Automated execution and evaluation of simulation experiments in the context of backward simulation

Manufacturing processes are increasingly driven by new product requirements, innovation, and cost efficiency. As a result, researchers are exploring new techniques and tools to optimize operational production planning. One such tool is backward-oriented discrete event simulation (SimBack), which has shown great potential in this field. However, the process of conducting numerous simulation runs required for backward simulation is often time and resource-intensive, which limits its efficiency. To address this challenge, this paper presents an approach for automated execution and evaluation of simulation experiments in the context of a backwardoriented discrete event simulation approach for scheduling and capacity planning. The authors demonstrate their approach using a simulation model of the Semiconductor Manufacturing Testbed 2020 (SMT2020)

A biased-randomized simheuristic for a hybrid flow shop with stochastic processing times in the semiconductor industry

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksCompared to other industries, production systems in semiconductor manufacturing have an above-average level of complexity. Developments in recent decades document increasing product diversity, smaller batch sizes, and a rapidly changing product range. At the same time, the interconnections between equipment groups increase due to rising automation, thus making production planning and control more difficult. This paper discusses a hybrid flow shop problem with realistic constraints, such as stochastic processing times and priority constraints. The primary goal of this paper is to find a solution set (permutation of jobs) that minimizes the production makespan. The proposed algorithm extends our previous work by combining biased-randomization techniques with a discrete-event simulation heuristic. This simulation-optimization approach allows us to efficiently model dependencies caused by batching and by the existence of different flow paths. As shown in a series of numerical experiments, our methodology can achieve promising results even when stochastic processing times are considered.Peer ReviewedPostprint (author's final draft

A biased-randomized discrete-event algorithm for the hybrid flow shop problem with time dependencies and priority constraints

Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneous jobs are processed by a number of machines. The route that each job has to follow depends upon its type, and, in addition, some machines require that a number of jobs are combined in batches before starting their processing. The hybrid flow model is also subject to a global priority rule and a “same setup” rule. The primary goal of this study was to find a solution set (permutation of jobs) that minimizes the production makespan. While simulation models are frequently employed to model these time-dependent flow shop systems, an optimization component is needed in order to generate high-quality solution sets. In this study, a novel algorithm is proposed to deal with the complexity of the underlying system. Our algorithm combines biased-randomization techniques with a discrete-event heuristic, which allows us to model dependencies caused by batching and different paths of jobs efficiently in a near-natural way. As shown in a series of numerical experiments, the proposed simulation-optimization algorithm can find solutions that significantly outperform those provided by employing state-of-the-art simulation software.Peer ReviewedPostprint (published version

DESIGN AND IMPLEMENTATION OF A RICH INTERNET APPLICATION FOR PLANNING AND VISUALIZATION OF SUPPLY-CHAIN-PROCESSES

The globalization of markets characterized by increasing networking of economy, result in a strong competition of worldwide producing companies. These companies face challenges evented by individual products and short production times. This requires planning fundamentally refocuses on production and logistics which are highly complex supply chain processes. To handle the amount of information, companies currently use various slides and spreadsheets and documents or personally meetings in project rooms. The distributed and heterogeneous representation of the complex interactions reduce transparency and hamper the understanding of processes. A technology which offers an interesting approach to solve these Problems is the new technology of the Rich Internet Applications (RIA). RIAs are a new kind of web-based applications, equivalent to traditional desktop programs in their performance, capabilities and display options. In this paper this technology is used to design and implement a RIA for the planning and visualization of modern supply chain processes

Automatic evaluation of logistics processes based on system of indicators with the help of Microsoft Sharepoint

Due to the globalization, internationalization and the shift from seller-markets to buyermarkets, the demands on companies regarding efficiency and effectiveness steadily increase, leading to an increased competition. For each company, it is necessary to remain able to respond quickly to changes in daily production. Many problems according to its effectiveness and efficiency are caused by inadequate logistics processes, although the potential of these processes could be carried out by the permanent check of the actual performance against the background of the customer’s requirements. In order to challenge this measurement, the reorganisation of processes must be based exclusively on a full analysis of the existing processes, where key performance indicators are the basis. Key success factors during implementation and usage are the reduction of costs and cycle times with consistent quality. The aim of our approach is an automatic, key performance indicator-based assessment of logistics processes involving the Microsoft SharePoint technologies. To achieve this objective, a method is designed which includes 3 steps: 1) process documentation, 2) process analysis and 3) process evaluation. Step 1 describes the documentation of a selected logistic process and ensures, that the requirements and conditions for the next steps are met. This also includes the development of a process model. Process analysis aims at the elaboration of indicators, their measurement points and data sources on the basis of concrete objectives (e. g. the reduction of logistic costs). The last step is to identify those sub processes, that have to be changed. All steps are validated by an example of the procurement process of a producing company. The evaluation of the keys performance indicators is also implemented.business, performance, indicators, processes, analysis

Simulation-based planning of maintenance activities by a shifting priority method

Machine failures are major causes of direct downtime as well as system losses (blocked and idle times) in production flows. A previous case study shows that prioritizing bottleneck machines over others has the potential to increase the throughput by about 5%. However, the bottleneck machine in a production system is not static throughout the process of production but shifts from time to time. The approach for this paper is to integrate dynamic maintenance strategies into scheduling of reactive maintenance using Discrete Event Simulation. The aim of the paper is to investigate how a shifting priority strategy could be integrated into the scheduling of reactive maintenance. The approach is applied to and evaluated in an automotive case-study, using simulation for decision support. This shows how to shift prioritization by tracking the momentary bottleneck of the system. The effect of shifting priorities for planning maintenance activities and its specific limitations is discussed

Simulation-based planning of maintenance activities in the automotive industry

Factories world-wide do not utilize their existing capacity to a satisfactory level. Several studies indicate an average Overall Equipment Efficiency (OEE) of around 55% in manufacturing industry. One major reason is machine downtime leading to substantial system losses culminating in production plans with un-satisfactory robustness. This paper discusses an approach to integrate maintenance strategies into a pro-duction planning approach using discrete event simulation. The aim is to investigate how and where in the planning process maintenance strategies can be integrated and how different maintenance strategies influence production performance and the overall robustness of production plans. The approach is exemplified in an automotive case study, integrating strategies for reactive maintenance in a simulation model to sup-port decision making on how repair orders should be prioritized to increase production performance. The results show that introducing priority-based planning of maintenance activities has a potential to increase productivity by approximately 5%

Buffer Utilization Based Scheduling of Maintenance Activities by a Shifting Priority Approach – A Simulation Study

Machine breakdowns and improper maintenance management cause production systems to function inefficiently. Particularly, breakdowns cause rippling effects on other machines in terms of starved and blocked states. Effective planning of maintenance can lead to improved production system efficiency. This paper aims at improving system throughput through prioritization of maintenance work orders by continuously monitoring buffer levels. This paper proposes and tests a new approach to determine the machine priorities for dynamic scheduling of maintenance work orders by identifying buffer utilization. The approach is exemplified in an industrial use-case. The results have shown to increase throughput in comparison to a first-come-first-served approach for executing maintenance work orders. This new approach relies on simple data collection and analysis, which makes it a viable option for industries to implement with minimal effort. The results can suggest that systems view for maintenance prioritization can be a powerful decision support tool for maintenance planning

Multi-Layer Architecture for Transition of Business-Models to common Software-Tools and Optimization of the Model-Structure exemplified with Microsoft SharePoint 2010

ABSTRACT This paper describes a model to transfer established business models like bml models into a new dynamic structure which is immediately usable in standard software and portable between different systems without complete reengineering. Many products like Microsoft SharePoint provide toolkits for workflow development but these workflows are stored commonly in a proprietary way and are not easy alterable and adoptable. Aside from the possibility to embed complex business models in standard software, this approach supports runtime altering of the workflow structure in terms of optimization of the process structure to different targets like time, cost and quality. An exemplary extension to the basic model is given which describes a capacity limitation in single process steps. To respect these bounds it is necessary to embed artificial constraints in the workflow structure. To reach the goal of a loose coupled dynamic structure a multilayer architecture was developed, in which dynamically connected objects are used to represent the formal model structure. This approach allows a translation of processdescriptions into requirement-definitions which can be stored in relational database structures. The approach was validated by developing a prototype based on SharePoint 2010. A short description of the prototype follows the conceptual introduction