Lean Manufacturing (LM), a manufacturing system and philosophy, was originally developed by Toyota, Japan and is now widely practiced by many manufacturers throughout the world. Lean manufacturing is a systematic approach to identifying and reducing waste (non value-added activities) through continuous improvement by flowing the product at the pull of the customer in pursuit of perfection. LM is important, primarily because of waste reduction and reduction in lead time. The objective of this paper is to identify Lean manufacturing practices in small scale industries. For this purpose some case studies were chosen and critical observations are identified. Some of these annotations are improper utilization of resources, quality tools for improvements and improper plan for location and layout. This paper includes one case study with the initiatives, observations, results and conclusions of the study carried out in a small scale industry.
The work presents optimized Uncertainty and disturbance estimator (UDE) based robust controller to achieve the fixed wing Micro Aerial Vehicle (MAV) longitudinal and lateral stability. In the proposed control methodology, Genetic Algorithm (GA) is used to find the optimal value of UDE filter parameter (GAUDE) which is filter time constant. GA uses minimization of Integral absolute time error (IATE) based fitness function. In this work, the proposed controller is GAUDE based adaptive sliding mode control (SMC). The Lyapunov theory is used to establish the stability of the presented controller. The performance of proposed SMC-GAUDE controller is analyzed through comparative analysis using numerical simulations. The comparative analysis consists of the proposed controller performance evaluation with existing UDE based and conventional controllers. The comparative study shows the faster response to attain desired states alongwith smooth and chattering free control efforts offered by SMC-GAUDE controller. The results presents viability of the proposed controller. To show the robustness of the proposed controller, IATE performance index is evaluated. Also, the Monte-Carlo simulations are done to highlight the efficacy of the proposed controller in the presence of parametric variations in MAV aerodynamic coefficients and velocity.
This work proposes an Input-Output linearization (IOL) trajectory tracking controller for an actuated octocopter UAV. The underactuated 
octocopter dynamics is converted into actuated one using the differential flat outputs. The proposed controller for actuated octocopter UAV is 
robustified using α Uncertainty and Disturbance Estimator (αUDE). The Lyapunov theory is used to ascertain closed-loop stability in achieving the desired trajectory. A comparative study is carried out to show the better performance of the proposed controller. Results show the efficacy of the proposed controller in handling the effects of slow as well as fast varying disturbances, parametric uncertainties, and measurement noise. The quantitative analysis based on performance indices and root mean square error validated the results.
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