Advanced Planning and Scheduling Systems: Modeling and Implementation Challenges

Lupeikienė, Audronė; Dzemyda, Gintautas; Kiss, Ferenc; Čaplinskas, Albertas

doi:10.15388/informatica.2014.31

Cited by 20 publications

(12 citation statements)

References 113 publications

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“…Furthermore, manufacturing execution systems (MES) and advance planning and scheduling (APS) systems have also been developed in the last two decades to address some of these weaknesses of ERP systems (Öztürk & Ornek, 2014). While APS systems have been associated with various potential benefits, including support for real-time decision-making, the challenges associated with their implementation and integration with ERP systems render these benefits far from achievable in practice (Lupeikiene et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study

et al. 2021

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In furtherance of emerging research within smart production planning and control (PPC), this paper prescribes a methodology for the design and development of a smart PPC system. A smart PPC system uses emerging technologies such as the internet of things, big-data analytics tools and machine learning running on the cloud or on edge devices to enhance performance of PPC processes. It achieves this by using a wider range of data sources from the production system, capturing and utilizing the experience of production planners, using analytics and machine learning to harness insights from the data and allowing dynamic and near real-time action to the continuously changing production system. The proposed methodology is illustrated with a case study in a sweets and snacks manufacturing company, to highlight the key considerations and challenges production managers might face during its application. The case further demonstrates considerations for scalability and flexibility via a loosely coupled, service-oriented architecture and the selection of fitting algorithms respectively to address a business requirement for a short-term, multi-criteria and event-driven production planning and control solution. Finally, the paper further discusses the challenges of PPC in smart manufacturing and the importance of fitting smart technologies to planning environment characteristics.

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Section: Introductionmentioning

confidence: 99%

Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study

et al. 2021

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“…The concept of advanced planning and scheduling (APS) systems arose from join efforts of researchers and software developers to answer the challenges imposed by limitations of classical enterprise resource planning (ERP) systems (Lupeikiene et al , 2014). Such limitations include the absence of extended enterprise functionality, the lack of flexibility and of advanced decision support capabilities (Helo et al , 2014).…”

Section: Introductionmentioning

confidence: 99%

“…APS systems have wider ranges of functionalities related to production planning since it consists in their main goal (Vidoni and Vecchietti, 2015). In this sense, they do not substitute the ERP systems but supplement or extend them by providing advanced decision support tools (Lupeikiene et al , 2014). Most of the APS systems are tailored for their industries, involving specialized planning concepts, tasks, methods and optimization procedures (Ivert and Jonsson, 2010; Kilger and Wetterauer, 2015).…”

Section: Introductionmentioning

confidence: 99%

A framework for development of advanced planning and scheduling (APS) systems in glass container industry

Fachini

Espôsto

Camargo

2018

JMTM

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Purpose The purpose of this paper is to present a new framework for designing and implementing simple but effective advanced planning and scheduling (APS) systems in glass container industry by means of spreadsheets. Design/methodology/approach The conceptual framework for APS system design is developed by integrating principles of end-user computing and mixed-integer programming (MIP). This framework comprises the APS implementation and its integration with enterprise resource planning systems. Such a proposal is applied in a real-world glass bottle manufacturer and its performance assessment is carried out by using metrics of the well-known supply chain operations reference (SCOR) model. Findings The case study shows that the framework application can improve the responsiveness of glass container supply chain (SC) as well as reduce significantly SC planning costs. A further assessment of the end-user computing satisfaction highlights the general acceptance of the framework. Practical implications The proposed framework can assist glass industry managers and practitioners to solve their complex production planning problem since custom solutions are not available for this sector. Another important implication is the possible generalization of the framework given that MIP models for production planning are currently available in the literature for different industries. Originality/value On the one hand, the new framework successfully integrates concepts of end-user computing and MIP bridging the gap between theory of aforementioned areas and their practical applications. On the other hand, the paper contributes to the scarce literature on performance evaluation of APS systems and their impact on production system performance. The novel APS gain analysis based on SCOR metrics ensures that the system potential benefits are aligned with the modern concepts of supply chain management.

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“…A variety of methods and aspects of organizational modelling methods (perspectives, aspects and classifications of Business Process Modelling and Information Systems Modelling Techniques) are presented in Giaglis (2001), Krogstie (2012). The traditional EM and BPM methods and variety of aspects of IS domain modelling in IS development methods have no formal proving (evidence) for consistency from this viewpoint (Giaglis, 2001;Krogstie, 2012;Lupeikiene et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Towards Internal Modelling of the Information Systems Application Domain

Gudas¹,

Lopata²

2016

Informatica

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Model-driven IS engineering methods invoke the IS application domain modelling methods to acquire essential characteristics of organizational systems (enterprises). Business modelling for value creation is a relatively separate area, meanwhile it correlates with the IS application domain modelling methodologies and gives new insights for enhancement of enterprise modelling, business process modelling and BP management modelling approaches. The IS application domain and the business domain modelling are not isolated and could be investigated using the same paradigm of modelling. Yet there is some uncertainty in model-driven approaches towards the understanding of the enterprise management activities. A problematic consistency of modelling approaches indicate a need for a systemic analysis of IS application domain modelling concepts. The internal modelling paradigm is used for analysis of an enterprise management activity as a self-managed system, and hereby the lack of the conceptual basis for domain modelling in IS engineering is determined. This approach is aimed to reveal hidden information transactions of the business management activities. The understanding of the IS application domain as a self-managed system allowed to redefine such concepts as management transaction, management function and enterprise process. The metastructure of management transaction is defined and illustrated for business management layer and IS development layer.

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Advanced Planning and Scheduling Systems: Modeling and Implementation Challenges

Cited by 20 publications

References 113 publications

Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study

Designing and developing smart production planning and control systems in the industry 4.0 era: a methodology and case study

A framework for development of advanced planning and scheduling (APS) systems in glass container industry

Towards Internal Modelling of the Information Systems Application Domain

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