Search Results (42)

The main thrust of the study is the need to cut down the time taken for mold changes in plastic injection molding which is fundamental to the productivity and efficiency of the process. The research encompasses Lean Manufacturing, DMAIC, and SMED which are improved using fuzzy logic and AI for rapid changeover optimization on the NEGRI BOSSI 650 machine. A decrease in downtime by 65% and an improvement in the Process Cycle Efficiency by 46.8% followed the identification of bottlenecks, externalizing tasks, and streamlining workflows. AI-driven analysis could make on-the-fly adjustments, which would ensure that resources are better allocated, and thus sustainable performance is maintained. The findings highlight how integrating Lean methods with advanced technologies enhances operational agility and competitiveness, offering a scalable model for continuous improvement in industrial settings. Full article

The Moroccan garment industry faces challenges in scheduling small order batches, often hindered by traditional product family-based methods that increase downtime by 15–20%. This study proposes a clustering-based scheduling approach, grouping garments by technological times rather than product families to reduce changeovers and downtime by 30–35%. A case study in a Moroccan factory with 50–100-unit batches showed a 20% lead time reduction and a 15% productivity boost. Using methods like K-Means, the approach enhances planning flexibility and resource use. This methodology offers a scalable solution for optimizing production and maintaining competitiveness in fast fashion markets. Full article

Optimizing production efficiency in Surface-Mount Technology (SMT) manufacturing is a critical challenge, particularly in high-mix environments where frequent product changeovers can lead to significant downtime. This study presents a scheduling algorithm that minimizes changeover times on SMT lines by leveraging the commonality of Surface-Mount Device (SMD) reel part numbers across product Bills of Materials (BOMs). The algorithm’s capabilities were demonstrated through both simulated datasets and practical validation trials, providing a comprehensive evaluation framework. In the practical implementation, the algorithm successfully aligned predicted and measured changeover times, highlighting its applicability and accuracy in operational settings. The proposed approach integrates heuristic and optimization techniques to identify scheduling strategies that not only minimize reel changes but also support production scalability and operational flexibility. This framework offers a robust solution for optimizing SMT workflows, enhancing productivity, and reducing resource inefficiencies in both greenfield projects and established manufacturing environments. Full article

Adopting a new milking system at a dairy farm causes various changes. This study examined the impact on udder health when changing from a conventional milking system to an automatic milking system. For this purpose, quarter milk samples were taken six times from 138 cows at one conventional dairy farm in Northern Germany over a five-week period around the time of the milking system changeover. To assess udder health, the absolute number of new intramammary infections and the causative pathogen genera and species were analysed for each individual study time point. Pathogen species were detected using matrix-assisted laser desorption ionisation time-of-flight, and the infection dynamics were analysed using two Poisson regression models. In addition, the prevalence and incidence of new intramammary infections and the infection dynamics of the four most frequently isolated pathogen species were calculated. Mixed models were used to determine the development of the new infection rate, the somatic cell count, the teat-end condition, and the udder hygiene between the individual study time points and to compare the new infection rate before and after the changeover of the milking system. After the automatic milking system had been installed, a significant increase in the quarter-level somatic cell count occurred (p < 0.001). Two days before the installation of the automatic milking system, the mean quarter-level somatic cell count was 11,940 cells/mL milk; one sampling date later, 8 days after the changeover, a mean quarter-level somatic cell count of 60,117 cells/mL milk was measured. The significant increase in somatic cell count was probably caused by the time between the last milking and the quarter milk sampling. Additionally, significantly more udders were scored as clean 8 days (95%) and 15 days (96%) after the changeover of the milking system compared to at the last sampling date (88%). Also, significantly more teat ends were classified as free of hyperkeratosis 15 days (80%) compared to 22 days (67%) after the changeover of the milking system. The highest number of absolute new intramammary infections was detected 8 days before the transition of the milking system (28.6%). The lowest number of absolute new intramammary infections occurred 8 days after the change to the automatic milking system (11.0%). Minor mastitis pathogens, such as non-aureus staphylococci and coryneform bacteria, were mainly responsible for the development of new intramammary infections. The most frequently isolated pathogen species were Staphylococcus sciuri, Staphylococcus chromogenes, Staphylococcus haemolyticus, and Corynebacterium amycolatum, with a prevalence of up to 23.9, 10.7, 8.4, and 5.3%, respectively. By comparing the new infection rate before and after the changeover of the milking system, it was possible to establish that the changeover to the automatic milking system had no significant influence on the new intramammary infection rate (p = 0.988). Therefore, this trial confirmed that the changeover from a conventional milking system to an automatic milking system had no negative influence on udder health. Full article

Coccidiosis in broiler chickens continues to be a major disease of the gastrointestinal tract, causing economic losses to the poultry industry worldwide. The goal of this study was to generate a symptomatic Eimeria maxima (1000 oocysts) infection to determine its effect on the luminal and mucosal microbiota populations (L and M) in the jejunum and ileum (J and IL). Samples were taken from day 0 to 14 post-infection, and sequencing of 16S rRNA was performed using Illumina technology. Infected birds had significantly (p < 0.0001) lower body weight gain (BWG), higher feed conversion ratio (FCR) (p = 0.0015), increased crypt depth, and decreased villus height (p < 0.05). The significant differences in alpha and beta diversity were observed primarily at height of infection (D7). Analysis of taxonomy indicated that J-L and M were dominated by Lactobacillus, and in IL-M, changeover from Candidatus Arthromitus to Lactobacillus as the major taxon was observed, which occurred quicky in infected animals. LEfSe analysis found that in the J-M of infected chickens, Lactobacillus was significantly more abundant in infected (IF) chickens. These findings show that E. maxima infection affects the microbiota of the small intestine in a time-dependent manner, with different effects on the luminal and mucosal populations. Full article

To ensure the efficient functioning of solar energy generation systems, it is crucial to have dependable designs and regular maintenance. However, when these systems or their components operate at multiple working levels, optimizing reliability becomes a complex task for models and analyses. In the context of reliability modeling in solar energy generation systems, researchers often assume that random variables follow an exponential distribution (binary-state representation) as a simplification, although this may not always hold true for real-world engineering systems. In the present paper, a multi-state solar energy generating system with inverters in series configuration is investigated, in which unreliable by-pass changeover switches, common cause failures (CCFs), and multiple repairman vacations are also considered. Furthermore, the arrivals of CCFs and the repair processes of the failed system due to CCFs are governed by different Markovian arrival processes (MAPs), and the lifetimes and repair times of inverters and by-pass changeover switches and the repairman vacation time in the system have different phase-type (PH) distributions. Therefore, the behavior of the system is represented using a Markov process methodology, and reliability measures for the proposed system are derived utilizing aggregated stochastic process theory. Finally, a numerical example and a comparison analysis are presented to demonstrate the findings. Full article

Objectives: The objective of this study was to analyse and detail surgical process improvement activities that achieve the highest economic impact. Methods: Over 4 years, a team of technicians and healthcare professionals implemented a set of Lean surgical process improvement projects at Vall d’Hebron University Hospital (VHUH), Barcelona, Spain. Methods employed in the study are common in manufacturing environments and include reducing waiting and changeover time (SMED), reducing first time through, pull, and continuous flow. Projects based on these methods now form part of the daily routine in the surgical process. The economic impact on the hospital’s surgical activity budget was analysed. Results: Process improvements have led to annual operational savings of over EUR 8.5 million. These improvements include better patient flow, better management of information between healthcare professionals, and improved logistic circuits. Conclusions: The current cultural shift towards process management in large hospitals implies shifting towards results-based healthcare, patient-perceived value (VBHC), and value-added payment. A Lean project implementation process requires long-term stability. The reason a considerable number of projects fail to complete process improvement projects is the difficulty involved in establishing the project and improving management routines. Few studies in the literature have investigated the economic impact of implementing Lean management a posteriori, and even fewer have examined actual cases. In this real case study, changes to surgical block management were initiated from stage zero. After being carefully thought through and designed, changes were carried out and subsequently analysed. Full article

While new production areas (greenfields) have state-of-the-art technologies for implementing digitalization, existing production areas (brownfields) and devices must first be upgraded with technologies before digitalization can be implemented. The aim of this research work is to use a case study to identify the differences in the implementation of machine learning (ML) projects in brownfields and greenfields. For this purpose, an ML application for the detection of changeover times on milling machines is implemented and analyzed in the brownfield and greenfield scenarios as well as a combined scenario. Particular attention is paid to the selection of sensors and features. It was found that the abundant availability of features in the greenfield scenario poses pitfalls when creating ML projects if the underlying sensors cannot be checked for their suitability. For the changeover detector use case, the best model quality was achieved for the combined scenario, followed by the greenfield scenario. Full article

The business world is becoming more competitive. Therefore, it is crucial to increase the flexibility of production by decreasing the time used in the processes of preparing the production lines for new items’ production, reducing changeover and setup times. This paper presents a case study where the main goal is to reduce the setup time of welding robots. Single Minute Exchange of Die (SMED) was implemented, using other tools such as the Spaghetti Diagram, ERCS Analysis (Eliminate, Rearrange, Combine, Simplify), Gemba Walk, Standardized Work, Flowcharts, and Pareto Diagram. The setup time decreased by 36% in the welding robots studied, decreasing the motions by 43% during the changeover process and reducing the time from the categories: “transportation”, “main”, “other”, and “waiting”. In addition to SMED implementation, this study offers an integrated study of several Lean tools and Quality tools to achieve the maximum reduction of changeover and setup times. Full article

Background and Objectives: Local anesthetics administered via epidural catheters have evolved from intermittent top-ups to simultaneous administration of continuous epidural infusion (CEI) and patient-controlled epidural analgesia (PCEA) using the same device. The latest programmed intermittent epidural bolus (PIEB) model is believed to create a wider and more even distribution of analgesia inside the epidural space. The switch from CEI + PCEA to PIEB + PCEA in our department began in 2018; however, we received conflicting feedback regarding workload from the quality assurance team. This study aimed to investigate the benefits and drawbacks of this conversion, including the differences in acute pain service (APS) staff workload, maternal satisfaction, side effects, and complications before and after the changeover. Materials and Methods: Items from the APS records included total delivery time, average local anesthetic dosage, and the formerly mentioned items. The incidence of side effects, the association between the duration of delivery and total dosage, and hourly medication usage in the time subgroups of the CEI and PIEB groups were compared. The staff workload incurred from rescue bolus injection, catheter adjustment, and dosage adjustment was also analyzed. Results: The final analysis included 214 and 272 cases of CEI + PCEA and PIEB + PCEA for labor analgesia, respectively. The total amount of medication and average hourly dosage were significantly lower in the PIEB + PCEA group. The incidences of dosage change, manual bolus, extra visits per patient, and lidocaine use for rescue bolus were greater in the PIEB + PCEA group, indicating an increased staff workload. However, the two groups did not differ in CS rates, labor time, maternal satisfaction, and side effects. Conclusions: This study revealed that while PIEB + PCEA maintained the advantage of decreasing total drug doses, it inadvertently increased the staff burden. Increased workload might be a consideration in clinical settings when choosing between different methods of PCEA. Full article

Although vision-guided robotic picking systems are commonly used in factory environments, achieving rapid changeover for diverse workpiece types can still be challenging because the manual redefinition of vision software and tedious collection and annotation of datasets consistently hinder the automation process. In this paper, we present a novel approach for rapid workpiece changeover in a vision-guided robotic picking system using the proposed RoboTwin and FOVision systems. The RoboTwin system offers a realistic metaverse scene that enables tuning robot movements and gripper reactions. Additionally, it automatically generates annotated virtual images for each workpiece’s pickable point. These images serve as training datasets for an AI model and are deployed to the FOVision system, a platform that includes vision and edge computing capabilities for the robotic manipulator. The system achieves an instance segmentation mean average precision of 70% and a picking success rate of over 80% in real-world detection scenarios. The proposed approach can accelerate dataset generation by 80 times compared with manual annotation, which helps to reduce simulation-to-real gap errors and enables rapid line changeover within flexible manufacturing systems in factories. Full article

One of the key postulates of the modern automotive industry is the increase in production efficiency while minimizing costs. In the opinion of experts from the automotive industry, meeting this condition may be the first stage on the way to preventing waste generation and implementing a circular economy model. The article presents a case study of issues related to the lean manufacturing methodology in terms of the impact of shortening the changeover time of the assembly line on the overall production efficiency. The presented considerations focus on the optimization of the production process using the SMED (Single Minute Exchange of Die) technique of a selected spare part. From the point of view of the Lean Manufacturing concept, the main goal of the SMED technique is to increase the flexibility of responding to changing customer needs by shortening the changeover times and faster responses to changing orders. The article describes the stages of implementing the SMED method and its impact on the increase in the OEE (Overall Equipment Efficiency) index, which allows for the percentage recognition of the degree of machine park utilization, which is one of the key factors for assessing energy efficiency. In addition, the benefits that have been achieved by using this method in terms of time and economy have been presented. The theoretical aspects related to the method used were supplemented with its practical implementation in order to improve the changeovers in a manufacturing company in the automotive industry. Based on the obtained test results, an analysis of the effectiveness of the measures taken to reduce the changeover time was carried out. The use of the SMED methodology contributed to a significant reduction in changeover time—by as much as 291.4 s. The burden on operators was significantly reduced—the total time and number of operations performed by them (both internal and external) was reduced. Operator paths have also been shortened using simple procedures such as changing the layout of the lines and modifying the changeover tool trolleys and tool locking system at the stations. The presented research may be helpful in answering the question whether the implementation of the SMED idea may be the key to effective resource management and, at a later stage, to the implementation of the circular economy model. In addition, the research results can find their practical application among both manufacturers of spare parts and the vehicles themselves, considering introducing process changes on their production lines in order to increase production efficiency and implementing the idea of industrial sustainability. Full article

With the increasing automation of mobile phone assembly, industrial robots are gradually being used in production lines for loading and unloading operations. At present, industrial robots are mainly used in online teaching mode, in which the robot’s movement and path are set by teaching in advance and then repeat the point-to-point operation. This mode of operation is less flexible and requires high professionalism in teaching and offline programming. When positioning and grasping different materials, the adjustment time is long, which affects the efficiency of production changeover. To solve the problem of poor adaptability of loading robots to differentiated products in mobile phone automatic assembly lines, it is necessary to quickly adjust the positioning and grasping of different models of mobile phone middle frames. Therefore, this paper proposes a highly adaptive grasping and positioning method for vision-guided right-angle robots. Full article

In Singapore, there is an increasing need for independence from manpower within the Building and Construction (B&C) Industry. Prefabricated Prefinished Volumetric Construction (PPVC) production is mainly driven by benefits in environmental pollution reduction, improved productivity, quality control, and customizability. However, overall cost savings have been counterbalanced by new cost drivers like modular precast moulds, transportation, hoisting, manufacturing & holding yards, and supervision costs. The highly modular requirements for PPVC places additive manufacturing in an advantageous position, due to its high customizability, low volume manufacturing capabilities for a faster manufacturing response time, faster production changeovers, and lower inventory requirements. However, C3DP has only just begun to move away from its early-stage development, where there is a need to closely evaluate the process parameters across buildability, extrudability, and pumpability aspects. As many parameters have been identified as having considerable influence on C3DP processes, monitoring systems for feedback applications seem to be an inevitable step forward to automation in construction. This paper has presented a broad analysis of the challenges posed to C3DP and feedback systems, stressing the admission of process parameters to correct multiple modes of failure. Full article

Driven from real-life applications, this work aims to cope with the scheduling problem of automotive glass manufacturing systems, that is characterized as a two-stage flow-shop with small batches, inevitable setup time for different product changeover at the first stage, and un-interruption requirement at the second stage. To the best knowledge of the authors, there is no report on this topic from other research groups. Our previous study presents a method to assign all batches to each machine at the first stage only without sequencing the assigned batches, resulting in an incomplete schedule. To cope with this problem, if a mathematical programming method is directly applied to minimize the makespan of the production process, binary variables should be introduced to describe the processing sequence of all the products, not only the batches, resulting in huge number of binary variables for the model. Thus, it is necessary and challenging to search for a method to solve the problem efficiently. Due to the mandatory requirement that the second stage should keep working continuously without interruption, solution feasibility is essential. Therefore, the key to solve the addressed problem is how to guarantee the solution feasibility. To do so, we present a method to determine the minimal size of each batch such that the second stage can continuously work without interruption if the sizes of all batches are same. Then, the conditions under which a feasible schedule exists are derived. Based on the conditions, we are able to develop a two-step solution method. At the first step, an integer linear program (ILP) is formulated for handling the batch allocation problem at the first stage. By the ILP, we need then to distinguish the batches only, greatly reducing the number of variables and constraints. Then, the batches assigned to each machine at the first stage are optimally sequenced at the second step by an algorithm with polynomial complexity. In this way, by the proposed method, the computational complexity is greatly reduced in comparison with the problem formulation without the established feasibility conditions. To validate the proposed approach, we carry out extensive experiments on a real case from an automotive glass manufacturer. We run ILP on CPLEX for testing. For large-size problems, we set 3600 s as the longest time for getting a solution and a gap of 1% for the lower bound of solutions. The results show that CPLEX can solve 96.83% cases. Moreover, we can obtain good solutions with the maximum gap of 4.9416% for the unsolved cases. Full article