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The use of Additive Manufacturing (AM) technology has largely increased in the last years. Because of its large differences from conventional technologies, the use of AM in production systems might call for new strategies in production planning and control. To this aim, this paper proposes analytical models to predict aggregate performance measures such as flow time, work in process, and production throughput, for production systems characterised by Laser Powder Bed Fusion AM technology. These indicators could be used both in operations strategy development and in technology comparison. The proposed models differentiate for their detail of the analysis and the number of input parameters that need to be estimated. The results show that the level of detail of the model affects the analysis leading to quite different values of the performance measures, especially in the case of highly saturated systems. Also, a discussion about the applicability of the proposed model to other AM technologies show whether and to what extent the proposed models can be applied for modelling other AM technologies. [ABSTRACT FROM AUTHOR]

Order release optimisation is essential in production planning, especially in discrete manufacturing. Order release planning models with load-dependent lead times must anticipate the time-dependent work-in-process and output for any given release schedule and thus require an anticipation model that approximates the time-dependent behaviour of queueing systems. We present a generic optimisation model for order release planning in stochastic, non-stationary manufacturing systems that includes a well-defined interface for the anticipation model. We develop two stationary backlog carryover (SBC) approaches to approximate time-dependent queueing behaviour and prove their consistency with the order release model. The resulting nonlinear programming model is shown to be a special case of the well-known clearing function models. A numerical study demonstrates that the optimised order releases for different demand patterns are close to the optimum that results from simulation-based optimisation even for extreme demand and release patterns. The resulting output closely matches the simulated output with some deviations. [ABSTRACT FROM AUTHOR]

Production planning and scheduling for companies with divergent processes, where a single component can be transformed into several finished products, are challenging as planners might face material misallocation issues. In this paper, we address the problem of managing a divergent process with DDMRP stock buffers, where different finished products are bottled with the same component having a fixed batch size. An allocation decision needs to be made to determine the quantities of finished products to be bottled. This study is motivated by a real-life problem faced by a dermo-cosmetic company. We compare and analyze by simulation nine different policies triggering allocation decisions. The first policy is the classic DDMRP rule, while the others are new policies, including a virtual buffer of a generic finished product and ConWIP loops, delaying the allocation decision. Our results show that the policy combining the classic DDMRP rule and a ConWIP loop surrounding a part of the process reduces the work-in-process by 34% compared to the classic DDMRP while ensuring high customer service rates and control of flow times. [ABSTRACT FROM AUTHOR]

In order to regulate work in process (WIP) to the desired value in the job shop production control system, capacity adjustment as an effective and efficient measure, which is typically achieved by flexible staffs and working time. In this paper, instead of traditional labour-oriented approaches, we consider a machinery-based capacity adjustment via reconfigurable machine tools (RMTs) to compensate for unpredictable events. To this end, we employ model predictive control (MPC) in combination with genetic algorithm (GA) to explicitly consider complex reconfiguration strategies and address the related integer assignment optimisation problems. To further reduce energy consumption and avoid frequent and unnecessary reconfigurations while keeping a certain level of performance, we adopt an event-triggered MPC scheme with the proposed 'Double-layer event-triggering conditions'. Through extensively illustrated simulations, we demonstrate the effectiveness and plug-and-play availability of the proposed method for a six-workstation four-product job shop system and compare it to a state-of-the-art method. [ABSTRACT FROM AUTHOR]

The CNC machining scheduling problem is a classic flexible job shop scheduling problem (FJSSP) that has been proven to be NP-hard. Although there has been extensive research on FJSSP, its applications in real-world CNC machining scheduling problems have received limited attention, with few related papers. In reality, several critical characteristics within the CNC machining industry can significantly impact the scheduling problem, such as process plan flexibility, multiple resource constraints, and lot streaming. This study aims to establish a scheduling system for the CNC machining industry that integrates order information, work in process information, and the aforementioned characteristics, using a hybrid multi-objective genetic algorithm (HMOGA) combined with local search. The optimal parameter combination for HMOGA is determined through a design of experiments, while the effectiveness of local search is evaluated using computational analysis. Finally, real data from a company is used to validate the proposed method. The results demonstrate that the scheduling system developed in this study effectively addresses real-world CNC machining scheduling problems. [ABSTRACT FROM AUTHOR]

We address three variants of the two-dimensional cutting stock problem in which the guillotine cutting of large objects produces a set of demanded items. The characteristics of the variants are the rectangular shape of the objects and items; the number of two or three orthogonal guillotine stages; and a sequencing constraint that limits the number of open stacks to a scalar associated with the number of automatic compartments or available space near the cutting machine. These problems arise in manufacturing environments that seek minimum waste solutions with limited levels of work-in-process. Despite their practical relevance, we are not aware of mathematical models for them. In this paper, we propose an integer linear programming (ILP) formulation for each of these variants based on modelling strategies for the two-dimensional guillotine cutting stock problem and the minimisation of the open stacks problem. The first two variants deal with exact and non-exact 2-stage patterns, and the third with a specific type of 3-stage patterns. Using a general-purpose ILP solver, we performed computational experiments to evaluate these approaches with benchmark instances. The results show that several equivalent solutions of the cutting problem allow obtaining satisfactory solutions with a reduced number of open stacks. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between collaborative robot (CR) parameters and worker utilization and system performance in human–robot collaboration (HRC) environments. We investigated whether optimized parameters increase workplace efficiency and whether adapting these parameters to the individual worker improves workplace outcomes. Three experimental scenarios with different CR parameters were analyzed in terms of the setup time, assembly time, finished products, work in process, and worker utilization. The main results show that personalized CR parameters significantly improve efficiency and productivity. The scenario in which CR parameters were tailored to individual workers, balanced the workload, and minimized worker stress, resulting in higher productivity compared to non-people-centric settings. The study shows that personalization reduces cognitive and physical stress, promotes worker well-being, and is consistent with the principles of human-centered manufacturing. Overall, our research supports the adoption of personalized, collaborative workplace parameters, supported by the mathematical model, to optimize employee efficiency and health, contributing to human-centered and efficient HRC environments. [ABSTRACT FROM AUTHOR]

The integrity of product assembly in the precision assembly industry significantly influences the quality of the final products. During the assembly process, products may acquire assembly defects due to personnel oversight. A severe assembly defect could impair the product's normal function and potentially cause loss of life or property for the user. For workpiece defect inspection, there is limited discussion on the simultaneous detection of the primary kinds of assembly anomaly (missing parts, misplaced parts, foreign objects, and extra parts). However, these assembly anomalies account for most customer complaints in the traditional hand tool industry. This is because no equipment can comprehensively inspect major assembly defects, and inspections rely solely on professionals using simple tools and their own experience. Thus, this study proposes an automated visual inspection system to achieve defect inspection in hand tool assembly. This study samples the work-in-process from three assembly stations in the ratchet wrench assembly process; an investigation of 28 common assembly defect types is presented, covering the 4 kinds of assembly anomaly in the assembly operation; also, this study captures sample images of various assembly defects for the experiments. First, the captured images are filtered to eliminate surface reflection noise from the workpiece; then, a circular mask is given at the assembly position to extract the ROI area; next, the filtered ROI images are used to create a defect-type label set using manual annotation; after this, the R-CNN series network models are applied to object feature extraction and classification; finally, they are compared with other object detection models to identify which inspection model has the better performance. The experimental results show that, if each station uses the best model for defect inspection, it can effectively detect and classify defects. The average defect detection rate (1-β) of each station is 92.64%, the average misjudgment rate (α) is 6.68%, and the average correct classification rate (CR) is 88.03%. [ABSTRACT FROM AUTHOR]

This paper proposes a novel global scheduling approach for cycle time control strategy in large complex manufacturing systems with multiple workcentres, such as semiconductor manufacturing systems. The interaction between workcentres is taken into account by using global information such as release quantities, the Work-In-Process (WIP), cycle time targets and machine capacities. Local scheduling decisions in workcentres are steered by production targets, i.e. quantities of products to complete in each operation and each period on a scheduling horizon. These global production targets are determined by a mathematical model (global scheduling model), which optimises the satisfaction of cycle time targets. One of the major innovations of the proposed model is that it relies on the temporal trace of the WIP. The mathematical model is coupled with a generic multi-method simulation model for evaluation purpose. Computational experiments conducted on industrial data show that our global scheduling approach efficiently controls the cycle times of products. [ABSTRACT FROM AUTHOR]

The resilience of a production system is determined by its capability to respond to internal breakdowns and/or external disruptions and recover. In conventional production systems, internal disruptions such as machine breakdown are handled by parallel stations and storage buffers, which come at a cost. In this paper, we propose to use reconfigurable machines (RMs) and movable buffers (MBs) to increase the resilience of a production system. The production system is modelled using a modified Markov chain model. To reduce the computational effort, an iterative method is adopted for the production lines that have many RMs and MBs. The resilience of the production system is evaluated by a combination of production loss, steady production rate with threshold, work-in-process in Idle-area of MBs, process time of work-in-process in Idle-area of MB with threshold, and investment return. Two production systems are analysed, one with 3 operations and the other with 10 operations. The computer simulation results indicate that the resilience of a production system can be improved by more than 9% by RMs and MBs. Finally, a set of guidelines for design production systems with RMs and MBs are also given. [ABSTRACT FROM AUTHOR]

Copyright of Ingeniería (0121-750X) is the property of Ingenieria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the era where mass production is inevitable, developments in the manufacturing process have helped industries to produce goods in batches of enormous quantities. With the drastic growth in technology, it is crucial to update, and improve assembly lines continuously. This study aims to systematically understand the area where an assembly line needs improvement to enhance its process and productivity. Published articles related to assembly line improvements, lean techniques, and simulation were synthesized exhaustively. A Discrete Event Simulation model of an automated manufacturing company was developed based on the data acquired and observations. Integration of lean techniques along with simulation adds to the effectiveness of the proposed method. Crucial areas that need improvement were identified, and lean techniques such as Kaizen and Poka-Yoke were applied. The efficiency of the proposed improvements was visualized by altering the simulation model. The average WIP was reduced from 87.2 to 81.2, and the cycle time of seven stations was reduced as a result of the implementation of Lean principles. Laser Marking Station (Fixture clamping and Stopper Cylinder) and Pad Printing & Vision Inspection Station witnessed a twofold improvement in the proposed model. There was an improvement in throughput by 7.14%. The study would prove helpful for managers and policymakers to visualize the usefulness of implementing lean techniques with minimal investment. [ABSTRACT FROM AUTHOR]

Students employing problem-based learning (PBL) face complex problems admitting multiple solutions. Knowledge maps are an effective tool to support students in PBL to represent, analyze, and guide their knowledge structure. Previous studies have examined the use of knowledge mapping techniques in both individual and collaborative learning process. These studies explored how knowledge mapping influenced students' learning outcomes and their knowledge understanding, but they did not document how the map structure changed when shifting from individual to collaborative mapping process. In this work-in-process study, we collected maps from students first as individuals and then as they collaboratively worked in groups to solve a case. We examined two questions: (Q1) how does the structure of a map change when shifting from individuals to groups, and (Q2) how does the size of a group mediate these changes. We used 12 network science metrics capturing the breadth (e.g., number of edges) and complexity (e.g., number of cycles) of problems and compared these metrics in individuals versus groups (Q1) and across group sizes (Q2). Based on 44 individual maps arranged in 10 groups of four or five students, we found that (1) five metrics significantly differ (p < 0.05 in a one-way ANOVA) between individual and group maps; and (2) only the number of edges and paths are affected by the size of a group (based on Tukey's HSD test). Our first result confirms that learner-learner interactions can enhance performance. The second result shows that group sizes of four or five students have no implications on the results, hence instructors who may currently be hesitating between these two options may choose either size. Future studies may reveal whether differences exist between pairs, medium group sizes, or larger groups. [ABSTRACT FROM AUTHOR]

Estimates of production systems performance metrics, such as machine efficiency, e, system throughput, TP, lead time, LT, and work-in-process, WIP, are necessary for evaluating effectiveness of potential system modifications. Calculating these estimates requires machines MTBF and MTTR, which can be obtained by measuring up- and downtime realizations on the factory floor. A question arises: What is the smallest number of measurements required to ensure the desired accuracy of the induced estimates e ˆ , ( T P ˆ ), ( L T ˆ ) and ( W I P ˆ )? This paper provides an answer to this question in terms of serial lines with exponential machines. The approach is based on the theory of ( α , β)-precise estimates ( M T B F ˆ ) and ( M T T R ˆ ), where α represents estimate's accuracy and β its probability. Specifically, the paper calculates ( α X , β X )-precise estimates of X ∈ { e , T P , L T , W I P } induced by ( M T B F ˆ ) and ( M T T R ˆ ), and evaluates the smallest number of machines' up- and downtime measurements, which ensure the desired precision of X ˆ ∈ { e ˆ , T P ˆ , L T ˆ , W I P ˆ }. In addition, the paper develops a method for evaluating the smallest number of parts quality measurements to ensure ( α q , β q )-precise estimate of machines' quality parameter q and the desired ( α T P q , β T P q )-precise estimate of good parts throughput, T P ˆ q . The results obtained are intended for production systems managerial/engineering/research personnel as a tool for designing continuous improvement projects with analytically predicted outcomes. [ABSTRACT FROM AUTHOR]

The study examines the role of lean manufacturing principles of Single Minute Exchange of Die (SMED) and Kanban in augmenting productivity through metrics of reduction in inventory, changeover time and units produced per lot. The paper uses case study-based approach to examine the significant effects of SMED and Kanban on an emblem manufacturing setup. Primary data pertaining to emblem produced in maximum quantity was gathered. The data collection process involved identifying internal and external activities during injection molding process. Analysis of the data revealed which of the activities can be removed and which can be standardized in order to reduce setup time. The results showed that SMED method facilitated a reduction of 53% in setup time. Significantly, the method saved about 25 min in setup time per batch, leading to a total saving of 750 min per month. In addition, metrics of number of units produced daily and work-in-process inventory showed marked improvements, as the results showed a reduction by 25% and 50% respectively. The application and recording of beneficial outcomes of both SMED and Kanban in an automotive parts manufacturing company, which forms a vital link in the entire supply chain, makes the contribution of this study novel. [ABSTRACT FROM AUTHOR]

This paper is part of the work in process' doctoral thesis on drag queen art in Costa Rica, as a dissident and resistance artistic representation. It is a case study analysis based on transculturation, as a historical sociocultural interpretation method and the American Baroque, also a method for interpretation and an artistic style consolidated during Latin America national identity formation processes in the Spanish colony from 16th to 18th centuries, that for some authors continued in its neo-baroque version from 19th to 20th centuries, influencing the 21st century Costa Rica's drag queen artistic representations postmodern aesthetic. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the buffer allocation problem on a serial production line with five workstations and four buffer locations with unreliable operating conditions. Originally, this work was used as an optimization criterion to maximize the Overall Equipment Effectiveness indicator; said indicator is used to evaluate the performance of the processes in Lean Manufacturing; a comparison of the generated solution configurations is made with respect to other optimization criteria such as the minimization of the average work-in-process inventory and the maximization of Throughput. Three case studies involving the production line operating in a balanced and unbalanced manner are examined. The evaluation method used in this document is simulation. On the other hand, an exhaustive enumeration of the analyzed solution space is made. The results report the optimal allocation of buffers in the case studies and the differences that exist in the distribution of these in the optimization criteria investigated. [ABSTRACT FROM AUTHOR]

This conceptual study aims to produce rough analysis methods and visualizations for production data (formatted in time, location, and work) that can be collected from construction sites that utilize takt production. The scope is on creating methods for evaluating the soundness of the takt plan and its execution. Relevant production literature regarding takt production management and data collection are utilized in the production of the methods and visualizations. However, only imaginary production data are utilized in this study to keep the indicators as simplified and clear as possible. A total of seven indicators with varying levels of novelty are provided in the study. The proposed indicators emphasize punctual adherence to the takt schedule, homogenous production pace, avoiding trade overlapping in locations, steady work in process, and coherent short and long-term production targets. Both as-planned and as-built perspectives are considered. The proposed indicators are argued to be valuable for production management and research and development processes since they provide status information and document the progression of the production for later indicators purposes. This study also acts as a foundation for further empirical studies regarding takt production data utilization. [ABSTRACT FROM AUTHOR]

We consider a single-item production–inventory system under a base stock policy for inventory control. We model the system as a closed Gordon–Newell network. The population size of the network is equal to the base stock level, which is the sum of the finished goods and work-in-process inventory. Each exogenous demand, which follows a Poisson process, releases a production order for a new unit and increases the amount of the work-in-process inventory. When there are no items in the finished goods inventory available, arriving demand is lost. The replenishment network operates with state dependent service rates, which we assume to be increasing and concave. First, we analyze the queue length behavior of a two node system and provide conditions under which the mean queue length at the production server is convex in the number of customers in the system. We prove that this leads to convexity of a standard cost function. Using Norton's theorem, we are able to generalize our results for arbitrarily large production–inventory systems. [ABSTRACT FROM AUTHOR]

In this research, a dynamic optimization of milk-run system (MRS) managed with an IT-based Kanban (ITK) is performed. The main tasks are to i) explore how artificial intelligence may allow MRS to choose the most efficient path and ii) measure the impact on the main production parameters. The study explores the Kanban signals activating an ant colony optimization algorithm that finds the best path from supermarket to the lines. Then, genetic algorithm solves an objective function to find the optimal delivery times according to the paths found. The optimal path is dynamically found for each MRS supply cycle. Within the empirical results, significant improvements for production parameters and overall system performance have been appraised. The lead time and material handling time show a strong decrease to 39% and 48%, respectively, while work in process decreases of 22% for all assembly lines. Workstation starvation decreased by 43% and machine saturation increased by 37%. [ABSTRACT FROM AUTHOR]

Order review and release (ORR) in a job shop considering sequence-dependent setup time (SDST) is among the most challenging job shop problems. This study investigates the effect of varying setup times and workload trigger levels on ORR policies performance in a stochastic dynamic job shop considering SDST. It is essential to examine the effect of varying setup times and workload trigger levels on ORR policies, because, for different ORR policies, workload trigger level plays a major role to control the work-in-process on the shop floor. Further, in manufacturing industries, less setup time is required in some cases, but it can also be equal to or greater than the processing time in others. Promodel ® simulation software is used to develop the simulation model for conducting experiments. The performance of the system is evaluated in terms of mean lead time (MLT), mean throughput time (MTT), number of tardy jobs (NOTJ), and total setups (TS) performance measures. From results, it is found that for a given ORR policy and at a given setup time level, lower workload trigger level provides minimum MTT and maximum MLT, TS, and NOTJ performance measures. As the workload trigger level increases, MTT performance measure increases, whereas MLT, TS, and NOTJ performance measures decrease. Further, for a given ORR policy and workload trigger level, as the setup time level increases, MTT and MLT performance measures increase. In contrast, TS and NOTJ performance measures decrease. A stochastic dynamic job shop considering ORR and SDST where setup time is either less than, equal to or more than operation processing time is the novelty of the work. [ABSTRACT FROM AUTHOR]

One of the main problems of modern manufacturing systems is the increasing complexity related to modern Industry 4.0 technologies that are fundamentally changing manufacturing and logistics processes and operations. Industry 4.0 includes, e.g., flexible automation and robotization, which make complex manufacturing systems difficult to analyze. Some modeling and simulation methods are being used to solve industrial problems and can serve as an interface between the production level and management level. The new trend of the Digital Twin, creating simulation models as similar as possible to the real system, and a Digital Twin framework for a manufacturing line from the automotive industry, was considered. Simulation models typically start from the empty state and some warmup time is required to achieve the stable state. The Key Performance Indicators were also analyzed for the stable state. However, there are many stochastic parameters such as machinery failures, human errors, quality issues, etc., that make the real processes differ from simulated processes, and cause the instability of production throughput and changes in the Work in Process. To analyze the Work in Process in the model, initialization of the model with proper production data is required, as the Digital Twin uses data synchronization with the production database. In this paper, the digital model of a human-robot-operated manufacturing system with Work-in-Process data synchronization is analyzed, and the results of the statistical analysis of simulation experiments are presented. The obtained results show high variability of finished production, which is related to system instability due to random failures, especially when the system starts from an empty state. However, an increase in initial Work in Process results in better efficiency and stability for the whole system. The DT simulation of the manufacturing system can be very helpful, as it becomes a repository of knowledge about the real system and enables the analysis of its dynamics. However, for proper functionality, the model should include information about the current WIP state, which enables the start of the simulation with exactly the same number of queues as in the real system. The presented method can also be used in similar enterprises from other industries, especially for those with discrete processes or high WIP variability, and for further synchronization of other DT parameters. [ABSTRACT FROM AUTHOR]

In response to Industry 4.0 and the rise of intelligent manufacturing, this study develops a system combining Long Short-Term Memory (LSTM) Neural Networks and a Multi-Objective Genetic Algorithm to improve prediction and optimization in manufacturing scheduling. A novel model predicts work-in-process (WIP) inventory using LSTM neural networks, accommodating dynamic changes in production. A manufacturing scheduling model is also created and solved using a multi-objective genetic algorithm, simplifying the resolution process and obtaining practical solutions. These methods provide a valuable approach to optimizing production scheduling in intelligent manufacturing, enhancing efficiency and economic gains. [ABSTRACT FROM AUTHOR]

Although efforts to improve the productivity of semiconductor fabs have mostly focused on processing machine scheduling, recent productivity drops due to insufficient automated material handling system (AMHS) resources have made the efficient control of AMHS a major issue in improving overall productivity. This study introduces a storage prioritization procedure (SPP) for the effective allocation of work-in-process (WIP) to storage devices is applied to a real-world 300 mm fab. The proposed SPP utilizes a minimum-cost flow-based model to generate priority lists of storage devices for wafer lot transfers after determining the push or pull strategy for each machine group. Experimental studies are conducted according to four simulation scenarios that demonstrate the superior performance of the SPP. The field application results verify the SPP performance in the real-world fab. The productivity improvement due to the SPP is estimated to be tens of million dollars during the two months of the study period. [ABSTRACT FROM AUTHOR]

The necessity of optimum safety stock is really essential for any smart production system. For this reason, the effect of autonomation policy makes a big difference with the basic traditional automation policy. Basically, for a long-run production system, a process may transfer to an 'out-of-control' state from an 'in-control' state due to labour problems, machinery problems, or any kind of energy problems. During this 'out-of-control' state, machines produced imperfect items instead of perfect items. As a result, an inspection is required to identify the imperfect ones. Until now, this inspection has been utilised by human beings through the traditional automation policy and inspection errors may occur. To perform an error-free inspection, an autonomation policy is examined in this model to detect imperfect items from the production process, which makes the process smarter. The defective rate is random and follows a certain distribution. A budget and a space constraints are adopted, which makes the model non-linear with a constraint problem. Contradictory to the existing literature, the demand is price- and quality-sensitive together in a smart production system. To solve this non-linear problem with an optimised value of backorders, number of delivery lots, safety factors, and collection rate, a non-linear optimisation technique (Khun–Tucker optimisation technique) is employed. A numerical example and sensitivity analysis are provided to illustrate the model. The result finds that the optimum autonomation policy can save work-in-process inventory at the optimum value of the decision variable in the proposed model. [ABSTRACT FROM AUTHOR]

During the abnormal operations before breakdown of a multistate manufacturing system, product quality loss could systematically characterise the affected economic cost in advance. However, few studies have considering the valuable quality loss data, thus, a novel risk-oriented optimisation approach of integrated maintenance is proposed considering the quality loss of work-in-process (WIP) obtained from the manufacturing system. First, the functional risks in manufacturing systems are expounded and classified by detectable deviations and potential manufacturing defects of the finished product based on machine performance state, and product quality loss is therefore applied for preventive maintenance activities. Second, the degradation path of machine performance and its effect on WIP are clarified. Explicit risk is presented by dimensional deviations of key quality characteristics, whereas implicit risk is quantified by the influence of component- and system-level manufacturing defects on the early product usage phase. Third, different levels of maintenance actions are proposed, and the integrated preventive maintenance plan for the entire production horizon is obtained by minimising product quality loss and PM investments. The optimal decision combination is solved by genetic algorithm. Finally, the optimal maintenance strategy is presented to verify the superiority of this method through the analysis of a cylinder head manufacturing system. [ABSTRACT FROM AUTHOR]

Parts kitting is a frequently adopted method to feed parts from a warehouse to an assembly line. While kitting allows minimisation of space occupation and Work In Process holding cost at the workstations, also simplifying materials flow and supporting manual assembly, it is penalised by high workforce cost for manual kits preparation. For this reason, automated kitting systems have been also proposed although their practical application is somewhat limited owing to the relevant capital investment and scarce performances of robotised kitting systems. Moreover, economic models allowing a quantitative comparison of manual and automated kitting systems are not yet available in the literature. As a contribution to fill this gap, in this paper a cost model useful to compare manual and automation-assisted parts retrieval and kitting systems is presented. The model can be used as a decision-making tool when planning and justifying kitting systems. The model includes capital investment, workforce, space occupation and quality costs. A case study as an application example is also included to demonstrate the model capabilities. Results show that automation-assisted kitting systems can be competitive in comparison to manual kitting and that break-even conditions can be also identified by the proposed method. [ABSTRACT FROM AUTHOR]

Lot splitting is an important strategy for avoiding the starvation of workstations, for accelerating the progress of jobs, and ultimately for improving overall due date performance. While lot splitting has received much attention in the extant literature, the use of alternative lot transfer policies that determine how the flow of lots through the production system is synchronised has been largely neglected. This study uses simulation to assess the performance of different lot synchronisation policies at release and different lot transfer policies on the shop floor in a ConWIP (Constant Work-In-Process) controlled job shop. The results suggest that different approaches should be applied at the release and shop floor levels. While lots should be synchronised in some form at order release, their progress on the shop floor should not be synchronised. Instead, lot coordination should be executed by dispatching in accordance with repetitive lots logic. The results further highlight that if lot progress is synchronised in systems that limit the workload, then lot release should also be synchronised. Otherwise, blocking may occur if lot progress on the shop floor depends on the release of lots, which in turn depends on lot progress. These findings have important implications for research and practice. [ABSTRACT FROM AUTHOR]

We propose a method to generate magnetic skyrmions by intense laser pulses optimally focused on a magnetically ordered 2D-layer. In particular, we consider few-cycle intense pulses with the magnetic vortex structure near the focus region on the layer. The spin dynamics is modeled using the Landau–Lifshitz–Gilbert equation and includes the Dzyaloshinskii–Moriya interaction. We demonstrate that skyrmions can be observed within a few picoseconds after the end of the laser pulse. We analyze the physical picture of this process and work out which laser pulse and 2D-layer parameters are required for the generation. [ABSTRACT FROM AUTHOR]

Cycle time, which is of order of ten weeks for most products in semiconductor wafer fabrication facilities (wafer fabs), must be explicitly considered in production planning models. Cycle times depend nonlinearly on the resource workload in a wafer fab. Different data-driven (DD) production planning formulations are studied in this paper. Such formulations are based on a set of system states representing the congestion behavior of a wafer fab with work in process (WIP) and resulting output levels. Different WIP-output relations in the DD formulations are investigated. In addition, different methods are proposed to gather representative sets of system states. The DD formulations are compared with the Allocated Clearing Function (ACF) formulation with respect to profit and cost values using simulation models of a scaled-down and a large-sized multi-product wafer fab, respectively. The simulation results show that some DD variants are able to outperform the ACF formulation under several experimental conditions. [ABSTRACT FROM AUTHOR]

Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG. [ABSTRACT FROM AUTHOR]

To stay competitive on the constantly changing and demanding market, production systems need to optimize their performance daily. This is particularly challenging in labour-intensive industries, which is characterized by highly volatile customer demand and significant daily variability of available workers. The Uncertainty related to the key production parameters in the industry is causing disruptions in long-term production planning and optimization, which leads to the long lead production times, operational risks and accumulation of inventory. To address these challenges, production systems need to ensure adequate operational production planning and optimization of all variables that are influencing the productivity of their systems on a daily basis. To tackle the problem, this study elaborates the application of discrete event simulations and genetic algorithm, using the Tecnomatix Plant Simulation software, to support decision-making and operational production planning and optimization in the industry. The simulation model developed for this purpose considers: customers demand changes, variable production times, operationally available resources and production batch size, to provide an optimal production sequence with the highest number of produced pieces and the lowest total work in process (WIP) inventory per day. To demonstrate the efficiency of the methodology and prove the benefits of the selected optimization approach, a case study is conducted in the textile factory. [ABSTRACT FROM AUTHOR]

Manufacturing organizations continuously strive to improve their performance to survive in the competitive market. This study aims to improve the performance of a production line by utilizing a discrete event simulation model for manufacturing the rotor part of an electric motor. While previous studies have focused primarily on technical factors, this paper addresses the shortage of research on the impact of physical ergonomics on production line performance. By integrating human movements into other improvement methods, this study proposes four strategies: one-piece flow, elimination of unnecessary human motions, their integration, and switching to a Cellular Manufacturing System (CMS). The results demonstrate that the adoption of the one-piece flow among some workstations increases productivity and utilization of resources by about 21 % and 9 %, respectively. However, the elimination of the unnecessary motions resulted in insignificant improvement due machine’s automatic nature. Lastly, the study found that converting the production line into a CMS resulted in a significant increase in productivity (32 %), maximum resource utilization (17 %), and a decrease in work in process (40 %). [ABSTRACT FROM AUTHOR]

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Purpose: Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms. Design/methodology/approach: To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created. Findings: To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS. Originality/value: Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance. [ABSTRACT FROM AUTHOR]

Purpose: This paper proposes an integrated value stream mapping (VSM) for a complex assembly line to improve the leanness of a complex automotive component manufacturing organization. Design/methodology/approach: This study depicts the application of VSM at the case organization, where top management is concerned about the challenges of higher cycle time and lower productivity. Gemba walks were conducted to establish the concept of "walk the flow, create the flow" along the assembly line. The multi-hierarchical cross-functional team developed the current value stream map to know the "as-is" state. Then, the team analysed the current VSM and proposed the future VSM for the "to-be" state. Findings: The integrated VSM shows different processes and work cells, various wastes, non-value-added activities, cycle time, uptime and the material and information flows for both products of the assembly line on the same map. The integrated VSM reduced cycle time, non-value-added activities, work in process inventory and improved line efficiency and production per labour hour for both the products, simultaneously. Research limitations/implications: The limitation of the study is that the study focussed only on the application of VSM for one complex assembly only. Future research may be conducted using the developed integrated VSM approach in other complex production environments. Practical implications: Managers can identify and reduce system waste by incorporating the concept of integrated VSM in a complex production or assembly environment where two or more products are being manufactured/assembled with low similarity. Originality/value: The application of VSM for assembly lines is highly challenging because of merging flows, a large number of child parts in the lines and assembly of more than one product on the same line. [ABSTRACT FROM AUTHOR]

This study aims to investigate the effect of the leaf-spreading process on the flavor quality and biochemical components of white tea during withering. Under the indoor air conditions preset at 20-22 ℃ and 55%-65% relative humidity (RH), the static withering on bamboo sieves (0.5 kg fresh leaves per sieve: diameter (Φ) = 90 cm) was used as the control (Immobility). Tea samples were acquired by thin or thick piling-up, namely Bingshai or Duiqing when the weight loss rate of fresh tea shoots reached 65%, 70%, and 75%. The results showed that there were the similar sensory qualities in all tea samples. However, the freshness of the aroma decreased, and the sweetness of the taste increased in the white tea samples with Duiqing, compared with the Immobility and Bingshai. The quality of tea samples with the late Bingshai (4 to 8 sieves of work in process (WIP) merged into 1 sieve when the weight loss rate arrived at 70%) was slightly better than those with the early Bingshai (2 to 6 sieves of WIP merged into 1 sieve when the weight loss rate reached 65%). Furthermore, the best sensory qualities of the tea samples were produced from the thinnest Bingshai than Immobility. The best quality white tea sample was acquired with the thickest Duiqing (6 sieves of WIP merged into 1 basket) when treated for the same length of time (2 days) and different thicknesses (2 to 6 sieves of WIP merged into 1 bamboo basket: diameter (Φ) = 46 cm, height (H) = 72 cm) of Duiqing at the weight loss rate of 75%. Additionally, the WIP was preferred for the shortest duration (2 days), if treated with a different length of time (2 to 6 days) at such thickness of Duiqing. Although no regular changes were seen in the contents of catechins, alkaloids, and the main free amino acids among different treatments, the levels of proline (sweet) and some floral fruit components (phenylethanol, nerol, and geraniol) were significantly reduced in the white tea samples from the Duiqing process group, compared with the Immobility/Bingshai process group. The biochemical pattern recognition showed that all white tea samples were divided into two groups, i.e., Immobility/Bingshai and Duiqing process groups. The Duiqing process effectively regulated the biochemical compositions in the white tea samples, with an increase in the content of fatty acids, alkanes, norisoprenoids, and aldehydes. The 23 chemical compounds (such as nerol, citral, and vanillin) were considered the most important markers to distinguish them from each other. These findings can provide a strong reference to regulating the flavor quality of white tea using leaf spreading. [ABSTRACT FROM AUTHOR]

Although a significant amount of research exists on the implementation of the CONstant Work In Process (CONWIP) production control strategy in different types of manufacturing environments, the challenge posed by the complex flow of multiple products through the case manufacturing system of this work necessitates defining a unique type of item release rule to operate with the CONWIP control. The case system is a chair cover production line, which has sets of cross-trained teams that can process its different product models with different levels of efficiency. This work focusses on the CONWIP control strategy, but with the introduction of a new item release rule for prioritising items for release into the system. Results from simulation experiments show that operating CONWIP with an item release rule that is synchronised with the work rate of each of the system's cross-trained teams improves its performance. In comparison with a First in First out (FIFO) rule, this item release rule shortens the system throughput time. It also increases the chances of items being processed by the team most suitable for them, thereby minimising the quality and efficiency issues that might occur in systems that consist of teams with varying levels of proficiency for processing the different product models. Irrespective of the item release rule that is applied, CONWIP achieves a better distribution of workload amongst the teams than a Push control achieves. [ABSTRACT FROM AUTHOR]

Workload Control is a production control concept for high-variety shops built on the principle of input/output control. The literature, however, has argued that input/output control overemphasises throughput improvements to the detriment of the timing of individual orders and, consequently, that it needs to be supplemented by a preceding customer enquiry stage where due dates are set. Yet, although there are broad separate literature streams on due date setting, order release, and output control, there is a lack of research on the three functions together. In response, this study uses simulation to assess the combined performance effect of all three functions. Results show that each control function can be related to a specific performance objective. The degree of emphasis that should be placed on each function, therefore, depends on a company's specific performance needs. Due date setting and capacity adjustments (output control) are shown to support each other as they address different performance objectives. Meanwhile, order release (input control) is effective in reducing work-in-process and can play a role in making throughput improvements when capacity adjustments are not possible. Findings enhance existing literature on the diagnosis of delivery reliability performance in high-variety shops, with important implications for research and practice. [ABSTRACT FROM AUTHOR]

Unbalanced, unreliable (UR), unpaced, merging assembly lines are simulated in this study with varying line lengths, buffer storage capacities, imbalance degrees and unequal mean operation time configurations and uneven buffer capacity (BC) allocation. This paper contributes to the literature by suggesting that, in many cases, imbalance can improve merging lines' performance, as compared to a corresponding balanced merging line. It was found that an inverted bowl or descending patterns for mean operation times (MTs), and an inverted bowl (concentrating BC towards the centre of the line) or an ascending pattern for buffer allocation, result in higher throughput (TR). In terms of average buffer level (ABL), the best pattern is a monotone decreasing order regarding MTs and a monotone increasing order with respect to BC allocation. Additionally, it was found that when considering a profit function, the best performing patterns for UR lines tend to be the patterns that reduce ABL, even when considering very low inventory holding costs; contrary to the behaviour of the profit function in reliable lines, which suggests that either patterns that increase TR or reduce ABL can lead to a good performance, depending on the values of the unitary inventory holding costs. [ABSTRACT FROM AUTHOR]

In recent years, assembly line design methodologies have included the possibility of sharing tasks between stations. These approaches increase the throughput, improving the workload balance among the stations. Sharing operations can support the management of assembly lines with task redundancy. The redundancy of the tasks between two consecutive stations improves the robustness of the assembly line to unforeseen events. A control policy that allocates the shared tasks between two adjacent stations is crucial for the performance of the assembly line. This paper proposes a fuzzy approach to distributing the workload of the shared tasks between two consecutive stations. The fuzzy model allows for the distribution of the workload between the stations in a more gradual way. Simulations were conducted to allow for a performance evaluation with a model proposed in the literature. The results show how the fuzzy model improves all the performance measures evaluated; in particular, when the inter-arrival of the raw items is rather stable. In these conditions, the reduction of the average time and its standard deviation is about 50% to 80%, while the reduction of the work in process is about 60% to 90%. These benefits are obtained with a relevant increase of the variations of the average utilization of the stations. [ABSTRACT FROM AUTHOR]

Kanban control systems have been around for decades and have been used to control work-in-process of manufacturing systems. Lately many variations of the basic control system have been developed; however, much of the work in the development and comparison of control systems has focused on a single-stage manufacturing system producing a single product type. In this research, we present procedures for optimising multiple product kanban control systems, namely Base Stock, Traditional Kanban Control System and Extended Kanban Control System (both dedicated and shared type). We then conduct a detailed simulation study to compare the performance of the systems using a common total cost measure. Numerical results show that the dedicated and shared-extended kanban control systems outperform the other two systems. The study also shows that in spite of their different schematics and contrary to conventional wisdom, the performance of dedicated and shared-extended kanban control systems doesn’t differ much. [ABSTRACT FROM AUTHOR]

We also discovered that outside large, industrial organizations, the corporate entrepreneurship strategic profile could differ depending on industry, size of the organization, and the organization's maturity. One qualitative interview participant, a manager of corporate innovation in a global chemicals industry organization, emphasized this lack of clarity in terminology: "Transformational has a lot of different meanings to a lot of companies." Innovation Models Used by Organizations Our first question investigated the innovation models large industrial organizations use. The VP of technology for a large healthcare organization said his organization was more aligned as 20 percent in core, 60 percent in adjacent, and 20 percent in transformational, which he said was "because we live in a large organization, and we have within arm's reach the opportunity to leverage adjacent innovation.". [Extracted from the article]

The maintenance conversion scheduling problem (MCSP) is faced by organizations such as those in the airline, defense, heavy equipment, and transportation industries switching from an asset maintenance program with longer, less‐frequent service visits to one with shorter, more frequent visits. One example is the United States Air Force (USAF) High Velocity Maintenance program piloted at the Warner Robbins Air Logistics Center on the C‐130 aircraft line. The USAF MCSP is complex, as planners must schedule significantly more aircraft depot maintenance visits during the conversion period and must determine the timing and specific order in which each aircraft completes a repetitive sequence of maintenance visits. The conversion is expected to yield a stable long‐term maintenance schedule, while balancing annual depot workload and operating within reasonable flow times and work‐in‐process levels. While practically important, this problem has received little to no attention in the literature. Therefore, this research formalizes the general MCSP within an optimization framework, shows the MCSP is NP‐complete, proposes a computationally effective solution approach, and shows that a balanced long‐term schedule depends critically on the conversion period schedule. Our solutions are markedly better than USAF proposed schedules and underscore the value of leveraging synergies between asset availability and maintenance efficiency. Our approach moves the focus away from batch scheduling toward a smoother, more uniform, mixed‐model type schedule that yields more stable maintenance operations and a more consistent, predictable level of aircraft readiness. The manuscript concludes with a discussion of the main theoretical and practical implications of our work. [ABSTRACT FROM AUTHOR]

Resumen: Se analizan los efectos de la pandemia en el proceso de trabajo en dos plataformas digitales de reparto que operan en Argentina y Chile: Rappi y PedidosYa. A partir de entrevistas semiestructuradas y análisis de prensa y páginas web, se constata cómo las plataformas han descargado sobre las trabajadoras y trabajadores los costos de la crisis a través del uso instrumental de la figura del contratista independiente y la intensificación del control. Los repartidores han reaccionado a esta situación a través de múltiples formas de resistencia que van desde el arriendo o préstamo de cuentas a la organización de paros internacionales. [ABSTRACT FROM AUTHOR]