scholarly journals Application of Reinforcement Learning in Production Planning and Control of Cyber Physical Production Systems

2018 ◽  
pp. 123-132 ◽  
Author(s):  
Andreas Kuhnle ◽  
Gisela Lanza
Keyword(s):  
Reinforcement Learning ◽  
Production Planning ◽  
Production Systems ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Cyber Physical Production Systems ◽  
And Control

An Ontology-Based Approach for Production Planning and Control of Cyber-Physical Production Systems

2020 ◽  
pp. 274-300
Author(s):  
Elvis Hozdić
Keyword(s):  
Production Planning ◽  
Manufacturing Systems ◽  
Production Systems ◽  
System Structure ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Control Functions ◽  
Foundational Ontology ◽  
Cyber Physical Production Systems ◽  
And Control

The objective of this research is to develop a new ontology-based approach for the management and control of cyber-physical production systems (CPPSs). In the CPPSs, the management and control functions are integrated with a physical part of manufacturing system. The function of production planning and control of manufacturing systems (PPC) is an important part of the management and control of the CPPSs. The elements of the cyber system structure enable the dynamic management and control of manufacturing systems in real time, through the realization of the digitalized and cybernated functions of PPC. The proposed approach to management and control of the CPPSs is based on the foundational ontology of manufacturing systems. The digitalized production planning, scheduling, and control functions are implemented as a multi-agent system (MAS). The communication between agents was addressed to support the autonomic decision for each individual agent. A case study demonstrates feasibility of the approach through the use of simulation experiments.

scholarly journals Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications

2020 ◽  
Vol 12 (9) ◽  
pp. 3791 ◽  
Author(s):  
Olumide Emmanuel Oluyisola ◽  
Fabio Sgarbossa ◽  
Jan Ola Strandhagen
Keyword(s):  
Production Planning ◽  
Production Management ◽  
Production Systems ◽  
Production Planning And Control ◽  
Market Uncertainty ◽  
Planning And Control ◽  
Make To Order ◽  
Smart Technologies ◽  
And Control ◽  
Process Strategy

Many companies are struggling to manage their production systems due to increasing market uncertainty. While emerging ‘smart’ technologies such as the internet of things, machine learning, and cloud computing have been touted as having the potential to transform production management, the realities of their adoption and use have been much more challenging than anticipated. In this paper, we explore these challenges and present a conceptual model, a use-case matrix and a product–process framework for a smart production planning and control (smart PPC) system and illustrate the use of these artefacts through four case companies. The presented model adopts an incremental approach that companies with limited resources could employ in improving their PPC process in the context of industry 4.0 and sustainability. The results reveal that while make-to-order companies are more likely to derive greater benefits from a smart product strategy, make-to-stock companies are more likely to derive the most benefit from pursuing a smart process strategy, and consequently a smart PPC solution.

scholarly journals Investigation of the Potential to Use Real-Time Data in Production Planning and Control of Make to Order (MTO) Manufacturing Companies

2021 ◽  
pp. 165-185
Author(s):  
Manuel Woschank ◽  
Patrick Dallasega ◽  
Johannes A. Kapeller
Keyword(s):  
Real Time ◽  
Production Planning ◽  
Production Systems ◽  
Lead Times ◽  
Production Planning And Control ◽  
Time Data ◽  
Planning And Control ◽  
Make To Order ◽  
Real Time Data ◽  
And Control

AbstractThe integrated planning and control of logistics processes can be seen as one of the basic prerequisites for the successful implementation of smart production systems and smart and lean supply chains, as well. Therefore, modern Industry 4.0 approaches are mainly focusing on (1) the principles of decentralization and (2) the usage of real-time data to improve the overall logistics performance in terms of promised delivery dates, work in progress, capacity utilization, and lead-times. In this context, this chapter systematically evaluates the application of decentralized production planning and control strategies, e.g., KANBAN and CONWIP, in comparison with traditional approaches, like MRP. Moreover, the impact of real-time data usage in production planning and control systems on lead-times and work in progress is investigated using a discrete event simulation based on primary data from a make to order manufacturer. The results of this industrial case study research confirm the significant potential that lies in smart production systems and smart and lean supply chains and, therefore, in the introduction of Industry 4.0 technologies and technological concepts in production and logistics systems.

Simulationsbasierte Produktionsassistenz*/Simulation-driven operation assistance

2018 ◽  
Vol 108 (03) ◽  
pp. 148-154
Author(s):  
G. Höllthaler ◽  
C. Richter ◽  
M. Hörmann ◽  
A. Zipfel ◽  
J. Fischer ◽  
...  
Keyword(s):  
Production Planning ◽  
Material Flow ◽  
Production Systems ◽  
General Description ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Simulation Based ◽  
Production Area ◽  
And Control ◽  
Detailed Presentation

Mit zunehmender Komplexität in Produktionssystemen, die sich auch aus der steigenden Variantenvielfalt ergibt, sind Entscheider im Produktionsumfeld mit immer komplexeren Fragestellungen konfrontiert. Zur Entscheidungsunterstützung stellt dieser Beitrag ein simulationsbasiertes Assistenzsystem vor. Neben einer allgemeinen Beschreibung des Aufbaus des Assistenzsystems wird im Detail der integrierte Materialflussservice betrachtet, der zur Beantwortung von Fragen rund um die Produktionsplanung und -steuerung zum Einsatz kommt.   An increasing complexity in production systems resulting, for example, from a growing number of variants, gives rise to more complex issues which stakeholders in the production area have to cope with. To support these stakeholders, this paper introduces a novel simulation-based assistant system. In addition to the general description of the assistant system’s setup, a detailed presentation of the integrated material flow service is given. This service deals with issues of production planning and control.

scholarly journals Production Planning and Control (PPC): production pointing system deployment, use and unfolding

2020 ◽  
Vol 11 (5) ◽  
pp. 1551
Author(s):  
José Henrique de Andrade ◽  
Francisco Andrea Simões Braga ◽  
Luciano Campanini ◽  
Josadak Astorino Marçola ◽  
Bruna Carvalho Nunes Rocha
Keyword(s):  
Production Planning ◽  
Production Management ◽  
Production Control ◽  
Production Systems ◽  
Production Planning And Control ◽  
Planning And Control ◽  
Management Processes ◽  
Efficiency And Effectiveness ◽  
And Control

The growing need for efficiency and effectiveness in production systems management has increased the importance of processes and activities related to Production Planning and Control (PPC). Several authors point out that the more dynamic, competitive market, with higher demands from consumers and the increasing insertion of technology to support decision making, make the need for robust management processes imperative. In line with this scenario, the present work aims to present the report of a process of implementation, use and the consequences of a production pointing system. To achieve the proposed objective, a literature review was conducted on the topics of interest and a case study in a company that manufactures hospital medical products in the interior of São Paulo state. As main results, it was observed that the adoption and evolution of a production pointing system generated significant gains for the company's Production Control and increased maturity in terms of Production Management, but required significant efforts and investments to maintain and evolve the production deploying process.

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