ProSense*/ProSense – Improving the forecast quality of detailed planning

2016 ◽  
Vol 106 (04) ◽  
pp. 218-223
Author(s):  
C. Reuter ◽  
F. Brambring ◽  
T. Hempel ◽  
A. Gützlaff
Keyword(s):  
Production Control ◽  
Industrie 4.0 ◽  
Production Data ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Eine Analyse ◽  
Planning And Control ◽  
Process Chains ◽  
And Control

Immer kundenindividuellere Prozessketten sowie eine gleichzeitig steigende Marktdynamik stellen Unternehmen und insbesondere die Produktionssteuerung vor große Herausforderungen. Das Forschungsprojekt ProSense erarbeitet Lösungen für eine Produktionssteuerung in Zeiten von Industrie 4.0. Durch eine Analyse der Abweichungen zwischen Plan- und Ist-Daten wird die Verbesserung der Planungsgüte in der Produktion erreicht.   Customer-specific process chains and increasingly dynamic market conditions pose a major challenge for manufacturing companies and especially their production planning and control processes. The research project ProSense develops solutions for a production control in the context of Industrie 4.0. An analysis of the variance between planned and actual production data improves the planning quality.

ProSense/ProSense - Production control in the context of Industrie 4.0

2015 ◽  
Vol 105 (06) ◽  
pp. 422-426
Author(s):  
C. Reuter ◽  
F. Brambring ◽  
T. Hempel ◽  
F. Schulte ◽  
L. Dambeck
Keyword(s):  
Production Planning ◽  
Production Control ◽  
Industrie 4.0 ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Specific Process ◽  
Planning And Control ◽  
Intelligent Sensors ◽  
Process Chains ◽  
And Control

Immer kundenindividuellere Prozessketten sowie eine gleichzeitig steigende Marktdynamik stellen Unternehmen und insbesondere die Produktionssteuerung vor große Herausforderungen. Das Forschungsprojekt ProSense erarbeitet Lösungen für eine Produktionssteuerung in Zeiten von Industrie 4.0. Auf Basis kybernetischer Unterstützungssysteme und intelligenter Sensorik soll der Entscheider optimal bei Planung und Steuerung der Produktion unterstützt werden.   Customer-specific process chains and increasingly dynamic market conditions pose a major challenge for manufacturing companies and especially their production planning and control processes. The research project ProSense develops solutions for a production control in the context of Industrie 4.0. Building on cybernetic support systems and intelligent sensors, the employees can be optimally supported in decisions concerning production planning and control.

Digitale Produktion und intelligente Steuerung/Digital Production and Intelligent Production Control – Integrating digital and real-world production for adaptive and automated control

2020 ◽  
Vol 110 (04) ◽  
pp. 255-260
Author(s):  
Marvin Carl May ◽  
Andreas Kuhnle ◽  
Gisela Lanza
Keyword(s):  
Production Control ◽  
Production Systems ◽  
Industrie 4.0 ◽  
World Production ◽  
Production Planning And Control ◽  
Automated Control ◽  
Planning And Control ◽  
Digital Production ◽  
Digitale Modelle ◽  
And Control

Im Rahmen der stufenweisen Umsetzung von Industrie 4.0 erreicht die Vernetzung und Digitalisierung die gesamte Produktion. Den physischen Produktionsprozess nicht nur cyber-physisch zu begleiten, sondern durch eine virtuelle, digitale Kopie zu erfassen und zu optimieren, stellt ein enormes Potenzial für die Produktionssystemplanung und -steuerung dar. Zudem erlauben digitale Modelle die Anwendung intelligenter Produktionssteuerungsverfahren und leisten damit einen Beitrag zur Verbreitung optimierender adaptiver Systeme.   In the wake of implementing Industrie 4.0 both integration and digitalization affect the entire production. Physical production systems offer enormous potential for production planning and control through virtual, digital copies and their optimization, well beyond purely cyber-physical production system extensions. Furthermore, digital models enable the application of intelligent production control and hence contribute to the dissemination of adaptively optimizing systems.

Die synchrone Produktion*/Synchronous manufacturing - An approach for semi-autonomous production planning and control and human-based decision support

2015 ◽  
Vol 105 (04) ◽  
pp. 204-208
Author(s):  
D. Kreimeier ◽  
E. Müller ◽  
F. Morlock ◽  
D. Jentsch ◽  
H. Unger ◽  
...  
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Production Planning ◽  
Data Exchange ◽  
Production Control ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Manufacturing Execution Systems ◽  
And Control ◽  
Manufacturing Execution

Kurzfristige sowie ungeplante Änderungen – wie Auftragsschwankungen, Maschinenausfälle oder Krankheitstage der Mitarbeiter – beeinflussen die Produktionsplanung und -steuerung (PPS) von Industriefirmen. Trends wie Globalisierung und erhöhter Marktdruck verstärken diese Probleme. Zur Komplexitätsbewältigung bei der Entscheidungsfindung zur Fertigungssteuerung kommen in der Produktion Werkzeuge der „Digitalen Fabrik“, beispielsweise Simulationsprogramme, oder IT (Informationstechnologie)-Lösungen, wie Manufacturing Execution Systems (MES), zum Einsatz. Eine Verknüpfung dieser Bereiche würde einen echtzeitfähigen Datenaustausch erlauben, der wiederum eine echtzeitfähige Entscheidungsunterstützung bietet. Der Fachbeitrag stellt hierfür einen Lösungsansatz vor.   Sudden and unsystematic changes, such as fluctuations in order flow, machine failures, or employee sick days affect the Production Planning and Control (PPC) activities of industrial companies. Trends like globalization and increased market pressure intensify these problems. To master the complexity of decision-making in production control, tools of the digital factory (e.g. simulation systems) or IT systems (e.g. Manufacturing Execution Systems (MES)) are applied in manufacturing. Combining these areas would enable real-time capable data exchange which, in turn, provides real-time capable decision support. This article presents an approach for solving this problem.

scholarly journals Production Planning and Control System with Just in Time and Lean Production: A Review

2021 ◽  
Vol 6 (2) ◽  
pp. 019-027
Author(s):  
Afriansyah Afriansyah ◽  
Amrifan Saladin Mohruni
Keyword(s):  
Production Planning ◽  
Production Control ◽  
Lean Production ◽  
Production Method ◽  
Just In Time ◽  
Production Planning And Control ◽  
Planning And Control ◽  
The Difference ◽  
And Control ◽  
Structure Properties

Manufacturing can be defined as applying physical and/or chemical processes to modify the structure, properties, and appearance of a given starting material to produce parts or products. Manufacturing often entails combining multiple elements for the creation of assembled products. This study aimed to establish a general understanding of development production planning and control and typical products such as just in time and lean production. Method of this study through literature review. This study described activities related to production planning and production control, the difference between lean production and traditional production (push system), and the structure of lean production as known as Toyota system manufacturing.

Eine bibliometrische Analyse/PPC and machine learning A bibliometric analysis

2020 ◽  
Vol 110 (04) ◽  
pp. 220-225
Author(s):  
Matthias Schmidt ◽  
Janine Tatjana Maier ◽  
Mark Grothkopp
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Dynamic Environment ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Comprehensive Review ◽  
Planning And Control ◽  
Individual Task ◽  
The Individual ◽  
And Control

Produzierende Unternehmen stehen in einem dynamischen Umfeld vor der Herausforderung eine zunehmende Datenmenge effizienter zu verarbeiten. In diesem Zusammenhang werden häufig Ansätze des maschinellen Lernens (ML) diskutiert. Der Beitrag stellt eine umfassende Aufarbeitung des Stands der Forschung bezogen auf den Einsatz von ML-Ansätzen in der Produktionsplanung und -steuerung (PPS) bereit. Daraus lässt sich der Forschungsbedarf in den einzelnen Aufgabengebieten der PPS ableiten.   In a dynamic environment, manufacturing companies face the challenge of processing an increasing amount of data more efficiently. In this context, approaches of machine learning (ML) are often discussed. This paper provides a comprehensive review of the state of the art regarding the use of ML approaches in production planning and control (PPC). Based on this, the need for research in the individual task areas of PPC can be derived.

scholarly journals The concept of operation and production control

2021 ◽  
Vol 27 (2) ◽  
pp. 100-107
Author(s):  
Radosław Wolniak
Keyword(s):  
Artificial Intelligence ◽  
Production Planning ◽  
Industry 4.0 ◽  
Production Management ◽  
Production Control ◽  
Main Function ◽  
Production Planning And Control ◽  
Factors Affecting ◽  
Planning And Control ◽  
And Control

Abstract The theoretical aim of the paper is to analyses the main function and concept of production control in operation management. The empirical aim of the paper is to investigate polish production firm opinion about factors affecting production planning and control and also functions of production planning and control. Production control is very important in every factory, and every aspect of operation and production management especially in times of Industry 4.0 conditions. In the paper we presented all classical seven task of production management control. Also there is in the paper an analysis of main factors affecting production control in industrial organization. In the paper we analysed the problems connected with production control. Nowadays in the conditions of Industry 4.0 this is very important concept because the increasing level of digitalization of all industrial processes leads to possibility of detailed analysis of all processes and better level of control. Operation managers should have good level of knowledge about production control and especially quality control. They can use in this many new information tools like statistical methods and artificial intelligence. Especially we think that in the future many function of production control would be assisted by artificial intelligence. We also in the paper give results of research conducted on example of 30 polish production organizations located in Silesia region.

Energieautarke Produktion/Energy self-sufficient production - Challenges for an electricity self-supply in production planning and control

2017 ◽  
Vol 107 (03) ◽  
pp. 148-153
Author(s):  
M. Rösch ◽  
C. Schultz ◽  
S. Braunreuther ◽  
G. Prof. Reinhart
Keyword(s):  
Energy Supply ◽  
Energy Sources ◽  
Steady Increase ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Small Power ◽  
Planning And Control ◽  
Power Stations ◽  
And Control ◽  
Internal Consumption

Mit der Umstrukturierung des Stromnetzes im Zuge der Energiewende sind die Strompreise für Industriekunden zuletzt deutlich gestiegen. Gleichzeitig ist eine Kostendegression für Kleinkraftwerke sowie Stromspeicher zu beobachten, die zu einer wachsenden Attraktivität von Stromeigenversorgungen führt. Der Fachbeitrag beleuchtet das Umdenken, das dabei für Produktionsstandorte bei der Energieversorgung und der informationstechnischen Vernetzung aller Erzeuger und Verbraucher erforderlich ist.   Due to the steady increase of renewable and volatile energy sources, industrial customers are faced with rising prices for electricity. At the same time, falling costs for energy storage systems and small power stations, especially photovoltaic, make customer generation and internal consumption more attractive. This paper highlights the changes thus necessary for manufacturing companies with regard to the energy supply and the integration of generators and consumers.

scholarly journals Sistem Peramalan Jumlah Persediaan Minuman Menggunakan Metode Moving Average

CYCLOTRON ◽  
2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mochammad Rizaldi Putramawan
Keyword(s):  
Moving Average ◽  
Demand Forecasting ◽  
Production Data ◽  
Business Owner ◽  
Production Planning And Control ◽  
Analysis Techniques ◽  
Product Demand ◽  
Planning And Control ◽  
Forecasting System ◽  
And Control

Abstrak— Banyaknya usaha membuat tiap - tiap orang bersaing menjadi yang terbaik untuk mendapatkan konsumen. Ketika pemilik usaha tidak dapat memanfaatkan teknologi infomasi, maka banyak informasi yang terbuang percuma. Bentuk laporan yang masih manual membuat pemilik menjadi kesulitan dalam melihat perkembangan usaha, akibatnya pemilik dapat melakukan kesalahan dalam pengambilan keputusan terutama untuk penambahan atau pengurangan stok barang.Sedangkan, tiap perusahaan baik barang ataupun jasa menghendaki peningkatan profit di setiap bulannya, sehingga perusahaan ini memerlukan suatu aplikasi untuk membantu menentukan prediksi penjualan. Dengan demikian, dibutuhkan suatu aplikasi untuk peramalan yang sangat penting digunakan untuk mengelola semua perencanaan di dalam perusahaannya.Oleh karena itu, Manajemen perlu membuat peramalan permintaan produk secara tepat agar tidak terjadi kelebihan atau kekurangan produksi. Teknik analisis data menggunakan metode rata–rata bergerak (moving average) yang paling berdaya guna sebagai pendukung perencanaan dan pengendalian produksi sehingga bisa memaksimalkan manajemen rantai pasokan produk. Kata kunci: Sistem Peramalan, Moving Average Abstract— The number of businesses makes everyone competes to be the best to get consumers. When a business owner can not take advantage of information technology, a lot of information is wasted. The form of reports that are still manual makes the owner becomes difficult in seeing the development of the business, consequently the owner can make mistakes in making decisions, especially for the addition or reduction of inventory.Meanwhile, each company whether goods or services require increased profits in each month, so this company needs an application to help determine sales predictions. Thus, an application is required for very important forecasting used to manage all the planning within the company.Therefore, Management needs to make accurate product demand forecasting to avoid excess or lack of production. Data analysis techniques use the most effective moving average method as a supporter of production planning and control so as to maximize supply chain management.Keywords: Forecasting System, Moving Average

scholarly journals Production Planning and Control as Routing in Manufacturing Networks

MENDEL ◽  
2018 ◽  
Vol 24 (2) ◽  
pp. 1-8
Author(s):  
Terje Bach ◽  
Bjørn Jæger ◽  
Arild Hoff
Keyword(s):  
Production Planning ◽  
Network Routing ◽  
Production Planning And Control ◽  
Manufacturing Companies ◽  
Planning And Control ◽  
Manufacturing Networks ◽  
Manufacturing Network ◽  
And Control ◽  
A Company ◽  
Work Centre

In this paper, we explore the use of network routing for production planning and control in manufacturing of complex industrial products. Such a product is the result of a joint effort of many manufacturing companies; each considered a collection of work centre nodes connected by transportation links forming a company-wide manufacturing network. Each company is, in turn considered a manufacturing node connected to other manufacturers by transportation links forming a distributed manufacturing network that produces the final product. We model the manufacturing network as a distribution network where the incoming and outgoing inventories of products are distinct nodes in addition to the work centre nodes. Production planning and control are done by minimizing the cost of handling all products in all work centre nodes. This formulation provides a scalable and flexible production planning and control scheme adhering to the networked structure of manufacturing of complex products. We apply the model to a company-wide manufacturing network as a first approach. A case study using the model demonstrates production planning using network routing at a manufacturer of ship propulsion engines.

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