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Browsing by Subject "Production planning"

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Combining Process Mining And Simulation In Production Planning

Langer, Adrian; Ortmeier, Christian; Martin, Niels Lasse; Abraham, Tim; Herrmann, Christoph (Hannover : publish-Ing., 2021)

The conditions for industrial companies are changing due to increasing customer demands for individualised as well as sustainable products. Furthermore, companies are confronted with technological change by digital tra ...
Computational Manufacturing for Multi-Material Lightweight Parts

Hürkamp, André; Lorenz, Ralf; Behrens, Bernd-Arno; Dröder, Klaus (Amsterdam [u.a.] : Elsevier, 2019)

In this contribution, a computational approach for the manufacturing of multi-material lightweight parts is presented. For an efficient online optimization procedure, a proper orthogonal decomposition on offline obtained ...
Computer-Aided Assembly Sequence Planning for High-Mix Low-Volume Products in the Electronic Appliances Industry

Yao, Mingyue; Drescher, Benny; Stewart, Erik; Manoj, Lakshmi; Wittstamm, Max; Henke, Leonhard; Ghodasara, Shyam; Ge, Ming (Hannover : publish-Ing., 2022)

Electronic appliance manufacturers are facing the challenge of frequent product orders. Based on each product order, the assembly process and workstations need to be planned. An essential part of the assembly planning is ...
Conceptualization of the use of Artificial Intelligence for Interdependencies Analysis in Requirements Engineering

Burggräf, Peter; Bergweiler, Georg; Fiedler, Falko; Slawik, Viktor; Recker, Jonas (Hannover : publish-Ing., 2022)

The efficiency in product development is largely determined by the quality of the requirements and the ability of the product design and production planner to analyze them. Interdependencies between multiple requirements ...
Continuous modelling of machine tool failure durations for improved production scheduling

Denkena, Berend; Dittrich, M.-A.; Keunecke, L.; Wilmsmeier, S. (Heidelberg : Springer, 2020)

Unforeseen machine tool failures due to technical issues can cause downtimes leading to delays during production. To reduce delays, rescheduling of the production is, in most cases, necessary. However, warranting such a ...
Cross-Company Routing Planning: Determining Value Chains in a Dynamic Production Network Through a Decentralized Approach

Markert, Julia; Saubke, Dominik; Krenz, Pascal; Hotz, Lothar (Hannover : publish-Ing., 2022)

Demand-based, local production will gain relevance in the context of sustainability and circular economy. One way to implement local value creation is through establishing highly dynamic networks that consolidate the ...
Deep Reinforcement Learning In Production Planning And Control: A Systematic Literature Review

Panzer, Marcel; Bender, Benedict; Gronau, Norbert (Hannover : publish-Ing., 2021)

Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions ...
Development of a Concept for Real-Time Control of Manual Assembly Systems

Sudhoff, Martin; Linsinger, Matthias; Schulte, Daniel; Kuhlenkötter, Bernd (Hannover : publish-Ing., 2020)

In contrast to automated machines and installations, manual assembly still lacks real-time process monitoring and possibilities for short-term control and adaptation of assembly systems. This article describes an approach ...
Discovering Heuristics And Metaheuristics For Job Shop Scheduling From Scratch Via Deep Reinforcement Learning

van Ekeris, Tilo; Meyes, Richard; Meisen, Tobias (Hannover : publish-Ing., 2021)

Scheduling is the mathematical problem of allocating tasks to resources considering certain constraints. The goal is to achieve the best possible scheduling quality given a quality metric like makespan. Typical scheduling ...
Do We Really Know The Benefit Of Machine Learning In Production Planning And Control? A Systematic Review Of Industry Case Studies.

Kramer, Kathrin Julia; Rokoss, Alexander; Schmidt, Matthias (Hannover : publish-Ing., 2021)

The field of machine learning (ML) is of specific interest for production companies as it displays a perspective to handle the increased complexity within their production planning and control (PPC) processes in an ...
Framework for the Application of Industry 4.0 in Lithium-Ion Battery Cell Production

Schmied, Jessica; Puchta, Alexander; Scharmann, Timon; Töpper, Hans-Christoph; Kampker, Achim; Fleischer, Jürgen; Dröder, Klaus; Daub, Rüdiger (Hannover : publish-Ing., 2022)

The application of Industry 4.0 in lithium-ion battery cell production enables companies to achieve increased product quality and global competitiveness, since the majority of value creation takes place in this process. ...
Influence of ISO 9001 on the configuration of production planning and control

Hillnhagen, Simon; Mütze, Alexander; Nyhuis, Peter; Schmidt, Matthias (Amsterdam [u.a.] : Elsevier, 2024)

The target-oriented configuration of production planning and control (PPC) is a critical factor for companies with increasingly complex supply chains. The logistical performance of companies, which can be measured and ...
Modelling The Influence Of Production Planning And Production Scheduling On Business Performance In The Manufacturing Industry Of South Africa

Chinomona, Elizabeth; Kgaogelo Mogano, Mamonare Minky (Hannover : publish-Ing., 2023)

It is apparent that for manufacturing companies to succeed, it is crucial to consider the factors that will contribute positively to the performance of the business. The issues related to production planning and production ...
Ontology-based production planning under the consideration of system robustness

Denkena, Berend; Dittrich, Marc-André; Münch, Gina Vibora (Amsterdam [u.a.] : Elsevier, 2021)

Volatile markets and high customer requirements regarding schedule reliability increase the relevance of robust production planning. To achieve robustness in planning, system-inherent buffers are used. Buffers include ...
Operational planning of maintenance measures by means of event-driven simulation

Denkena, B.; Kršninga, S.; Doreth, K. (Amsterdam [u.a.] : Elsevier, 2012)

Modern manufacturing systems are characterized by an increasing complexity and high dynamic. This leads to new challenges for the operational planning of maintenance and production. This paper introduces a novel approach ...
Optimization of delivery adherence based on capacity planning and bid pricing

Denkena, B.; Dittrich, M.-A.; Wilmsmeier, S.; Stamm, S. (Heidelberg : Springer, 2020)

Sales revenues of enterprises are often subject to seasonal fluctuation. This leads to high or low utilized resources and this in turn to revenue losses. Hence, the enterprises invest a high effort to improve long and ...
The Potential of AutoML for Demand Forecasting

Kramer, Kathrin Julia; Behn, Niclas; Schmidt, Matthias (Hannover : publish-Ing., 2022)

In demand forecasting, which can depend on various internal and external factors, machine learning (ML) methods can capture complex patterns and enable precise forecasts. Accurate forecasts facilitate targeted, demand-oriented ...
Process Data Validation for Manual Assembly Systems used for Highly Variable Products

Sudhoff, Martin; Viehöver, Jonas; Herzog, Michael; Kuhlenkötter, Bernd (Hannover : publish-Ing., 2022)

The production of customized goods is becoming more and more important for industrial companies. The large number of variants resulting from this, up to batch size 1 production, requires a high degree of flexibility. To ...
Tactical Production Planning for Customer Individual Products in Changeable Production Networks

be Isa, Johannes; Zimmermann, Thomas; Scherwitz, Phiipp; Reinhart, Gunther (Hannover : publish-Ing., 2020)

The requirements of future production are characterized by increasing demand volatility as well as very short delivery times and high timeliness in the order-based production environment. Furthermore, the trend to customer ...

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