Lean terms in apparel manufacturing

Jana, Prabir; Tiwari, Manoj Kumar

doi:10.1016/b978-0-12-819426-3.00010-2

Cited by 8 publications

(6 citation statements)

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“…The selection of measures allows to identify optimisation perspectives in several processes. Other researchers, such as Jana and Tiwari (2021), in their work on the careful production of clothing, have investigated the restructuring of the organisation in modern conditions through the following elements: careful management in clothing production; careful problem solving; visual management; rapid configuration; autonomy; process balancing; careful quality control; careful personnel; careful supply chain management; flexible manufacturing.…”

Section: Discussionmentioning

confidence: 99%

Structural Reorganisation of a Company in a Crisis of Supply Discrepancies

Семенченко¹,

Мажара

2023

BJES

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The relevance of research is determined by the risk of any organisation being affected by the negative effects of overproduction. This requires businessmen to quickly identify and solve related problems by carrying out structural reorganisation of their companies. As such, the main goal of the article is to research the problematic of the overproduction crisis, which is concluded by such objectives as crisis consequences for government and manufacturing organizations evaluation, and development of recommendations regarding the structural reorganization of organizations in the current conditions. The main research methods are graphical and tabular methods, as well as synthesis and analysis in combination in a complex approach, which allows to study crisis processes in order to optimise the company's activity through effective structural reorganisation. The main results of the research are the study of the concept of overproduction crisis and its problematic consequences for the country and the industry. The analysis of the influence of overproduction on the production and trade organisation and the development of proposals for the structural reorganisation of the company in crisis conditions. Organisational reconstruction in the modern environment was studied through the use of careful management, careful problem solving, visual management, quick configuration tool, autonomy, process balancing, careful quality assurance, careful human resource usage, careful supply chain management and production flexibility. Organisational restructuring can also be aimed at the implementation of digital technology, which can be categorised by the scenarios of forecasting, waste analysis and redistribution. Organisational restructuring in the modern environment has been studied through the use of careful management, careful problem solving, visual management, quick configuration tool, autonomy, process balancing, careful quality assurance, careful human resource usage, careful supply chain management, and production flexibility. In order to prevent the influence of crisis occurrence through changes in organisational structure, these procedures were proposed: assembly line load stabilisation, manufacturing analysis and 5S system. The results of this article and the conclusions based on them may be of practical value for students studying the peculiarities of effective financial management in the conditions of crisis, as well as for businessmen interested in maintaining their financial results, maximising profits, preventing crisis problems and optimising business activity through changes in the company structure.

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Section: Discussionmentioning

confidence: 99%

Structural Reorganisation of a Company in a Crisis of Supply Discrepancies

Семенченко¹,

Мажара

2023

BJES

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“…The training and the validation sets are, respectively, random 80% and 20% of windows in the dataset. This is a common proportion in the related works and is inspired by the Pareto principle [67]. The results of the ablation study are shown in Table 5 and graphically in Figure 3.…”

Section: Ablation Studymentioning

confidence: 96%

A Novel Transformer-Based IMU Self-Calibration Approach through On-Board RGB Camera for UAV Flight Stabilization

Avola

Cinque

Foresti

et al. 2023

Sensors

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During flight, unmanned aerial vehicles (UAVs) need several sensors to follow a predefined path and reach a specific destination. To this aim, they generally exploit an inertial measurement unit (IMU) for pose estimation. Usually, in the UAV context, an IMU entails a three-axis accelerometer and a three-axis gyroscope. However, as happens for many physical devices, they can present some misalignment between the real value and the registered one. These systematic or occasional errors can derive from different sources and could be related to the sensor itself or to external noise due to the place where it is located. Hardware calibration requires special equipment, which is not always available. In any case, even if possible, it can be used to solve the physical problem and sometimes requires removing the sensor from its location, which is not always feasible. At the same time, solving the problem of external noise usually requires software procedures. Moreover, as reported in the literature, even two IMUs from the same brand and the same production chain could produce different measurements under identical conditions. This paper proposes a soft calibration procedure to reduce the misalignment created by systematic errors and noise based on the grayscale or RGB camera built-in on the drone. Based on the transformer neural network architecture trained in a supervised learning fashion on pairs of short videos shot by the UAV’s camera and the correspondent UAV measurements, the strategy does not require any special equipment. It is easily reproducible and could be used to increase the trajectory accuracy of the UAV during the flight.

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“…Here, we draw from the “Pareto principle,” described by Jana and Tiwari 127 as a commonplace case where “80% of the outcomes are controlled or decided by 20% of the activities or factors. For example, 80% of the total profit is generated by 20% of the product categories, or 80% of the maintenance expenses are incurred by 20% of the machines.” Applying the Pareto principle, the last 20% of automation may require 80% of the total effort towards bringing full autonomy to an experiment.…”

Section: How Do We Make Frugal Twins Better?mentioning

confidence: 99%