Designing And Optimizing Production In A High Variety / Low Volume Environment Through Data-Driven Simulation

2021 ◽  
Author(s):  
Virginia Fani ◽  
Bianca Bindi ◽  
Romeo Bandinelli
Keyword(s):  
Simulation Model ◽  
Production Systems ◽  
Discrete Event ◽  
Simulation Models ◽  
Product Variety ◽  
Data Driven ◽  
Business Decisions ◽  
Footwear Industry ◽  
Data Driven Approach ◽  
High Level

HVLV environments are characterized by high product variety and small lot production, pushing companies to recursively design and optimize their production systems in a very short time to reach high-level performance. To increase their competitiveness, companies belonging to these industries, often SMEs working as third parties, ask for decision-making tools to support them in a quick and reactive reconfiguration of their production lines. Traditional discrete event simulation models, widely studied in the literature to solve production-related issues, do not allow real-time support to business decisions in dynamic contexts, due to the time-consuming activities needed to re-align parameters to changing environments. Data-driven approach overcomes these limitations, giving the possibility to easily update input and quickly rebuild the model itself without any changes in the modeling code. The proposed data-driven simulation model has also been interfaced with a commonly-used BI tool to support companies in the iterative comparison of different scenarios to define the optimal resource allocation for the requested production plan. The simulation model has been implemented into a SME operating in the footwear industry, showing how this approach can be used by companies to increase their performance even without a specific knowledge in building and validating simulation models.

scholarly journals A data‐driven approach for predicting nepheline crystallization in high‐level waste glasses

2020 ◽  
Vol 103 (9) ◽  
pp. 4913-4924
Author(s):  
Irmak Sargin ◽  
Charmayne E. Lonergan ◽  
John D. Vienna ◽  
John S. McCloy ◽  
Scott P. Beckman
Keyword(s):  
Data Driven ◽  
High Level Waste ◽  
Data Driven Approach ◽  
High Level

HP Product Variety Management

2017 ◽  
pp. 1-7
Author(s):  
Gad Allon ◽  
Jan Van Mieghem ◽  
Ilya Kolesov
Keyword(s):  
Product Variety ◽  
Data Driven ◽  
Product Portfolio ◽  
Product Introduction ◽  
Systematic Data ◽  
Data Driven Approach

HP sells configure-to-order products. With millions of part combinations going into an order, the challenge is deciding which parts to keep in the portfolio to balance costs with revenues. The case explains how one would approach this problem before product introduction, but focuses on managing the existing portfolio.Students will develop a systematic, data-driven approach to decide on the best product portfolio to sell for a configure-to-order business. Which SKUs are candidates for a “global core” product offering? For an extended offering? For elimination?

scholarly journals A data‐driven approach to stimulus selection reveals an image‐based representation of objects in high‐level visual areas

2019 ◽  
Vol 40 (16) ◽  
pp. 4716-4731 ◽  
Author(s):  
David D. Coggan ◽  
Afrodite Giannakopoulou ◽  
Sanah Ali ◽  
Burcu Goz ◽  
David M. Watson ◽  
...  
Keyword(s):  
Data Driven ◽  
Stimulus Selection ◽  
Visual Areas ◽  
Data Driven Approach ◽  
High Level

Data-driven anomaly detection in cyber-physical production systems

2015 ◽  
Vol 63 (10) ◽  
Author(s):  
Oliver Niggemann ◽  
Christian Frey
Keyword(s):  
Anomaly Detection ◽  
Production Systems ◽  
Data Driven ◽  
Plant Analysis ◽  
Product Complexity ◽  
Automation Systems ◽  
Data Driven Approach ◽  
Assistance Systems ◽  
Cyber Physical Production Systems ◽  
Intelligent Assistance

AbstractDue to global competition and increasing product complexity, the complexity of production systems has grown significantly in recent years. This places an increasing burden on automation developers, systems engineers and plant constructors. Intelligent assistance systems and smart automation systems are a possible solution to face this complexity: The machines, i.e. the software and assistance systems, take over tasks that were previously carried out manually by experts. At the heart of this concept are intelligent anomaly detection approaches based on models of the system behaviors. Intelligent assistance systems learn these models automatically: Based on data, these systems extract most necessary knowledge about the diagnosis task. This paper outlines this data-driven approach to plant analysis using several use cases from industry.

The Vanderbilt PICC Service: Program, Procedural, and Patient Outcomes Successes

2005 ◽  
Vol 10 (4) ◽  
pp. 183-192 ◽  
Author(s):  
Doug Burns
Keyword(s):  
Patient Outcomes ◽  
Medical Center ◽  
Nursing Program ◽  
Data Driven ◽  
Complication Rates ◽  
Advanced Practice ◽  
The Past ◽  
Data Driven Approach ◽  
High Level ◽  
Vanderbilt University

Abstract Since its inception in early 2000, Vanderbilt University's Peripherally Inserted Central Catheter (PICC) Service has experienced a high level of success as measured by high proficiency rates and increasing patient procedures each year, low complication rates during and after PICC placements, and an increasing scope of influence within the Vanderbilt University Medical Center and Children's Hospital, the surrounding community, and in the Southeastern United States. Primary drivers of the PICC Service's continuing success include consistent applications of technique and technology, a data-driven approach to assessing the program's progress, and appropriately managing customers' expectations and needs. Over the past five years, data were collected on more than 12,500 PICC placements performed in this specialized nursing program. Retrospective analyses of the data demonstrate an increasing rate of successful placements (from 87.2% to 92.4%) since the program's inception in 2000 to late 2004. Furthermore, the choice of PICC technology has had a significant impact on the odds for occlusion or infection. The Vanderbilt PICC Service provides a model by which other programs can be established, maintained, and expanded into advanced practice.

scholarly journals A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters

2021 ◽  
Author(s):  
Jordan Dotson ◽  
Eric Anslyn ◽  
Matthew Sigman
Keyword(s):  
Density Functional ◽  
Level Density ◽  
Enantiomeric Excess ◽  
Data Driven ◽  
Functional Theory ◽  
Dynamic Covalent Chemistry ◽  
Sensor Optimization ◽  
Data Driven Approach ◽  
High Level ◽  
Sensor Molecules

Dynamic covalent chemistry-based sensors have recently emerged as powerful tools to rapidly determine the enantiomeric excess of organic small molecules. While a bevy of sensors have been developed, those for flexible molecules with stereocenters remote to the functional group that binds the chiroptical sensor remain scarce. In this study, we develop an iterative, data-driven workflow to design and analyze a chiroptical sensor capable of assessing challenging acyclic γ-stereogenic alcohols. Fol-lowing sensor optimization, the mechanism of sensing was probed with a combination of computational parameterization of the sensor molecules, statistical modeling, and high-level density functional theory (DFT) calculations. These were used to elucidate the mechanism of stereochemical recognition and revealed that competing attractive non-covalent interactions (NCIs) determine the overall performance of the sensor. It is anticipated that the data-driven workflows developed herein will be generally applicable to the development and understanding of dynamic covalent and supramolecular sensors.

scholarly journals DISCRETE-EVENT SIMULATION MODELS FOR DIDACTIC SUPPORT

2016 ◽  
Vol 13 (3) ◽  
pp. 300
Author(s):  
Cíntia De Lima Rangel ◽  
João José De Assis Rangel ◽  
Eduardo Shimoda ◽  
Janaína Ribeiro Do Nascimento
Keyword(s):  
High School ◽  
Simulation Model ◽  
Discrete Event Simulation ◽  
Educational Achievement ◽  
Discrete Event ◽  
Simulation Models ◽  
Event Simulation ◽  
Discrete Event Simulation Model

This paper presents the evaluation of a discrete event simulation model designed to be used as a didactic aid instrument in classes of a technical course on high school. The simulation model was developed using the free version of the Arena software. Among the results obtained, it was found that applying this model as a didactic resource in classes has enabled an increase of quality in the students’ learning. This result was even more significant concerning students with average grades below 6. In these cases, with the help of the simulator, students of worse educational achievement obtained performance close to the ones that had average grades equal to or higher than 8.

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