This study investigates production bottlenecks at the packing station of PT Anta Boga Pangan Nusantara, where manual operations resulted in prolonged cycle times and reduced efficiency. The research aims to design and implement a Karakuri Kaizen–based Lean Mover to minimize work time and enhance process performance. A quantitative approach was employed, involving direct observation, time measurement, and process analysis. The implementation of the Lean Mover successfully reduced the cycle time from 158.08 seconds to 24.74 seconds, outperforming the target takt time of 27 seconds. These findings demonstrate that low-cost, energy-efficient mechanical systems can effectively eliminate non-value-added activities, balance operator workloads, and improve productivity in food industry operations. The novelty of this study lies in the application of Karakuri Kaizen within the food manufacturing sector, a field rarely explored in previous research, thereby extending its applicability beyond conventional industrial settings. The study contributes theoretically by providing empirical evidence of Karakuri Kaizen’s effectiveness in optimizing manual operations in resource-constrained environments, and practically by offering an ergonomic, sustainable, and affordable alternative to high-cost automation systems.

In work environments and industries, there are several factors that contribute to the fall of productivity and these factors have been the cause of several investigations so that one can minimize the issue of cleaner and complexity of production in mechanical machines workshops and other engineering branches, in order to provide satisfaction, safety and increased production part of the organization customer satisfaction. The planning of the physical arrangement presents itself as an aspect that can confer decisive improvements, since in addition to defining the flow of materials in the production process. The present case study aims to present a proposal for the implementation of the improved layout in the mechanical workshop of the Ethiopia “Selam workshop” located in Kotbe. The current layout of the Selam machinery workshop has exerted negative influence on issues such as production volume, system flexibility and even material and labor costs. In machining shops specifically, there are many process variables that make it difficult to work on improving the productivity index. Here, it analyzed the production process in the machining sector in which the process variables are from the high amount of shapes of the parts to the position of the machines, tools, and differentiated production devices. It analyzes the production process in two moments based on the production time. In the first, productivity before and, in the other, after the study and process changes focused on approximation of sectors, tools, using as work philosophy the Lean Manufacturing (takt time) to control the production time, especially with regard to the techniques of continuous improvement through the SPL Muther (approximation of sectors). Here are presented three layouts proposals, the first, is general occupation with new compartments or arranged compartments, the second, layout of the machinery in the line of Machining and a third layout for the flow of people and goods. Therefore, with the implementation of this project were met general aspects to the needs of the projected, bringing about changes like: reduction of complexity in production in the line of machining, creation of warehouses for raw material and finished products, increased sectorial cooperation, increase of the final quality of the service provided, enhancement of the workers' ergonomic settings.

The application of lean thinking in healthcare has gained momentum in recent years, yet its implementation continues to face persistent challenges. Among these, staff resistance and conceptual misalignment between industrial principles and clinical environments remain significant barriers. This study argues that these issues stem not from the failure of lean theory itself, but from a flawed translation of lean tools, particularly Value Stream Mapping (VSM), from manufacturing to healthcare. To address this, we propose a systematic translation model that redefines key VSM elements (e.g., customer, inventory, takt time) in a way that aligns with the operational realities of outpatient care. The model is empirically validated through two case studies conducted in Saudi Arabia: an ophthalmology clinic and a dental clinic. By applying translated VSM tools, both clinics achieved substantial reductions in and patient waiting time, without compromising value-added care. The findings support the efficacy of contextualized lean implementation and provide healthcare managers with a practical framework for operational improvement. This study contributes to bridging the gap between lean theory and its real-world application in clinical settings.

Most production lines in practice rely on some form of output control since realised cycle times fluctuate. One simple yet effective approach is flexible takt times. Since takt times are distributed over the whole production cycle, flexible takt times require an overlap of work (and thus time) zones. There are arguably three main approaches: restricted zones of overlap, free zones of overlap, and complete overlap. The first is known as variable takt, the second as bucket brigade or baton zone bumping, and the last as rotating seru or rabbit chase. This study assesses the different approaches for the first time using discrete event simulation. Results show that combining rotating seru with passing leads to the best performance in our simulated environment. An in-depth analysis further indicates a dynamic interplay of hand-off, idle, blocking and transport time that explains performance results. Findings have major implications for practice and future research.

This research develops and validates autonomous artificial intelligence agents for fault detection and self-healing in smart manufacturing systems within the context of Industry 4.0, addressing critical challenges in operational efficiency and reliability. Motivated by the need to reduce unplanned downtime and enhance production resilience, the study pursues three objectives: designing a robust AI architecture for fault detection, implementing effective self-healing mechanisms, and evaluating performance through rigorous testing. The literature review highlights gaps in temporal-spatial data integration and explainable self-healing, underscoring the potential of spiking neural networks (SNNs) and symbolic rule engines. Adopting a design science research paradigm, the proposed hybrid AI framework integrates SNNs, symbolic reasoning, and Isolation Forest algorithms, supported by industrial IoT sensor networks capturing vibration, thermal, and acoustic data. Validation was conducted through hardware-in-loop simulations, fault injection testing, and field deployments in automotive and electronics manufacturing environments. Results demonstrate a 97.3% fault detection accuracy and 89.4% self-healing recovery rate, reducing mean-time-to-repair by 31.7% and improving overall equipment effectiveness by 6.7 points, offering high annual savings for mid-sized manufacturers. Limitations include a 2.7% error margin in detection accuracy and an 83-second material regeneration latency, which exceed some high-speed production takt times. The research concludes by recommending adoption of the framework for improved manufacturing resilience and suggests future work in transfer learning and energy-efficient algorithms to enhance cross-domain scalability and sustainability.

Abstract The maritime industry has a very representative weight in the world economy, with 80% of the volume of international trade of goods transported by sea, which makes shipbuilding a relevant strategic industry. However, this industry faces important challenges not only in terms of competitiveness, but also due to its characteristics, namely very high cycle times and engineering-to-order production systems. The implementation of lean in industry has allowed the reduction of waste and costs, increased efficiency, and productivity. Thus, the implementation of these principles can contribute in a very significant way to help this industry to face the numerous challenges. Although lean principles and tools are already being applied in the shipbuilding industry, there is an absence of systematic characterisation of these practices in the literature, as well as the advantages and barriers to their application. Therefore, through a systematic literature review, the aim of this article was to compile and categorise the different lean practices, the benefits of their implementation, as well as the main adoption factors and barriers faced when implementing them in the maritime construction industry. Furthermore, a conceptual framework is also proposed with the purpose of facilitating the development of lean application in the shipbuilding industry. The implications of applying lean tools in shipbuilding for each dimension of sustainability are also analysed. The results of the review show that the implementation of lean in the context of maritime construction has been effective, with the main benefits being a reduction in the production cycle time, a reduction in costs, better utilisation of space and a reduction in the distances travelled by operators and parts, and an increase in productivity. The most frequently implemented tools are Value Stream Mapping, Takt Time, Kaizen, Kanban, and Just in Time. The barriers associated with human factors and the intrinsic characteristics of shipbuilding were predominant as obstacles to implementing lean. Future research in this industry is essential, particularly in quantifying the benefits and identifying different strategies for implementing these initiatives.

This applied, explanatory-level study addresses the design and implementation of a manufacturing cell to reduce the accumulated lead time in a molecular biology laboratory in Lima, Peru, during the COVID-19 pandemic. A detailed analysis of the initial situation was conducted, proposing the configuration of two cells decoupled by work-in-process inventory. Although the required takt time was not achieved nor a perfect balance of workloads, the results confirmed the initial hypothesis, showing a significant reduction in idle times, an improvement in workflow, and an increase in the laboratory's responsiveness. These findings highlight the effectiveness of lean methodologies in high-demand and complex contexts

PT XYZ perusahaan yang memproduksi produk farmasi, salah satunya memproduksi salep untuk pengobatan luka luar. Permasalahan utama yang dihadapi adalah tingginya waktu siklus (cycle time) pada proses filling yang melebihi takt time yang telah ditentukan perusahaan, yaitu 2.631,85 detik. Cycle time aktual mencapai 9.054,51 detik, yang menunjukkan adanya aktivitas pemborosan (waste) dalam proses produksi. Penelitian ini bertujuan untuk menganalisis penyebab pemborosan waktu di bagian produksi dan mengusulkan perbaikan melalui penerapan metode PDCA (Plan-Do-Check-Action) sebagai bagian dari pendekatan Lean Manufacturing. Metode yang digunakan mencakup wawancara, observasi langsung, serta pengumpulan data sekunder berupa waktu Setting mesin. Untuk mengidentifikasi akar penyebab masalah digunakan diagram fishbone dan metode 5W+1H, sedangkan pemetaan aktivitas dilakukan menggunakan Process Activity Mapping (PAM). Hasil penelitian menunjukkan bahwa pemborosan terjadi akibat kurangnya pelatihan operator, tidak adanya operator tetap, SOP yang tidak jelas, dan rendahnya pengawasan kualitas. Setelah dilakukan perbaikan dengan metode PDCA, cycle time berhasil diturunkan menjadi 2.631,85 detik, menunjukkan peningkatan efisiensi sebesar 6.422,66 detik dari kondisi awal. Kesimpulannya, penerapan metode PDCA efektif dalam mengurangi aktivitas tidak bernilai tambah, meningkatkan efisiensi waktu, dan mendukung kelancaran proses produksi di PT XYZ. Perusahaan disarankan untuk terus melakukan evaluasi berkala dan perbaikan berkelanjutan guna menjaga konsistensi kualitas dan produktivitas.

PT. STE produces small bracket parts for four-wheeled vehicles. In July – September 2024, transport hook products are experiencing a significant increase in demand compared to other products. It is known that in the production process of this transport hook there are still obstacles or activities that do not add value to the company. Therefore identification of waste is carried out in order to minimize the occurrence of this waste. The purpose of this research is to identify and minimize waste in the spot welding production process and determine the takt time in the hook transport production process. The method used is Value Stream Mapping (VSM. The results of the current state value stream mapping analysis before making improvements in the form of minimizing things that do not provide added value to the hook transport production process get a cycle efficiency process value of 74%, while in the expected future state value stream mapping analysis efforts are made to minimize waste and improve value added activity by obtaining a cycle efficiency process value of 94% or increase of 20% and the results of the analysis by calculating the take time in the spot welding production process is equal to 52.85 seconds, this means that in carrying out the hook transport production process it takes 52.85 seconds/product to be able to fulfill requests from consumers

A methodology to micro-machine glass with a chamfered edge geometry using a single-pass ultrafast laser process is described. An input laser source is shaped into three spatially and temporally coordinated Bessel beamlets with controlled phases, each of which forms a single segment of a continuous C-chamfer shaped intensity profile. Beamlets are simultaneously deployed to induce damage (nanoperforation) extending through the thickness of a glass sample in a single laser shot. The methodology is experimentally demonstrated, generating controlled nanoperforation contours which produce C-chamfer shaped glass edges in a single laser cutting pass. Chamfered glass parts can be easily separated along nanoperforation contours via application of simple mechanical bend stress, with no need for additional post-process release steps, such as etching. This method has the potential to create laser-based chamfers for industrial glass processing applications with fast takt times, minimal waste, and low cost-to-throughput ratios.

More and more companies worldwide have implemented the Lean Manufacturing Methodology to improve Quality by focusing on standardized processes and continuous improvement through the elimination of waste. The Dairy Industry has been one of the most important activities in Ecuador and requires adapting this Methodology in its processes. The objective of this study is to improve the cheese production process, focusing on waste elimination and continuous improvement. For this, the VSM (Value Stream Map) has been carried out to know the flow of materials of the company, as well as the times that add and do not add value, the actual measurement of the times of how long the process takes has been carried out and with this Information was obtained from the indicators takt time, cycle time, real time; The evaluation of the OEE percentage and finally the balance diagram were also made. After having the baseline, the application of tools such as 5S, Kaizen, TPM and the redistribution of facilities was proposed. The results obtained indicated that there are bottlenecks in the Draining and Grinding and Molding subprocesses and the OEE percentage would be oscillating at 76%, however, when the improvements were proposed, it would rise to 82% and there would no longer be bottlenecks. , thus evidencing that the Implementation of Lean Manufacturing Tools is of great importance since it improves the organization even in the work environment.

Constituting the biggest challenge in any manufacturing company’s product delivery, operational excellence can be accomplished by obtaining the best Quality, Cost, and Delivery (QCD). The delivery parameter has been an issue for the ABC Company, an Indonesian auto part manufacturer, having automotive manufacturers as customers, since its cycle time has been found to be lower than its takt time. This could jeopardize the company’s status in that it could degrade its customer service level. Thus, the company immediately initiated a quality control circle, especially when it was revealed that its production cycle time in Core Assy Line 3 was 49 s more than its targeted 41.7 s takt time. The team was then committed to reducing it to 39.2 s, accounting for a 20% reduction. A method named 8 steps and 7 tools was deployed under the Plan-Do-Check-Act (PDCA) approach to solve the specific problem. This method guided the team to find five root causes of the problem, while five solutions were equivalently provided. As a result, the achieved cycle time reduction was from 49 to 38.9 s, that is, a 21% decrease, capable of securing the company’s relationship with its customers and granting an order increase.

The company under study is a company specializing in producing cosmetics. Sales of the company have declined sharply in recent years due to failure to deliver on time. After analyzing, the root causes of the problem of low on-time delivery rate are high production lead time and high cycle time in the packaging processes. The study applied value stream management, VSM, to improve packaging production process of the company. The primary objectives were to reduce the production lead time and reduce production cycle time to meet the takt time, thereby improving the on-time delivery rate and the company’s sales. The results had shown that the lead time had been reduced by 46.23% from 42.4 to 22.8 h, the cycle time had been reduced 31.25% from 32 to 22 s, meeting the takt time.

This systematic review explores the integration of Lean Six Sigma (LSS) methodologies with Digital Twin (DT) technologies to assess their combined impact on manufacturing efficiency and performance valuation. With the growing need for real-time monitoring, predictive analytics, and continuous improvement in industrial environments, the fusion of LSS and DT offers a promising hybrid framework for enhancing productivity, reducing defects, and enabling adaptive control mechanisms. The review followed the PRISMA 2020 guidelines to ensure transparency and rigor, resulting in the inclusion of 72 peer-reviewed articles published between 2010 and 2024 across multiple sectors including aerospace, automotive, pharmaceuticals, electronics, and FMCG. Findings indicate that the integration of LSS-DT systems leads to significant improvements in cycle time reduction, takt time optimization, predictive maintenance, and real-time quality monitoring. A notable trend across the reviewed literature is the emergence of hybrid performance metrics that blend traditional Lean Six Sigma KPIs with digital system-level indicators such as simulation fidelity, data latency, and predictive control accuracy. While sectors like aerospace and automotive demonstrate high maturity in implementing these integrated frameworks, others—particularly small and medium-sized enterprises—face challenges related to cost, digital literacy, and infrastructural readiness. The review also identifies theoretical tensions between the deterministic nature of traditional Lean Six Sigma models and the probabilistic, adaptive capabilities of digital twin systems. Despite these challenges, the synthesis of findings confirms that LSS-DT integration fosters a culture of continuous improvement and operational resilience supported by data-driven decision-making. This study contributes to the evolving discourse on Industry 4.0 by offering an in-depth, cross-sectoral evaluation of LSS-DT convergence and proposing new directions for hybrid performance management in advanced manufacturing systems.

The concept of Lean Manufacturing is a methodology focused on eliminating waste in various activities through the application of five key principles: defining value, mapping the value stream, ensuring flow, establishing pull, and pursuing perfection. Starting with the identification of value based on product sales, it was determined that industrial rack product is the top-selling product. A Current Value Stream Map (Current VSM) was created to illustrate value-adding activities within the production process and highlight sources of waste. The analysis identified inefficiencies in the production processes of side frames, beams, and packaging, which hindered the ability to meet the target takt time of 60 seconds per unit. Once the processes requiring improvement were identified, strategies for optimization were developed, leading to the creation of an Improved Value Stream Map (Improve VSM). The implementation of waste reduction measures resulted in a significant decrease in production cycle time, from 104 seconds per unit to 60 seconds per unit—a reduction of 42.31%, enabling compliance with the target takt time. Ultimately, the complete elimination of waste led to the creation of an Ideal Value Stream Map (Ideal VSM). This was achieved by incorporating pull system and continuous u-shaped line principles and consolidating workstations to minimize non-value-adding activities. These improvements not only enhanced production efficiency but also maximized the ability to meet customer demands and contributed to building a competitive advantage.

Lean manufacturing embraces the principle of doing more with less by removing non-value-added activities from manufacturing processes to preserve effectiveness, flexibility, and profitability. Predictive maintenance in production stages are more critical since it involves machines which are prone to failure and a post failure maintenance stagnates the production which creates bottlenecks due to machine failures. Hence in this work a novel intuitive fuzzy syncretic lean frame work has been implemented to incorporate the need of intelligent systems. The framework is divided into phases which employs Fuzzy logic with embedded smart sensors for effective utilization of man machine and materials in order to improve the effectiveness of a production floor. A novel time based forecasting is done in the design phase which implements the lean tool Takt time. The manufacturing phase uses the sensors to determine the predictive maintenance of the machines thereby implementing continuous flow as the lean tool and the inspection phase uses smart sensor system for real time continuous monitoring of the machining process thereby incorporating Poka-yoke as a lean tool. Thus by implementing the framework the overall equipment effectiveness is achieved which helps in achieving continuous flow of products and defect free products in any production firm.

An investigation of mixed-model assembly line balancing problem with uncertain assembly time in remanufacturing

Abstract Background This research emphasizes the profound impact of intestinal parasitic infections on developing countries, particularly in regions such as sub-Saharan Africa, South and Central America, China, and East Asia. With over 1.5 billion people globally affected and 450 million facing serious illness and a mortality rate of 155,000 cases per year, the socio-economic hindrances posed by these infections necessitate innovative approaches for control and eradication. The integration of artificial intelligence (AI) and machine learning (ML) into parasitology, exemplified by the “Automated Diagnosis of Intestinal Parasites” (ADIP), from brazilian Portuguese “Diagnóstico Automatizado de Parasitas Intestinais” (DAPI) system, showcases a paradigm shift. This advanced system, combining simple and complex decision-making mechanisms, demonstrates promising results, achieving high agreement compared to TF-Test (three fecal test). Methods Data were extracted through reports from the laboratory information system (LIS) from January-December 2023. TF-test was replaced by ADIP system in October 2023. Data were analyzed using Microsoft Excel software, with a bibliographic survey in national and international repositories. Results The parasitology laboratory of AFIP implemented artificial intelligence (AI) with ADIP equipment associated with system LIS automation, automating the analysis of approximately 38,000 monthly stool samples. The ADIP classification, image analysis and subsequent algorithm allowed a reduced examination time, since approximately 90% of samples could be released automatically, optimizing the whole process. In addition, after a three-month period using only ADIP, positivity results increased from 7,63% (TF-test) to 9,53%. Our database is periodically reviewed by specialized professionals who validate positive results, ensuring the security of information obtained by artificial intelligence, bringing efficiency, safety, and quality to the laboratory processes. Conclusions Artificial intelligence (AI) in parasite identification and the automated results system promises a bright future. Collaboration between the scientific community and data scientists is crucial to enhance laboratory processes. Through these tools, it is possible to focus on continuous improvements, increased efficiency, and, most importantly, without sacrificing accuracy and result quality. With new technologies associated with the parasitology field, detailed records can be ensured, previously challenging to obtain, showcasing each step from result acquisition to issued report. Process improvement in parasitology brings optimizations, suggesting the potential for team reduction without compromising quality and improving the takt time.

Improving quality and laboratory testing turnaround time (TAT) is a constant challenge for a clinical laboratory. The formulas that describe the best way to manage these goals are outlined in International Organization for Standardization standards. According to standards, improvement must be timely and continuous. Lean methodology is a tool to meet this requirement. One of the fundamental elements of Lean is a systematic approach to process improvement by removing waste to create value for the end-user (eg, patient) of the service. This methodology can be adapted in resource-limited settings. The aim of this study was to test the application of Lean methodology in urinalysis. Lean has various collections of tools and concepts. We applied the most useful for the clinical laboratory: Gemba walk, Takt time, cycle time, and value-stream mapping. Finally, we created and approved workplace standards to improve the performance of urinalysis. We compared the TATs of urinalysis tests before optimization, immediately after, and long after (~5 months). We found that TATs had significantly shortened. The TATs of emergency (STAT) urine tests immediately after optimization improved: automated microscopy to 16% (P =.194), fully automated test-strip to 23% (P = .0172), and standardized urine sediment examination to 20% (P =.0048). The TATs of routine urine tests also improved immediately after optimization: automated microscopy to 18% (P <.0001), fully automated test-strip to 11% (P =.0025), and standardized urine sediment examination to 18% (P =.0011). After 5 months of Lean application within the urinalysis laboratory, TATs of routine urine tests remained improved; however, the improvement of STAT urine test TATs dropped to approximately 4%. The application of the Lean methodology shows significant improvement in TATs of processes in our laboratory.

Advances in industrial technologies are growing rapidly, the Company is trying to make periodic improvements to maintain its competitiveness by selecting the correct working method, the Tangerang ceramic industry is an industry engaged in the manufacture of porcelain, in January-December 2021 the production output never reaches the given standard company. The purpose of this research is to find out the cause of the non-achievement of the production target in January-December 2021, find the root of the problem and provide improvements to the non-achievement of the production target. The method used in this study is Line Balancing to calculate the line efficiency value of the Tangerang ceramic industry and find bottleneck stations that result in not achieving production targets, in this study fishbone diagrams and 5why are also used as additional tools to find the root of the existing problems. The results of this study indicate that the production value on the biscuit loading assembly line is 77.56% with a bottleneck at the finishing station with a cycle time of 32.82sec, or a standard time of 36.102 sec exceeding the standard takt time given to achieve the target of 1,800 pcs/shift by Therefore, improvements were made by increasing the number of special finishing operators, replacing raw materials with better quality, re-setting the machine or upgrading some spare parts, every item to be dismantled has been prepared near decha. From the results of the improvement in production output from January to March 2022, it increased by 84.83%. Keywords: Line Balancing, Porcelain, Bottle Neck, Fishbone Diagram, 5 Why, Line Efficiency, Calculation of Standard Time.