TY - CHAP

T1 - Towards a Service-Oriented Architecture for Production Planning and Control

T2 - 5th Conference on Production Systems and Logistics - CPSL 2023

AU - Behrendt, Sebastian

AU - Stamer, Florian

AU - May, Marvin Carl

AU - Lanza, Gisela

N1 - Conference code: 5

PY - 2023

Y1 - 2023

N2 - The trends of shorter product lifecycles, customized products, and volatile market environments require manufacturers to reconfigure their production increasingly frequent to maintain competitiveness and customer satisfaction. More frequent reconfigurations, however, are linked to increased efforts in production planning and control (PPC). This poses a challenge for manufacturers, especially in regard of demographic change and shortage of qualified labour, since many tasks in PPC are performed manually by domain experts. Following the paradigm of software-defined manufacturing, this paper targets to enable a higher degree of automation and interoperability in PPC by applying the concepts of service-oriented architecture. As a result, production planners are empowered to orchestrate tasks in PPC without consideration of underlying implementation details. At first, it is investigated how tasks in PPC can be represented as services with the aim of encapsulation and reusability. Secondly, a software architecture based on asset administration shells is presented that allows connection to production data sources and enables integration and usage of such PPC services. In this sense, an approach for mapping asset administrations shells to OpenAPI Specifications is proposed for interoperable and semantic integration of existing services and legacy systems. Lastly, challenges and potential solutions for data integration are discussed considering the present heterogeneity of data sources in manufacturing.

AB - The trends of shorter product lifecycles, customized products, and volatile market environments require manufacturers to reconfigure their production increasingly frequent to maintain competitiveness and customer satisfaction. More frequent reconfigurations, however, are linked to increased efforts in production planning and control (PPC). This poses a challenge for manufacturers, especially in regard of demographic change and shortage of qualified labour, since many tasks in PPC are performed manually by domain experts. Following the paradigm of software-defined manufacturing, this paper targets to enable a higher degree of automation and interoperability in PPC by applying the concepts of service-oriented architecture. As a result, production planners are empowered to orchestrate tasks in PPC without consideration of underlying implementation details. At first, it is investigated how tasks in PPC can be represented as services with the aim of encapsulation and reusability. Secondly, a software architecture based on asset administration shells is presented that allows connection to production data sources and enables integration and usage of such PPC services. In this sense, an approach for mapping asset administrations shells to OpenAPI Specifications is proposed for interoperable and semantic integration of existing services and legacy systems. Lastly, challenges and potential solutions for data integration are discussed considering the present heterogeneity of data sources in manufacturing.

KW - asset administration shell

KW - Industry4.0

KW - interoperability

KW - service-oriented architecture

KW - Service-oriented production

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85188018393&partnerID=8YFLogxK

U2 - 10.15488/15271

DO - 10.15488/15271

M3 - Article in conference proceedings

AN - SCOPUS:85188018393

T3 - Proceedings of the Conference on Production Systems and Logistics

SP - 255

EP - 267

BT - Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2

A2 - Herberger, David

A2 - Hübner, Marco

PB - Publish-Ing in cooperation with TIB - Leibniz Information Centre for Science and Technology University Library

CY - Hannover

Y2 - 14 November 2023 through 17 November 2023

ER -