Kontinuierliche Planung von Logistikflächen/Continuous planning of logistic areas within factories

2020 ◽  
Vol 110 (04) ◽  
pp. 195-200
Author(s):  
Michael Teucke ◽  
Marius Veigt ◽  
Hendrik Engbers ◽  
Malte Klose ◽  
Michael Freitag
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Continuous Monitoring ◽  
Software Tools ◽  
System P ◽  
And Storage

Da Logistikflächen für innerstädtische Fabriken nur begrenzt verfügbar sind, ist deren bestmögliche Nutzung bedeutsam. Der Einsatz von Softwarewerkzeugen ist in der Neuplanung von Logistikflächen gängige Praxis. Die effiziente Nutzung bestehender Flächen in Anbetracht geänderter Anforderungen wird aber selten kontinuierlich überprüft. Der Beitrag zeigt, wie eine kontinuierliche planerische Restrukturierung von Logistikflächen durch ein digitales Assistenzsystem unterstützt werden kann.   Due to limited available space in urban production plants, the best possible use of logistic and storage areas is very important. The use of software tools is common practice for the planning of new logistics areas. However, continuous monitoring of the efficient use of existing areas due to changing requirements is only rarely implemented. This article describes how a continuous restructuring planning of logistics areas can be supported by a decision support system.

scholarly journals A decision support system for cost determination in grain storage facility operations

2011 ◽  
Vol 31 (4) ◽  
pp. 735-744 ◽  
Author(s):  
Domingos S. M. Valente ◽  
Daniel M. de Queiroz ◽  
Paulo C. Corrêa ◽  
Luis C. da Silva ◽  
Sônia M. L. R. do Vale
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Turnover Rate ◽  
Grain Storage ◽  
Storage Facility ◽  
Factors Associated ◽  
Processing And Storage ◽  
Cost Determination ◽  
And Storage

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.

Potenziale der Distributionslogistik nutzen*/Utilizing distribution logistics’ potential - Evaluation of distribution logistics potential via a logistic assistance system

2016 ◽  
Vol 106 (04) ◽  
pp. 266-272
Author(s):  
J. Becker ◽  
R. Arnold ◽  
P. Prof. Nyhuis
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Assistance System ◽  
Efficient Design ◽  
System P ◽  
Distribution Logistics ◽  
Potential Evaluation ◽  
And Performance ◽  
Essential Contribution

Die Distributionslogistik als Bindeglied zwischen Produktion und Absatzmarkt wird unmittelbar vom Kunden wahrgenommen und beeinflusst maßgeblich den Unternehmenserfolg. Dieser Beitrag stellt mit dem „Distributions-Tool“ ein logistisches Assistenzsystem vor, welches die aktuellen Logistikkosten und die Logistikleistung der Distributionslogistik ermittelt sowie Potenziale zur Senkung der Kosten und Steigerung der Leistung ausgibt. In Verbindung mit weiteren qualitativen Kriterien lassen sich logistische Szenarien generieren und umfassend bewerten.   The design of its distribution logistics has a decisive influence on a company‘s logistical costs and performance. They, therefore, make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistical costs and performance. Combined with other qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.

scholarly journals Decision Support System in a Memristor-Based Mobile CIM Architecture Applied on Big Data Computation and Storage

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Wei Li ◽  
Zhao Deng
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Decision Support System ◽  
Data Processing ◽  
Computer Architecture ◽  
Support System ◽  
Integrated Circuit ◽  
Data Communication ◽  
Oxide Semiconductor ◽  
And Storage

Data computation and storage are essential parts of developing big data applications. The memristor device technology could remove the speed and energy efficiency bottleneck in the existing data processing. The present experimental work investigates the decision support system in a new architecture, computation-in-memory (CIM) architecture, which can be utilized to store and process big data in the same physical location at a faster rate. The decision support system is used for data computation and storage, with the aims of helping memory units read, write, and erase data and supporting their decisions under big data communication ambiguities. Data communication is realized within the crossbar by the support of peripheral controller blocks. The feasibility of the CIM architecture, adaptive read, write, and erase methods, and memory accuracy were investigated. The integrated circuit emphasis (SPICE) simulation results show that the proposed CIM architecture has the potential of improving the computing efficiency, energy consumption, and performance area by at least two orders of magnitude. CIM architecture may be used to mitigate big data processing limits caused by the conventional computer architecture and complementary metal-oxide-semiconductor (CMOS) transistor process technologies.

scholarly journals Sistem Pendukung Keputusan Penerimaan Jurnalis Menerapkan MultiObjective Optimization On The Basis Of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Fa'a INA-Rxiv Papers Computer
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Ratio Analysis ◽  
Employee Recruitment ◽  
Knowledge Based ◽  
System P ◽  
Computer Based ◽  
Moora Method ◽  
Support Decision Making

Decision support systems are part of computer-based information systems (including knowledge-based systems) that are usedto support decision making within an organization or company. The decision support system provides a semi-structureddecision, where no one knows for sure how decisions should be made. Recruitment of employee recruitment in PT.Waspada Medan always through some tight selection before set accepted as employees at PT.Waspada Medan. There are several criteria that must be owned by each participant as a requirement to become an employee of PT.Waspada Medan. To get the best participants then the PT.Waspada Medan requires a decision support system. In this study, the authors apply Multi-Objective Optimization on the basis of Ratio Analysis (MOORA Method) as the method to be applied in the application of decision support system

scholarly journals Mobile Decision Support Tool for Emergency Departments and Mass Casualty Incidents (EDIT): Initial Study (Preprint)

2018 ◽  
Author(s):  
Nicholas Boltin ◽  
Diego Valdes ◽  
Joan M. Culley ◽  
Homayoun Valafar
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Mass Casualty Incident ◽  
Mass Casualty ◽  
Patient Data ◽  
Chemical Exposures ◽  
System P ◽  
Collect Patient Data

BACKGROUND Chemical exposures pose a significant threat to life. A rapid assessment by first responders and emergency nurses is required to reduce death and disability. Currently, no informatics tools exist to process victims of chemical exposures efficiently. The surge of patients into a hospital emergency department during a mass casualty incident creates additional stress on an already overburdened system, potentially placing patients at risk and challenging staff to process patients for appropriate care and treatment efficacy. Traditional emergency department triage models are oversimplified during highly stressed mass casualty incident scenarios in which there is little margin for error. Emerging mobile technology could alleviate the burden placed on nurses by allowing the freedom to move about the emergency department and stay connected to a decision support system. OBJECTIVE This study aims to present and evaluate a new mobile tool for assisting emergency department personnel in patient management and triage during a chemical mass casualty incident. METHODS Over 500 volunteer nurses, students, and first responders were recruited for a study involving a simulated chemical mass casualty incident. During the exercise, a mobile application was used to collect patient data through a kiosk system. Nurses also received tablets where they could review patient information and choose recommendations from a decision support system. Data collected was analyzed on the efficiency of the app to obtain patient data and on nurse agreement with the decision support system. RESULTS Of the 296 participants, 96.3% (288/296) of the patients completed the kiosk system with an average time of 3 minutes, 22 seconds. Average time to complete the entire triage process was 5 minutes, 34 seconds. Analysis of the data also showed strong agreement among nurses regarding the app’s decision support system. Overall, nurses agreed with the system 91.6% (262/286) of the time when it came to choose an exposure level and 84.3% (241/286) of the time when selecting an action. CONCLUSIONS The app reliably demonstrated the ability to collect patient data through a self-service kiosk system thus reducing the burden on hospital resources. Also, the mobile technology allowed nurses the freedom to triage patients on the go while staying connected to a decision support system in which they felt would give reliable recommendations.

scholarly journals Study Approach of Simple Additive Weighting For Decision Support System

2017 ◽  
Author(s):  
N Nurmalini ◽  
Robbi Rahim
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Science And Technology ◽  
Scientific Research ◽  
Study Approach ◽  
System P ◽  
Simple Additive Weighting

This paper has been Published in International Journal of Scientific Research in Science and Technology (IJSRST): Volume 3 | Issue 3 | March-April - 2017 Date of Publication : 2017-04-30

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

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