A case study for simulation and optimization based planning of production and logistics systems

Sobottka, Thomas; Kamhuber, Felix; Henjes, Jan; Sihn, Wilfried

doi:10.1109/wsc.2017.8248064

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…A key modelling and simulation technological driver in this field is Discrete Event Simulation (DES) Although the benefits of DES tools are obvious and the tools are well-established and widely available their practical application is limited 13 , especially in small and medium-sized enterprises (SME's). This is mainly due to the perceived complexity of the simulation modelling involved, the subsequent digital skillsets required and the time-consuming nature of data acquisition necessary for successful modelling and analysis.…”

Section: The Digital Twinmentioning

confidence: 99%

Steps towards a Connected Digital Factory Cost Model

Tierney¹,

Higgins²,

Higgins³

et al. 2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">Digital transformation is at the forefront of manufacturing considerations, but often excludes discrete event simulation and cost modelling capabilities, meaning digital twin capabilities are in their infancy. As cost and time are critical metrics for manufacturing companies it is vital the associated tools become a connected digital capability. The aim is to digitize cost modelling functionality and its associated data requirements in order to couple cost analysis with digital factory simulation. The vast amount of data existing in today’s industry alongside the standardization of manufacturing processes has paved the way for a ‘data first’ cost and discrete event simulation environment that is required to facilitate the automated model building capabilities required to seamlessly integrate the digital twin within existing manufacturing environments.</div><div class="htmlview paragraph">An ISA-95 based architecture is introduced where phases within a cost modelling and simulation workflow are treated as a series of interconnected modules: process mapping (including production layout definition); data collection and retrieval (resource costs, equipment costs, labour costs, learning rates, process/activity times etc.); network and critical path analysis; cost evaluation; cost optimisation (bottleneck identification, production configuration); simulation model build; cost reporting (dashboard visualisation, KPIs, trade-offs). Different phases are linked to one another to enable automated cost and capacity analysis. Leveraging data in this manner enables the updating of standard operating procedures and learning rates in order to better understand manufacturing cost implications, such as actual cost versus forecasted, and to incorporate cost implications into scheduling and planning decisions.</div><div class="htmlview paragraph">Two different case studies are presented to highlight different applications of the proposed architecture. The first shows it can be used within a feasibility study to benchmark novel robotic joining techniques against traditional riveting of stiffened aero structures.</div><div class="htmlview paragraph">In the second case study discrete event digital factory simulations are used to supply important production metrics (process times, wait times, resource utilisation) to the cost model to provide ‘real-time’ cost modelling. This enables both time and cost to be used for more informed decision making within an ever demanding manufacturing landscape. In addition, this approach will add value to simulation processes by enabling simulation engineers to focus on value adding activities instead of time consuming model builds, data gathering and model iterations.</div></div>

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Section: The Digital Twinmentioning

confidence: 99%

Steps towards a Connected Digital Factory Cost Model

Tierney¹,

Higgins²,

Higgins³

et al. 2023

SAE Technical Paper Series

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show abstract

“…Źródło: Opracowanie własne na podstawie (Mourtzis, 2020) Pomimo szerokich możliwości dyskretna symulacja komputerowa jest rzadko wykorzystywana w codziennych procesach decyzyjnych przedsiębiorstw, szczególnie tych małych i średnich. Podnoszonymi problemami są trudność modelowania (Sobottka et al, 2017), kosztowność i czasochłonność tworzenia modelu i eksperymentów symulacyjnych (Law & Kelton, 2000;Robinson, 2014). W modelowaniu DES wykorzystywany jest software różnego typu.…”

Section: Rysunek 1 Symulacja Komputerowa W Zarządzaniu Rozwojem I Eks...unclassified

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2023

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Streszczenie: Artykuł zawiera przegląd ważnych aspektów, które należy wziąć pod uwagę w trakcie kształtowania organizacji inteligentnej (OI), patrząc z perspektywy koncepcji Lean Management (LM) oraz narzędzi z tej kategorii, które można zastosować w celu formowania nowej struktury organizacyjnej, jaką jest OI. W początkowej części artykułu omówiono koncepcję OI oraz dokonano próby wskazania jej cech charakterystycznych. Następnie zaprezentowano koncepcję LM oraz pokrótce omówiono wybrane narzędzia, które można wykorzystać przy próbie formowania OI. Skupiono się na próbie dobrania i dopasowania narzędzi LM tak, aby przeanalizować, czy wdrożenie wybranego narzędzia będzie wspierało osiągnięcie jednej z charakterystycznych cech OI. W niniejszym artykule zaprezentowano wybrane narzędzia z szerokiej gamy instrumentów LM oraz przedstawiono, w jaki sposób owe narzędzia mogą pozytywnie wpływać na określone cechy OI. Skupiono się na rozwiązaniach możliwych do zaimplementowania w środowisku firm o charakterze produkcyjnym, gdyż sam Lean oraz jego charakterystyczne narzędzia wywodzą się z tradycji firm z tego segmentu. Intencją tej publikacji jest poszerzenie zbioru aktualnej wiedzy teoretycznej jako punktu wyjścia, który może posłużyć za odniesienie dla praktycznych badań naukowców.

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“…The use of technology linked in Cyber Physical Systems (CPS), such as, for example, the mapping, visualization and real-time control of textile processes through specialized software allows organizations to carry out a survey in the short term and can generate environmental control action plans. The simulation of industrial processes and the visualization of performance measurement indicators support the correct placement of the industrial infrastructure and at the same time the minimization of waste is achieved in the real physical world (Abreu, Alves & Moreira, 2017;Sobottka, Kamhuber, Henjes & Sihn, 2017).…”

Section: Industrial Textile Case: From Empiric System To Textile Indu...mentioning

confidence: 99%

Sustainable manufacturing in the fourth industrial revolution: A big data application proposal in the textile industry

González

Hernández²,

Vásquez³

et al. 2022

JIEM

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Purpose: Design an industrial production model with a focus on industry 4.0 (Big Data) and decision-making analysis for small and medium-sized enterprises (SMEs) in the clothing sector that allows improving procedures, jobs and related costs within the study organization Develop a sustainable manufacturing proposal for the industrial textile sector with a focus on Big data (entry, transformation, data loading and analysis) in organizational decision making, in search of time and cost optimization and environmental impact mitigation related.Design/methodology/approach: The present research, of an applied nature, raises a value proposition focused on the planning, design and structuring of an industrial model focused on Big Data, specifically in the apparel manufacturing sector for decision-making in a structured and automated way with the methodological approach to follow: 1) Approach of production strategies oriented in Big Data for the textile sector; 2) Definition of the production model and configuration of the operational system; 3) Data science and industrial analysis, 4) Production model approach (Power BI) and 5) model validation. Methodological design of the investigation. 1) Presentation of the case study, where the current situational analysis of the company is carried out, formulation of the problem and proposal of solution for the set of data analyzed; 2) Presentation of a solution proposal focused on Big Data, on the identification of the industrial ecosystem and integration with the company's information systems, as well as the solution approach in the study and science of data in real time; 3) Presentation of the Model proposal for SQL structured databases in the loading, transformation and loading of important information for this study; 4) Information processing, in the edition of data in the M language of Power BI software, construction and elaboration of the model; 5) Presentation of the related databases, in the integration with the foreign key of the Master table and the transactional Tables; 6) Data analysis and presentation of the Dashboard, in the design, construction and analysis of the related study variables, as well as the approach of solution scenarios in the correct organizational decision makingFindings: The results obtained show an improvement in operational efficiency from the value-added proposal. Research limitations/implications: Currently, the number of studies applying Big Data technology for organizations in the textile and manufacturing sector in organizational decision making are limited. If analyzed from the local scene, there are few cases of Big Data implementation in the textile sector, as a consequence of the lack of projects and financing of value propositions. Another limiting factor in this research is the absence of digital information of high relevance for study and analysis, which leads to longer times in data entry and placement in information systems in real time. Finally, there is no data organizational culture, where there are processes and/or procedures for data registration and its transformation into clean data.Originality/value: This research integrates, as well as the correct organizational decision making For the verification of originality, the project search and systematic review of literature in the main online search engines are carried out for this research; In addition, the percentages of coincidence with online reviewers such as turnitin and plag.es are reviewed in the transparency of this study project.

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A case study for simulation and optimization based planning of production and logistics systems

Cited by 10 publications

References 15 publications

Steps towards a Connected Digital Factory Cost Model

Steps towards a Connected Digital Factory Cost Model

Untitled

Sustainable manufacturing in the fourth industrial revolution: A big data application proposal in the textile industry

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