Optimization of multi-agent auctioning processes in flexible production networks

Gehlhoff, Felix; Nabizada, Hamied; Fay, Alexander

doi:10.1109/indin41052.2019.8972115

Cited by 3 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Possible cost functions can include factors like material selection, set-up costs or location of production facilities (logistics) as well as trust. Additionally, if the participants of the coordination algorithm stem from different companies and use real prices (in contrast to transfer prices) the figure has to include the company's profit margin (Gehlhoff et al, 2019). The coordinator also implements scheduling functions that for example take sequence restrictions into account (Weyrich et al, 2014).…”

Section: Case Of Study Ocp and Af With The I40 Demonstratorsmentioning

confidence: 99%

“…cost of materials and order size) to calculate their costs. Afterwards, they calculate prices based on the margin that they aim for and additional optimization that includes the conditions on the market place and possible synergies (Gehlhoff et al, 2019). The coordinator chooses suitable offers to create the total offer and determines the total price and delivery date for the order.…”

Section: Order Management Using Opc Uamentioning

confidence: 99%

See 1 more Smart Citation

Automation platform independent multi-agent system for robust networks of production resources in industry 4.0

et al. 2021

Self Cite

View full text Add to dashboard Cite

The Cyber-Physical Production System (CPPS) is a concept derived from software (cyber) and hardware (physical) applications and is based on global information exchange between such systems. The CPPS is known as a trend of Industry 4.0 (I4.0) focusing on flexibility regarding new products and adaptability to new requirements. This paper focuses on two I4.0 scenarios described by the Platform Industrie 4.0 that describe challenges for the industry towards its digital future. First, it looks at the Order Controlled Production (OCP) scenario that deals with flexible and self-configuring production networks. It describes the dynamic organization of production resources required to execute a production order. Second, the Adaptable Factory (AF) application scenario is discussed, which focuses on the configuration of production resources and describes the adaptability of an individual facility through (physical) modification. This paper first provides a detailed analysis of the requirements from these scenarios. Furthermore, it analyses the current Multi-Agent System (MAS) architectures and agent-based planning and decision support systems requirements. MAS can be used to create application-independent I4.0 systems with arbitrary hardware automation platforms. To create a scalable communication network that also supports application independence and enables the semantically machine-readable description of the exchanged data, the OPC UA standard was adopted. As a result of the study, the concept shows how different and independent automation platforms can be seamlessly connected via OPC UA. The proposed MAS concept has been evaluated in different use cases, namely OCP and AF.

show abstract

Section: Case Of Study Ocp and Af With The I40 Demonstratorsmentioning

confidence: 99%

Section: Order Management Using Opc Uamentioning

confidence: 99%

Automation platform independent multi-agent system for robust networks of production resources in industry 4.0

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

Agent-Based Manufacturing Control for Industry 4.0—Fundamentals and Open Challenges

Gehlhoff,

Fay

2024

The Oxford Handbook of Agent-Based Computational Management Science

View full text Add to dashboard Cite

Manufacturing companies face different challenges like rising complexity of their manufacturing operations, the need to quickly develop and produce individualized products, and disruptions of traditional production systems due to changing market conditions, institutional rules, and customer preferences. Thus, there is a significant need for flexible and robust organization and control approaches to cope with these new realities. Industry 4.0 proclaims the automated and decentralized decision-making of products and resources based on digitalization, referring to the automated coordination of job allocation and execution. The decentralized coordination of products and resources also enables the local reaction to disturbances on the shop floor and within supply chains. Thus, to address the abovementioned challenges, Industry 4.0 provides a reference framework to utilize digitally enhanced technologies and recent computational developments like cyber-physical systems, the internet of things, and the smart factory to face these new challenges. Software agents, which are commonly associated with properties such as autonomy, intelligence, and sociability, provide the means to implement these new approaches. However, different aspects of the manufacturing control problem and engineering process, like interoperability, predictability, and business ethics, still need to be addressed.

show abstract

On agent-based decentralized and integrated scheduling for small-scale manufacturing

Gehlhoff

Fay

2019

At - Automatisierungstechnik

View full text Add to dashboard Cite

Small-scale manufacturing often relies on flexible production systems that can cope with frequent changes of products and equipment. Transports are a significant part of the production flow, especially in the domain of large and heavy workpieces that requires explicit planning to avoid unnecessary delays. This contribution takes a detailed look at how to create feasible integrated schedules within a decentralised or even heterarchical architecture and which information the agents have to exchange. These schedules incorporate constraints such as the blocking-constraint. They also consider dynamic setup and operation durations while finding a good-enough solution. The proposed agent-based solution applies to a wide variety of scheduling problems and reveals positive properties in terms of scalability and reconfigurability.

show abstract

Optimization of multi-agent auctioning processes in flexible production networks

Cited by 3 publications

References 11 publications

Automation platform independent multi-agent system for robust networks of production resources in industry 4.0

Automation platform independent multi-agent system for robust networks of production resources in industry 4.0

Agent-Based Manufacturing Control for Industry 4.0—Fundamentals and Open Challenges

On agent-based decentralized and integrated scheduling for small-scale manufacturing

Contact Info

Product

Resources

About