Time Operations Research Articles

Guidance and Control for Safe Contactless Plume Impingement Operations to Detumble an Uncooperative Spacecraft

In recent years, the interest in proximity operations to uncooperative and non-collaborative objects has been growing and and demanding for specific technology advances to tackle these challenging cases of in-orbit servicing and removal missions. Indeed, these architectures hold a crucial role in guaranteeing future sustainable and efficient space operations. One of the main challenges of conducting robotic operations with a chaser in close proximity to an uncooperative object stems from its rotational motion. A tumbling motion of a large target object may require a costly and complex synchronisation of the servicer relative trajectory to the capture point and hinder the safety of operations due to rotating appendages. In this paper, the plume impingement strategy is employed to control the target’s tumbling motion in a contactless fashion, thus guaranteeing feasible approach and capture operations. Specifically, guidance and control strategies to be employed during this delicate and complex operation are devised, focusing on improving the safety of the trajectory while maximising the efficiency of the impingement effect during proximity flight. Simulations discuss the detumbling of a satellite of a large constellation, critically comparing delta-v cost, trajectory safety and overall time of operations.

ScPathoQuant: a tool for efficient alignment and quantification of pathogen sequence reads from 10× single cell sequencing datasets.

Currently there is a lack of efficient computational pipelines/tools for conducting simultaneous genome mapping of pathogen-derived and host reads from single cell RNA sequencing (scRNAseq) output from pathogen-infected cells. Contemporary options include processes involving multiple steps and/or running multiple computational tools, increasing user operations time. To address the need for new tools to directly map and quantify pathogen and host sequence reads from within an infected cell from scRNAseq datasets in a single operation, we have built a python package, called scPathoQuant. scPathoQuant extracts sequences that were not aligned to the primary host genome, maps them to a pathogen genome of interest (here as demonstrated for viral pathogens), quantifies total reads mapping to the entire pathogen, quantifies reads mapping to individual pathogen genes, and finally integrates pathogen sequence counts into matrix files that are used by standard single cell pipelines for downstream analyses with only one command. We demonstrate that scPathoQuant provides a scRNAseq viral and host genome-wide sequence read abundance analysis that can differentiate and define multiple viruses in a single sample scRNAseq output. The SPQ package is available software accessible at https://github.com/galelab/scPathoQuant (DOI 10.5281/zenodo.10463670) with test codes and datasets available https://github.com/galelab/Whitmore_scPathoQuant_testSets (DOI 10.5281/zenodo.10463677) to serve as a resource for the community.

Simplified state‐dependent seismic fragility assessment

AbstractEarthquakes are clustered in time and space; therefore, structures may be subjected to multiple consecutive instances of potentially damaging shaking, with insufficient in‐between time for repair operations to take place. Methodologies to evaluate the risk dynamics in this situation require vulnerability models that are able to capture the transitions between damage states, from the intact conditions to failure, due to multiple damaging earthquakes, that is, state‐dependent fragility curves. One of the state‐of‐the‐art methods for the assessment of structure‐specific state‐dependent fragility curves relies on a variant of incremental dynamic analysis (IDA), which is often termed back‐to‐back or B2B‐IDA. The computational costs typically involved in B2B‐IDA motivate attempts to simplify the evaluation of state‐dependent fragility curves. This paper presents a simplified method for multi‐story moment‐resisting frame structures, based on pushover analysis in conjunction with a predictive model for the main features of a damaged structural system, such as residual deformations and loss of stiffness and/or strength. The predictive model enables the probabilistic definition of the post‐earthquake pushover curve of a damaged structural system, given the displacement demand imposed by a preceding damaging shock. The state‐dependent fragility curves are then evaluated via IDA of single‐degree‐of‐freedom oscillators based on these pushover curves. Illustrative applications validate the ability of the proposed methodology to provide state‐dependent fragilities with reduced computational costs compared to the back‐to‐back IDA method.

Airport take‐off and landing optimization through genetic algorithms

AbstractThis research addresses the crucial issue of pollution from aircraft operations, focusing on optimizing both gate allocation and runway scheduling simultaneously, a novel approach not previously explored. The study presents an innovative genetic algorithm‐based method for minimizing pollution from fuel combustion during aircraft take‐off and landing at airports. This algorithm uniquely integrates the optimization of both landing gates and take‐off/landing runways, considering the correlation between engine operation time and pollutant levels. The approach employs advanced constraint handling techniques to manage the intricate time and resource limitations inherent in airport operations. Additionally, the study conducts a thorough sensitivity analysis of the model, with a particular emphasis on the mutation factor and the type of penalty function, to fine‐tune the optimization process. This dual‐focus optimization strategy represents a significant advancement in reducing environmental impact in the aviation sector, establishing a new standard for comprehensive and efficient airport operation management.

Risk factors, susceptibility vessel sign and thrombosis pathology for prognosis inpatients with different subtypes of acute ischemic stroke treated with mechanical thrombectomy

Abstract Purpose This study highlights the relationship between stroke subtypes, thrombosis pathology, and SVS and identifies probable risk factors affecting recanalization and outcomes in endovascular treatment. Methods A prospective study was conducted in which 53 AIS patients received intravenous thrombolysis and mechanical thrombectomy (MT) from January 2017 to December 2019 in a native Hospital. The recanalization was evaluated using modified cerebral infarction thrombolysis grade and prognosis at 3 months using modified rankin Scale (mRS). The risk factors were identified using univariate and multivariate logistic regression analyses. The thrombus samples were stained to determine their composition. Magnetic SWI was used to determine SVS. Results Age, locations of occlusion, and treatments were significantly different of TOAST subtypes (P < 0.05). The time from door to puncture (TDP) and time of operation (TO) were significantly lower in the successful recanalization group (P < 0.05). National Institutes of Health Stroke Scale (NIHSS), MT, TDP, time from onset to recanalization (TOR), and TO have significant differences between the two groups of mRS ≤ 2 and > 3. The occurrence of symptomatic intracranial hemorrhage (sICH) significantly affected the mRS score. The red and mixed thrombi were common in patients with positive SVS whereas the white thrombi were associated with the negative SVS. Conclusion Improved recanalization and prognosis was observed in early MT and when endovascular operations time was reduced.

Farmer Perceptions to Climate Variability and Adaption Strategies in Nangrahar Province

Climate change is a major obstacal for farmers in the least developed countries such as Afghanistan and adaptation care is extremely scarce. This paper provides evience on the farmers’ perceptions regarding climate change, its impact and identification of best coping strategies in Nangarhar province. To do this end, we collected primary data from 384 farmers whom we interviewd across the three most affected district in the province. We employ percent analysis and Garrett rankingmethods to estimate the farmers perceptions, impact and coping strategies regarding climate change in the area. Farthermore, farmers percieved increased change in temperature (92.22%) and occurrence of drought (91.39%) respectively. Based on study findings, drying of water resources (96.46%), crop failure (85.32%) and making sarounding dring (82,03%) were observed as major impacts on farmers livelihoods of climate change. Therefore, drilling new bore well, change in time of farm operations and farm diversification were percieved and recommended as top ranked strategies to cope with climate change in Nangarhar.

Incentive-based coordination for scheduled delivery in prefab construction

An increasing number of projects are adopting prefabrication to economize on time, labor, and materials in fixed-position layout operations, such as construction, ship building, and aircraft manufacturing. In such contexts, independent contractor and fabricator make interdependent decisions, which calls for prudent supply chain management because performance relies on coordination between their decisions. Many studies have developed integrated systems and propose various algorithms for scheduling efficiency and reliability. Nevertheless, they pay scant attention to conflicting interests amongst independent partners, which may result in subpar performance not only for the supplier but for the contractor as well. Coordination of conflicting interests has been extensively studied in economics and supply chain management; yet, those studies focus on order-quantity decisions under demand uncertainty for profit maximization, while managers in fixed-position operations are more concerned about delivery decisions under scheduling uncertainty for cost minimization. We consider the case of construction and explore a contractual scheme that aligns the agents’ decisions for coordination in a construction supply chain. Specifically, we propose a supplier rebate for coordination: the supplier grants a rebate if the contractor accepts the shipment in accordance with the delivery schedule that the contractor initially chose. We show that the optimal rebate fully coordinates the supply chain to minimize the joint supply chain costs. Thus, both the contractor and supplier benefit from the coordination by negotiating a mutually acceptable way to allocate the savings in joint costs between them. We further show that the rebate motivates the contractor to enhance its work scheduling.

Efficient CNN-based low-resolution facial detection from UAVs

AbstractFace detection in UAV imagery requires high accuracy and low execution time for real-time mission-critical operations in public safety, emergency management, disaster relief and other applications. This study presents UWS-YOLO, a new convolutional neural network (CNN)-based machine learning algorithm designed to address these demanding requirements. UWS-YOLO’s key strengths lie in its exceptional speed, remarkable accuracy and ability to handle complex UAV operations. This algorithm presents a balanced and portable solution for real-time face detection in UAV applications. Evaluation and comparison with the state-of-the-art algorithms using standard and UAV-specific datasets demonstrate UWS-YOLO’s superiority. It achieves 59.29% of accuracy compared with 27.43% in a state-of-the-art solution RetinaFace and 46.59% with YOLOv7. Additionally, UWS-YOLO operates at 11 milliseconds, which is 345% faster than RetinaFace and 373% than YOLOv7.

Comparison between percutaneous short-segment fixation and percutaneous vertebroplasty in treating Kummell's disease: A minimum 2-year follow-up retrospective study.

Percutaneous kyphoplasty (PKP) or percutaneous short-segment fixation (PSSF) is often used to treat Kummell's disease. However, it is not clear which treatment is better for patients. To retrospectively compare the clinical efficacy of PVP and PSSF for the treatment of Kummell's disease. 60 patients were involved in this research and the period of follow-up was at least 2 years. 27 of them were treated with PVP (Group I) and the rest who received PSSF (Group II). The visual analog scale (VAS) and radiographic indexes of each participant had been measured preoperatively as well as 1 week, 3 months, and 2 years postoperatively. Additionally, the Oswestry Disability Index (ODI) scores were assessed at the last time point. Comparing the two groups, no statistical significance was found among all parameters preoperatively. The time of operations and blood loss is less in Group I. At each time point after operation, the imaging indices in Group II are lower (P< 0.05). One week after treatments, the VAS scores are lower in Group I, and similarly, 3 months are the same (P< 0.05), while VAS are similar at the last time point. In the aspect of ODI scores, they are lower in Group II during long-term follow-up. For the treatment of Kummell's disease, both PVP and PSSF have been found to be effective. PVP can provide rapid pain relief with a shorter operation time. However, in cases with severe kyphosis deformity, PSSF should be given priority.

The impact of electronic despatch advice on the service time of a means of transport in a distribution center

Purpose: The aim of the article is to verify the impact of the use of electronic notification of deliveries on the service time of a means of transport in a distribution center. Methodology: The study used electronic notification in the form of EDI DESADV messages. The research was carried out in one of the distribution centers of a retail company operating in Poland. The study used the method of recording the time of logistics operations. The study was conducted in two stages (each lasting a week), in which the time of logistics operations was recorded in conditions without and with the DESADV message implemented. Results: The results of the conducted research show that the use of electronic despatch advice allows you to reduce the time of handling the means of transport in the distribution center. Conclusion: Reducing the time of handling the means of transport in the distribution center brings numerous additional benefits, such as faster release of the means of transport and enabling it to carry out subsequent transport tasks, handling a larger number of unloadings with the same number of resources (e.g. warehouse ramps), accelerating the internal process and enabling faster reloading to other means of transport performing the distribution process.

System analysis of the procurement warehouse for the achievement of its effectiveness

The work shows the features of applying system analysis to the problems of increasing the efficiency of the procurement section of a large machine-building work. The purpose of the work is to eliminate obstacles to achieving the efficiency of the work of the procurement site with the help of system analysis. Specific solutions are presented for a comprehensive increase in the interaction of subsystems of the procurement site, redevelopment, and the use of more advanced devices to increase efficiency. To solve the problems, the main tools of system analysis are applied - suprasystem-system-subsystem analysis, structural analysis, functional analysis, and site-specific calculations - such as analysis of norms and time of operations, analysis of layouts and compliance with the organizational structure, as well as analysis of equipment operation and finding optimal solutions for its equipment. Discussed the results of the system analyses and limitation of it's implementation in real workshop.

An Assessment of Counter-Terrorism Options: A State Dependent Terror Queuing Model Perspective

The study is an application of a state-dependent queuing theory to evaluate the performance of counterterrorism (CT) options. The CT options examined include the Stick (use of force), the Carrot (non-coercive approaches), their combined variant, and covert agents. The model incorporates state transitions to capture the dynamic nature of terrorist recruitment processes in a CT environment. Performance measures are adapted from conventional queue frameworks to assess the effectiveness of these CT options in mitigating terrorist threats. The study analyses the CT options under an arithmetic progression pattern of terrorist recruitment and state transitions. The results demonstrate the importance of maximizing interdiction rate, discrimination rate, system efficiency, and intelligence integration while minimizing system unfairness factors, response time, and queue length for optimal CT operations. The results of the analysis also highlight a positive correlation between the Stick and the Carrot options, as well as between their intelligence-driven variants, emphasizing the need for a balanced and coordinated intelligence-driven CT approach. The study argues that relying solely on brute force or aggressive law enforcement measures without credible intelligence would be insufficient and counterproductive. It suggests leveraging syndromnized intelligence optimizing pseudo-terrorists (SIOP) agents for enhanced credibility, sufficient intelligence gathering, and covert supervision of terrorists’ compliance to Carrot instruments in the CT environment. The findings contribute to the existing literature on CT research and provide insights for informed decision-making in optimizing CT strategies. The study aims to support the development of more efficient and adaptive approaches to combat terrorism.

МОДЕЛИРОВАНИЕ СГЛАЖИВАЮЩИХ ТРАЕКТОРИЙ ПЕРЕМЕЩЕНИЯ АВТОНОМНЫХ ЭЛЕКТРИФИЦИРОВАННЫХ ПЛАТФОРМ

Automation of cargo transportation both inside production and warehouse premises and between individual objects of livestock and crop production complexes is a promising direction in saving fuel and energy resources of the agro-industrial complex. The use of autonomous vehicles for these purposes, including electrified platforms with non-operational adaptive control, is especially necessary due to the movement of significant volumes of cargo in cramped conditions of buildings and structures. However, the use of broken lines in the planning of ATU movements leads to the need for a significant reduction in the movement speed during the passage of turning sections of the trajectory. This significantly increases the execution time of technological operations, leads to additional energy consumption for braking and acceleration. Thus, the approach proposed in the work to the analytical determination of smoothing movement trajectories of autonomous vehicles is relevant. (Research Purpose) The research purpose is developing an approach to the construction of smoothing sections of the trajectory of a non-operational vehicle with adaptive control that does not require solving optimization problems. (Materials and methods) For a smoothing curve of polynomial form, a system of equations is derived from geometric conditions that defines its most rational form from the point of view of the maximum speed of passing an obstacle. After its representation in the local coordinate system associated with the bypassed obstacle, the equation of the desired curve is found. For the practical implementation of the method, formulas for the transition from a local coordinate system to an absolute one are given. (Results and discussion) A general method is proposed for smoothing the reference broken trajectories obtained at the initial stage of planning the movement of an autonomous electrified platform in cramped conditions. In the local coordinate system associated with the obstacle, the shape of the smoothing transition curves is found and formulas for the transition to the absolute coordinate system are given. (Conclusions) The obtained analytical solution to the construction of smoothing sections of the trajectory of an autonomous vehicle in cramped conditions of buildings and structures for agricultural purposes does not require complex calculations. This simplifies its practical application, including the implementation of programmable adaptive control systems using microprocessor hardware.

Deep Learning-Based SC-FDMA Channel Equalization

It is very challenging to design an effective wireless communication system. That’s because of numerous factors affecting the performance of a typical wireless communication system, such as nonlinear channel distortions and impairments. single carrier frequency division multiple access (SC-FDMA) is a multiple access scheme that is an important part of the long-term evolution (LTE) standard for uplink transmission. An advanced mobile radio system’s multiple access schemes should indeed meet stringent requirements, such as a low bit error rate (BER). In this article, we investigate the equalization problem for nonlinear channel distortions and impairments using deep neural networks (NN). We introduce a novel combined deep neural network channel equalization and symbol detection scheme based on a deep learning (DL) recurrent feedback (RF) long short-term memory (LSTM) neural network to achieve blind equalization and decoding for SC-FDMA systems without knowing the channel state information (CSI). To train the model efficiently, the training data is gathered by simulation, with channel effects and noise treated as a complete black box. CSI and constellation demapping are learned by a deep neural network (DNN) model. Then, the frequency-domain sequences that have been corrupted are implicitly equalized to get the broadcasted signal back. Our specified SC-FDMA system, which uses a quadrature phase-shift keying (QPSK) modulation method and the suggested Deep Learning-based model channel equalizer, performs better than the existing equalizers by an average of 1 to 4 dB at moderate signal-to-noise (SNR) ratios, according to simulation data. A complexity comparison between the proposed and the conventional equalizers was conducted in terms of training time, execution time, and number of operations. On combined channel equalization and symbol detection, the suggested system delivers state-of-the-art performance.

Justification of the structure and tasks of the automated system of forming a rational composition of the machine and tractor fleet of agricultural producers

Purpose. To increase the effectiveness and efficiency of management decisions by using an automated system for substantiating the rational composition of the machine-tractor fleet of agricultural producers. Methods. Monographic, system analysis, abstract and logical. Results. Based on the results of the analytical study, the structure of the automated system for substantiating the rational composition of the machine-tractor fleet of agricultural producers was developed, as well as the management tasks that arise at different levels of management of the machine-tractor fleet, the initial data for solving these tasks and the output data obtained in as a result of their solution. Conclusions. The basis of the problems that need to be solved during the substantiation of the composition of the machine-tractor fleet and the methods of solving them at different levels of management are substantiated. It was established that the following tasks are characteristic of the strategic level: justification of the level of technical support of the agricultural producer; determining the expediency of replenishment and withdrawal of technical means. For the tactical level, the following are characteristic: coordination of the parameters of the machine-tractor fleet with the characteristics of production plans; determination of the need for the involvement of additional technical means. At the operational level of management, the following are relevant: monitoring of the execution of technological operations; accounting for consumption of fuel and lubricants and technological materials; substantiation of the start time of technological operations; determination of effective distribution of technical means by fields and technological operations; justification of the organizational mode of work. Keywords: agriculture, machine and tractor fleet, management, automated systems.

Життєва самореалізація життєстійкості особистості у філософському вимірі

The issue of personal self-realization in life is considered in the philosophical dimension, which is based mainly on the analysis of scientific works of domestic researchers. The author’s position that resilience is a motivational component of the formation of a person’s attitude towards himself and the environment and contributes to a sense of significance and personal fulfillment has been updated. The fact that the issue of personal self-realization in life is the subject of scientific research by both domestic and foreign scientists is noted. Attention is focused on the need for further study and rebroadcasting of the issue of life self-realization of the hardiness of the individual in the philosophical dimension, in particular during the times of military operations and state changes in Ukraine. It is argued that the study of theoretical concepts of life self-realization of the individual deserves special attention, in particular the research of Ukrainian and foreign researchers. Philosophical ideas of the past have been studied and analyzed, as well as their transformation in scientific works. The stated position that resilience is a personal characteristic, an indicator of mental health and an internal resource that contributes to the maintenance of the psychological, social and physical state, that provides meaning and value in any life situations and contributes to the stability of life attitudes of a person, his successful socialization. It is determined that sustainability is a resource of self-realization of the individual and contributes to increasing the level of self-actualization and value-semantic orientations of students of higher education. It is outlined that, overcoming various challenges that arise in the environment, resilience is a necessary resource for the individual’s life self-realization, which determines the readiness to build a strategy and goals even in situations of uncertainty and is a key parameter of the individual’s ability to self-regulate. It is emphasized that the issue of self-development and selfrealization of students of higher education takes place in the educational environment of a higher education institution.

РАЗРАБОТКА ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ДЛЯ СИСТЕМ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ТЕХНОЛОГИЧЕСКИМ ПРОЦЕССОМ МЕХАНООБРАБОТКИ

The automation of production processes is the main direction in which manufacturing is currently being taken around the world. Currently, production automation is one of the ways to increase the efficiency of an enterprise. The main direction of automation of machining production is based on the widespread introduction of computer numerical control (CNC) systems. In a situation of limited opportunities to purchase new equipment with numerical control, the task of import substitution is set. One of the directions in solving this issue is expanding the functionality of existing CNC equipment at the enterprise by developing new control programs for them. This paper presents the results obtained for the milling section of numerically controlled machines of the HAAS model of the Super Mini Mill series of the industrial enterprise Avia LLC. The fundamental feature of a CNC machine is that it works according to a control program (CP), on which the cycle of operation of the equipment for processing a specific part is recorded. A preliminary analysis of the technical documentation of these machines showed that a number of important operations are missing from the control program, as a result of which some of them are performed manually by operators. The authors have developed new software, taking into account the identified shortcomings, using additional operations that expand the functionality of the considered equipment and eliminate manual control by machine operators. The software in automatic mode provides: setting a correction for the tool radius, which allows you to make the part contour programmed in the NC program independent of the diameter of the tool used; control of turning on/off the cutting fluid (coolant); the function of turning on the optional stop of the machine, in which the next operation starts automatically; recording the time of operations at each section of product processing. The program allows you to automatically control the trajectory of movement of the machine's executive bodies, and automates the process at the stage of setting up the tool for the product processing technology. Thus, automation of a number of operations on a CNC machine is aimed at increasing productivity, quality and accuracy of processing, reducing processing time and reducing the risk of producing defective parts. Author's certificates for state registration of the computer program were received.

Comparative Analysis of Genetic and Greedy Algorithm for Optimal Drone Flight Route Planning in Agriculture

In this study, the performance of the Genetic Algorithm (GA) in optimizing the agricultural drone flight route was compared with the Greedy Algorithm, revealing that GA produce routes that are, on average, 17.44 % more efficient. This efficiency, measured over 500 generations in a static field model, suggests substantial potential for saving resources and time in agricultural operations. Despite the effectiveness of the GA, its computational intensity limits real-time field applications, but offers advantages in offline route planning for pre-mapped areas. A t-test between flight lengths created by the algorithms highlighted a significant difference, with a p-value of approximately 7.18×10−9, indicating the GA's superior performance. Future research should aim to bridge the gap between the simplified binary field model used in simulations and the complexities of real-world agricultural landscapes to improve the practical deployment of GAs in drone route optimization.

Effect of corn Zea mays L. cob moisture content on the performance of a corn-cob sheller machine

The object of the research is machine shelling efficiency. This study focused on the assessment of a fabricated corn Sheller machine and resolution of optimal moisture content percentage dry basis (% MCdb) for shelling corn-cobs. Corn-cobs samples at 8, 13 and 18 % MCdb were sorted into 3.15, 2.15 and 1.15 kg feed-masses, respectively. Samples were selected in triplicates for shelling operations time 5, 6 and 7 seconds. Standard method was used to determine the effect of shelling operation on corn-cobs’ quality variables. Response Surface Method was employed to optimize data with machine feed-mass and moisture content as independent variables, whilst responses being: shelled, un-shelled, damaged, un-damaged corn grains, as well as grain breakage ratio, machine shelling efficiency and shelling process time. The data gotten from the results were utilized to evaluate the corn-cob shelling machine and were analyzed using ANOVA at 95 % confidence interval. Corn-cobs 8 % MCdb shelled at 5 seconds and machine feed mass of 3.15 kg had the highest shelling efficiency of 97.78 %, followed by 13 % MCdb, feed mass of 2.15 kg, machine shelling efficiency 92.06 %; shelled in 6 seconds, lastly, 18 % MCdb, feed mass of 1.15 kg, shelling efficiency was 87.82 % shelled in 6 seconds. The resultant recorded response masses; shelled, un-shelled, damaged corn grain (kg) and grain breakage ratio recorded were at lower values. At lower machine shelling time, feed mass and moisture content percentage (% MCdb) of the corn cobs, higher shelled grains off the corn-cobs were recorded with reduced damaged grains, indicating higher shelling efficiency of the fabricated corn-cob Sheller machine.

Decision making in operator-machine assignment problems: an optimization approach in U-shaped production lines

Decision-making is a complex problem in all fields of production, because decision makers have to find the most suitable solution alternative among the numerous, while the solution of the problem is limited by multiple, usually conflicting constraints. In the Industry 4.0 era, one of the most widely used production lines are the U-shaped production lines, which focus on the elimination of waste through a high utilization of workers. It means, that worker-machine assignment plays a significant role in the optimization of production processes in a U-shaped production line. The current investigation proposes a novel absorbing Markov chain (AMC) optimization approach to support the decision making regarding worker selection and assignment. The proposed approach integrates the AMC and the performance analysis of the production process. The numerical results validated the decision making model and showed that optimal worker-machine assignment can lead to about 20% production cost reduction, while the key performance indicators (KPI) of the U-shaped production line are significantly increased. The sensitivity analysis of influencing factors made it possible to identify the critical factors of this decision making problem, such as the qualification of operators, time of technological and logistics operations, and maintenance policy.