scholarly journals Redução do tempo de setup em uma linha de envase de produtos em uma fábrica de cosméticos / Reduced setup time on a product filling line in a cosmetics factory

2021 ◽  
Vol 7 (12) ◽  
pp. 119383-119395
Author(s):  
Bruno Diniz Francisco Neves ◽  
Leonardo Gonçalves Martins Cardoso ◽  
Matheus Tognozzi Fabri ◽  
Thiago Eidelmanas Higashi ◽  
Nelson Wilson Paschoalinoto
Keyword(s):  
Setup Time ◽  
Filling Line

Designing an Energy Efficient Scheme in MANET using Reconfigurable Directional (RDA) Algorithm

2018 ◽  
Vol 8 (4) ◽  
pp. 92
Author(s):  
Rinkle Chhabra ◽  
Anuradha Saini
Keyword(s):  
Ad Hoc ◽  
Energy Savings ◽  
Setup Time ◽  
Directional Antennas ◽  
Directional Antenna ◽  
Efficient Scheme ◽  
Primary Focus ◽  
Hoc Networks ◽  
Energy Gains ◽  
Insight Into

Mobile Ad Hoc Networks (MANET) are autonomous, infrastructure less and self-configuring networks. MANETs has gained lots of popularity due to on the fly deployment i.e. small network setup time and ability to provide communication in obstreperous terrains. Major challenges in MANETs include routing, energy efficiency, network topology control, security etc. Primary focus in this article is to provide method and algorithm to ensure significant energy savings using re-configurable directional antennas. Significant energy gains can be clinched using directional antenna. Key challenges while using directional antenna are to find destination location, antenna focusing, signal power and distance calculations. Re-configurable directional antenna can ensure significant energy gains if used intelligently. This article provides a brief insight into improved energy savings using re-configurable directional antennas and an associated algorithm

MINIMALISASI BIAYA SIMPAN DAN BIAYA SETUP PADA MULTIPLE PRODUK: SIMULASI DENGAN CAPACITATED LOT SIZING PROBLEM

2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma
Keyword(s):  
Production Cost ◽  
Lot Sizing ◽  
Setup Time ◽  
Production Costs ◽  
Total Production ◽  
Product Cycle ◽  
Lot Size ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.

scholarly journals Extraperitoneal Robotic Laparo-Endoscopic Single-Site Plus1-Port Radical Prostatectomy Using the da Vinci Single-Site Platform

2021 ◽  
Vol 10 (8) ◽  
pp. 1563
Author(s):  
Ching-Chia Li ◽  
Tsu-Ming Chien ◽  
Ming-Ru Lee ◽  
Hsiang-Ying Lee ◽  
Hung-Lung Ke ◽  
...  
Keyword(s):  
Radical Prostatectomy ◽  
Da Vinci ◽  
Specific Antigen ◽  
Operation Time ◽  
Setup Time ◽  
Single Site ◽  
University Hospital ◽  
Da Vinci Surgical System ◽  
Free Survival ◽  
The Aesthetic

Currently, over 80% of radical prostatectomies have been performed with the da Vinci Surgical System. In order to improve the aesthetic outlook and decrease the morbidity of the operation, the new da Vinci Single Port (SP) system was developed in 2018. However, one major problem is the SP system is still not available in most countries. We aim to present our initial experience and show the safety and feasibility of the single-site robotic-assisted radical prostatectomy (LESS-RP) using the da Vinci Single-Site platform. From June 2017 to January 2020, 120 patients with localized prostate cancer (stage T1–T3b) at Kaohsiung Medical University Hospital were included in this study. We describe our technique and report our initial results of LESS-RP using the da Vinci Si robotic system. Preoperative, intraoperative and postoperative patient variables were recorded. Prostate-specific antigen (PSA)-free survival was also analyzed. A total of 120 patients were enrolled in the study. The median age of patients was 68 years (IQR 63–71), with a median body mass index of 25 kg/m2 (IQR 23–27). The median PSA value before operation was 10.7 ng/mL (IQR 7.9–21.1). The median setup time for creat-ing the extraperitoneal space and ports document was 25 min (IQR 18–34). The median robotic console time and operation time were 135 min (IQR 110–161) and 225 min (IQR 197–274), respectively. Median blood loss was 365 mL (IQR 200–600). There were 11 (9.2%) patients who experienced complications (Clavien–Dindo classification Gr II). The me-dian catheter duration was 8 days (IQR 7–9), with a median of 10 days (IQR 7–11) of hospital stay. The PSA free-survival rate was 86% at a median 19 months (IQR 6–28) of follow up. Robotic radical prostatectomy using the da Vinci Single-Site platform system is safe and feasible, with acceptable outcomes.

scholarly journals Mathematical Modeling and Discrete Firefly Algorithm to Optimize Scheduling Problem with Release Date, Sequence-Dependent Setup Time, and Periodic Maintenance

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Mustafa A. Qamhan ◽  
Ammar A. Qamhan ◽  
Ibrahim M. Al-Harkan ◽  
Yousef A. Alotaibi
Keyword(s):  
Firefly Algorithm ◽  
Programming Model ◽  
Setup Time ◽  
Mixed Integer ◽  
Release Date ◽  
Sequence Dependent ◽  
Sequence Dependent Setup Time ◽  
Periodic Maintenance ◽  
Discrete Firefly Algorithm ◽  
Sequence Dependent Setup

An evolutionary discrete firefly algorithm (EDFA) is presented herein to solve a real-world manufacturing system problem of scheduling a set of jobs on a single machine subject to nonzero release date, sequence-dependent setup time, and periodic maintenance with the objective of minimizing the maximum completion time “makespan.” To evaluate the performance of the proposed EDFA, a new mixed-integer linear programming model is also proposed for small-sized instances. Furthermore, the parameters of the EDFA are regulated using full factorial analysis. Finally, numerical experiments are performed to demonstrate the efficiency and capability of the EDFA in solving the abovementioned problem.

scholarly journals Batch Scheduling In A Two-Stage Flexible Flow Shop Problem

2014 ◽  
Vol 39 (1) ◽  
pp. 3-16 ◽  
Author(s):  
Enrique Gerstl ◽  
Gur Mosheiov ◽  
Assaf Sarig
Keyword(s):  
Flow Shop ◽  
Optimal Solution ◽  
Setup Time ◽  
Optimal Number ◽  
Two Stage ◽  
Second Stage ◽  
Flow Shop Problem ◽  
Batch Sizes ◽  
Batch Schedule ◽  
Identical Jobs

Abstract We study a special two-stage flexible flowshop, which consists of several parallel identical machines in the first stage and a single machine in the second stage. We assume identical jobs, and the option of batching, with a required setup time prior to the processing of a new batch. We also consider the option to use only a subset of the available machines. The objective is minimum makespan. A unique optimal solution is introduced, containing the optimal number of machines to be used, the sequence of batch sizes, and the batch schedule. The running time of our proposed solution algorithm is independent of the number of jobs, and linear in the number of machines

The presence of microbial contamination and biofilms at a beer can filling production line

2021 ◽  
Author(s):  
Eva M Wagner ◽  
Sarah Thalguter ◽  
Martin Wagner ◽  
Kathrin Rychli
Keyword(s):  
Microbial Contamination ◽  
Extracellular Polymeric Substances ◽  
Protein Pattern ◽  
Critical Role ◽  
Extracellular Dna ◽  
Associated Matrix ◽  
Matrix Components ◽  
Late Stages ◽  
Microbial Status ◽  
Filling Line

Contamination of beer arises in 50% of all events at the late stages of production, the filling area. Hereby, biofilms, being consortia of microorganisms embedded in a matrix composed of extracellular polymeric substances, play a critical role. To date, most studies have focused on the presence of (biofilm forming) microorganisms within this filling environment. Our aim was to characterize the microbial status as well as the presence of possible biofilms at a can filling line for beer by determining the presence of microorganisms and their associated matrix components (carbohydrates, proteins and extracellular DNA (eDNA)). Targeted qPCR confirmed the presence of microorganisms at ten sites during operation and three after cleaning (from 23 sites respectively). The evaluation of carbohydrates, eDNA and proteins showed that 16 sites were positive for at least one component during operation and four after cleaning. We identified one potential biofilm hotspot, namely the struts below the filler, harboring high loads of bacteria and yeast, eDNA, carbohydrates and proteins. The protein pattern was different than that of beer. This work deepens our understanding of biofilms and microorganisms found at the filling line of beer beverages at sites critical for production.

scholarly journals Comparative study of cloud platforms to develop a Chatbot

2017 ◽  
Vol 6 (3) ◽  
pp. 57 ◽  
Author(s):  
Amit Patil ◽  
Marimuthu K ◽  
Nagaraja Rao A ◽  
Niranchana R
Keyword(s):  
Artificial Intelligence ◽  
Comparative Study ◽  
Time Complexity ◽  
Completion Time ◽  
Setup Time ◽  
Human Being ◽  
Cloud Platform ◽  
New Era ◽  
Ibm Watson ◽  
Aws Lambda

Before chatbots there were simply bots: The invention of a chatbot brought us to the new era of technology, the era of conversation service. A chatbot is a virtual person that can effectively talk to any human being with the help of interactive conversion textual skill. Now a days there are many cloud-based platforms available for developing and deploying the chatbot such as Microsoft bot framework, IBM Watson, Kore, AWS lambda, Microsoft Azure bot service, Chatfuel, Heroku and many more but all those techniques has some drawbacks such as built-in Artificial Intelligence, NLP, conversion service, programming etc. This paper represents the comparison between all cloud-based chatbot technologies with some constraint such as built-in AI, setup time, completion time, complexity etc. Finally, by the comparison, we will get to know that which cloud platform is efficient and suitable for developing chatbot.

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