This paper describes the study case results of coffee shop robotic arm assistant, which draws a “STAR” on a cappuccino, solved by students in a robotics class practice. They had applied the trajectory generation, in...
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ISBN:
(数字)9798350355284
ISBN:
(纸本)9798350355291
This paper describes the study case results of coffee shop robotic arm assistant, which draws a “STAR” on a cappuccino, solved by students in a robotics class practice. They had applied the trajectory generation, inverse kinematic model, and G-CODE, to do the planned task at simulation, and with real industrial robot arm in the lab. The results conclude the increase student interest and performance, in the Robotics course, with a challenge problem solving.
Inventory management in the health sector, specifically in the pharmaceutical service, represents a high percentage of logistics costs, putting pressure on health institutions to optimize inventory management to guara...
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ISBN:
(纸本)9783031768088
Inventory management in the health sector, specifically in the pharmaceutical service, represents a high percentage of logistics costs, putting pressure on health institutions to optimize inventory management to guarantee the availability of supplies. On the other hand, different regulations worldwide establish the adoption of mechanisms and policies for adequate inventory management, a situation that in low- and middle-income countries is restricted by resource limitations and the low implementation of robust techniques and methodologies. Different applications of models for inventory management have been identified in the literature, such as optimization models, Lean tools, and multicriteria decision-making methods. However, integrated approaches to optimize demand management, ordering, and controlling pharmaceutical services supplies are still under development. Therefore, the present study proposes a three-phase hybrid approach based on MCDM techniques and data analytics to improve inventory management of the pharmaceutical service in a health research center. The first stage consisted of characterizing the process to identify aspects for improvement. In the second stage, a multicriteria ABC classification model based on F-AHP and TOPSIS was applied to classify laboratory supplies for three selected clinical studies. Furthermore, the appropriate forecasting method was chosen for each clinical study, and a combined model (P model and FEFO model) was applied to establish the reorder point. Then, strategies, mechanisms, and policies were proposed to improve inventory management and redesign the process flow. As the main results, a multicriteria ABC method was obtained to classify laboratory supplies, taking into account Rotation (GW = 0.512), Criticality (GW = 0.286), and Availability (GW = 0.203). On the other hand, through data analysis and regression models, the exponential smoothing model with α = 0.10 was identified as the most convenient forecasting model, as
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