-cost automation for printed circuit board (PCB) assembly, computer-vision-based control, wireless sensor networks (WSNs) simulations, predictive maintenance based on Internet of Things (IoT), virtualization for operator training, intuitive robot programming using virtual reality (VR), autonomous trajectory generation, programming by demonstration for force-based tasks, on-line task allocation in human–robot collaboration (HRC), projector-based graphical user interface (GUI) for HRC, human safety in collaborative work cells, and integration of automated ground vehicles for intralogistics. All of these solutions were designed with the purpose of increasing agility in the manufacturing sector. They are designed to enable flexible and modular manufacturing systems that are easy to integrate and use while remaining cost-effective for SMEs. As such, they have a high potential to be implemented in the manufacturing industry. They can be used as standalone modules or combined to solve a more complicated task, and contribute to enhancing the agility, efficiency, and competitiveness of manufacturing companies. With their application tested in industrially relevant environments, the proposed solutions strive to ensure practical implementation and real-world impact. While this paper presents these solutions and gives an overview of their methodologies and evaluations, it does not go into their details. It provides summaries of comprehensive and multifaceted solutions to tackle the evolving needs and demands of the manufacturing sector, empowering SMEs to thrive in a dynamic and competitive market landscape. Full article

The most valuable components of coal fly ash are cenospheres. Cenospheres are hollow spherical particles produced during the coal-burning processes. As a result of their excellent characteristics, such as high workability, high heat resistance, low bulk density, and high strength, cenospheres can be used in the manufacturing of lightweight cement concrete. The research efforts and outcomes are to produce long-lasting cement-based lightweight concrete (LWC) composites with good mechanical properties. The novelty of this investigation is to determine the cement concrete strength when silica fume (SF) and cenospheres (CS) were used as a replacement for cement. Throughout the experiments, a consistent substitution of 12% silica fume was incorporated into cement mass. Silica is used as a micro filler and pozzolanic reactant to strengthen concrete. The concrete mixtures were tested to ensure they met the requirements of the lightweight concrete in terms of their mechanical, physical, and durability qualities. According to the findings, lightweight concrete standards were met, and environmental sustainability was improved with the use of these mix proportions. Concrete specimen’s self-weight decreases by 35% with 30% cenosphere as a replacement. The micrograph shows the lack of portlandite is filled by mullite and other alumino silicates from the cenosphere. In order to achieve sustainability in concrete manufacturing, these mixtures can be suggested for the making of structural LWC that makes use of a large volume of industrial waste while conserving cement and natural resources. Full article

Industries such as the manufacturing or logistics industry need algorithms that are flexible to handle novel or unknown objects. Many current solutions in the market are unsuitable for grasping these objects in high-mix and low-volume scenarios. Finally, there are still gaps in terms of grasping accuracy and speed that we would like to address in this research. This project aims to improve the robotic grasping capability for novel objects with varying shapes and textures through the use of soft grippers and data-driven learning in a hyper-personalization line. A literature review was conducted to understand the tradeoffs between the deep reinforcement learning (DRL) approach and the deep learning (DL) approach. The DRL approach was found to be data-intensive, complex, and collision-prone. As a result, we opted for a data-driven approach, which to be more specific, is PointNet GPD in this project. In addition, a comprehensive market survey was performed on tactile sensors and soft grippers with consideration of factors such as price, sensitivity, simplicity, and modularity. Based on our study, we chose the Rochu two-fingered soft gripper with our customized force-sensing resistor (FSR) force sensors mounted on the fingertips due to its modularity and compatibility with tactile sensors. A software architecture was proposed, including a perception module, picking module, transfer module, and packing module. Finally, we conducted model training using a soft gripper configuration and evaluated grasping with various objects, such as fast-moving consumer goods (FMCG) products, fruits, and vegetables, which are unknown to the robot prior to grasping. The grasping accuracy was improved from 75% based on push and grasp to 80% based on PointNetGPD. This versatile grasping platform is independent of gripper configurations and robot models. Future works are proposed to further enhance tactile sensing and grasping stability. Full article

Because of high conductivity, acceptable cost and good screen-printing process performance, silver pastes have been extensively used for making flexible electronics. However, there are few reported articles focusing on high heat resistance solidified silver pastes and their rheological properties. In this paper, a fluorinated polyamic acids (FPAA) is synthesized by polymerization of the 4,4′-(hexafluoroisopropylidene) diphthalic anhydride and 3,4′-diaminodiphenylether as monomers in the diethylene glycol monobutyl. The nano silver pastes are prepared by mixing the obtained FPAA resin with nano silver powder. The agglomerated particles caused by nano silver powder are divided and the dispersion of nano silver pastes are improved by three-roll grinding process with low roll gaps. The obtained nano silver pastes possess excellent thermal resistance with 5% weight loss temperature higher than 500 °C. The volume resistivity of cured nano silver paste achieves 4.52 × 10⁻⁷ Ω·m, when the silver content is 83% and the curing temperature is 300 °C. Additionally, the nano silver pastes have high thixotropic performance, which contributes to fabricate the fine pattern with high resolution. Finally, the conductive pattern with high resolution is prepared by printing silver nano pastes onto PI (Kapton-H) film. The excellent comprehensive properties, including good electrical conductivity, outstanding heat resistance and high thixotropy, make it a potential application in flexible electronics manufacturing, especially in high-temperature fields. Full article

Water contamination is a major issue due to industrial releases of hazardous heavy metals. Copper ions are among the most dangerous heavy metals owing to their carcinogenicity and harmful effects on the environment and human health. Adsorption of copper ions using alkali activated materials synthesized through the polycondensation reaction of an alkali source and aluminosilicates is the most promising technique, and has a high adsorption capability owing to a large surface area and pore volume. This research focuses on the effect of the alkaline activator ratio, which is a sodium silicate to sodium hydroxide ratio. Various exposing temperatures on metakaolin based alkali activated materials on a surface structure with excellent functional properties can be used as adsorbent materials for the removal of copper ions. A variety of mix designs were created with varying sodium silicate to sodium hydroxide ratios, with a fixed sodium hydroxide molarity, metakaolin to alkali activator ratio, hydrogen peroxide, and surfactant content of 10 M, 0.8, 1.00 wt%, and 3.0 wt%, respectively. Most wastewater adsorbents need high sintering temperatures, requiring an energy-intensive and time-consuming manufacturing process. In this way, metakaolin-based alkali activated materials are adsorbent and may be produced easily by solidifying the sample at 60 °C without using much energy. The specific surface area, water absorption, microstructure, phase analysis, functional group analysis, and adsorption capability of copper ions by metakaolin based alkali activated materials as adsorbents were evaluated. The water absorption test on the samples revealed that the sodium silicate to sodium hydroxide 0.5 ratio had the highest water absorption percentage of 36.24%, superior pore size distribution, and homogeneous porosity at 60 °C, with a surface area of 24.6076 m²/g and the highest copper ion uptake of 63.726 mg/g with 95.59% copper ion removal efficiency at adsorption condition of pH = 5, a dosage of 0.15 g, 100 mg/L of the initial copper solution, the temperature of 25 °C, and contact time of 60 min. It is concluded that self-supported metakaolin based alkali activated material adsorbents synthesized at low temperatures effectively remove copper ions in aqueous solutions, making them an excellent alternative for wastewater treatment applications. Full article

The high-mix, low-volume (HMLV) industry has seen growth in the need for product customisation with research to increase manufacturers’ flexibility for the variation in market demands. This paper reviews 152 documents from 2000 to October 2022, discussing work related to HMLV production. From an industrial perspective, this paper analyses the industries with HMLV, revealing production sectors and research areas, categorising the developed work, type of validation, and applications. The results show that most work is not industry-specific, with production planning as the central aspect of the research. While other parts of the production processes and value chain received less attention, the semiconductor and electronics industries are the two most researched with substantial validation, leaving gaps in other industries. Earlier work primarily focused on the theoretical development of production planning; however, the development of Industry 4.0 technologies advocates decision support systems for reactive production planning. This period sees the rise in robotics and automation, with improved robotics capability and human—robot collaboration. Assembly assistance systems were developed for manual production to aid operators in managing the variety of information. This paper serves as a reference for the HMLV manufacturing industry in a structured manner while identifying potential for future research in this field. Full article

Demand trends towards mass customization drive the need for increasingly productive and flexible assembly operations. Walking-worker assembly lines can present advantages over fixed-worker systems. This article presents a multiproduct parallel walking-worker assembly line with shared automated stations, and evaluates its operational performance compared to semiautomated and manual fixed-worker lines. Simulation models were used to set up increasingly challenging scenarios based on an industrial case study. The results revealed that semiautomated parallel walking-worker lines could achieve greater productivity (+30%) than fixed-worker lines under high-mix low-volume demand conditions. Full article