Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560433
Araz Ashouri, Yitian Hu, G. Newsham, W. Shen
Building system faults in commercial and office buildings can result in a reduced occupant comfort and increased utility bills. Energy performance-based anomaly detection helps operators efficiently identify faults. In this work, a data-driven method for anomaly detection is presented. Using a symbolic aggregate method, the weekly energy demand profiles are statistically quantised and labeled to determine normal and abnormal building behaviours. A case study with three federal office buildings has been conducted to demonstrate the proposed method. The resulting technology provides building operators with easily-interpreted and actionable information for optimised building performance.
{"title":"Energy Performance Based Anomaly Detection in Non-Residential Buildings Using Symbolic Aggregate Approximation","authors":"Araz Ashouri, Yitian Hu, G. Newsham, W. Shen","doi":"10.1109/COASE.2018.8560433","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560433","url":null,"abstract":"Building system faults in commercial and office buildings can result in a reduced occupant comfort and increased utility bills. Energy performance-based anomaly detection helps operators efficiently identify faults. In this work, a data-driven method for anomaly detection is presented. Using a symbolic aggregate method, the weekly energy demand profiles are statistically quantised and labeled to determine normal and abnormal building behaviours. A case study with three federal office buildings has been conducted to demonstrate the proposed method. The resulting technology provides building operators with easily-interpreted and actionable information for optimised building performance.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"85 5","pages":"1400-1405"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91432804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560449
F. Quinton, Idir Hamaz, L. Houssin
This paper considers the cyclic jobshop problem in a flexible context where is objective is to find the minimum cycle time of a periodic schedule. The flexibility feature comes from the ability of the machines or robots to perform several kinds of tasks. Hence, the scheduling problem does not only concern starting time of tasks but also on which machines the tasks will be performed. We propose an exact method to solve this problem and two heuristics.
{"title":"Algorithms for the flexible cyclic jobshop problem","authors":"F. Quinton, Idir Hamaz, L. Houssin","doi":"10.1109/COASE.2018.8560449","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560449","url":null,"abstract":"This paper considers the cyclic jobshop problem in a flexible context where is objective is to find the minimum cycle time of a periodic schedule. The flexibility feature comes from the ability of the machines or robots to perform several kinds of tasks. Hence, the scheduling problem does not only concern starting time of tasks but also on which machines the tasks will be performed. We propose an exact method to solve this problem and two heuristics.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"48 1","pages":"945-950"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91533742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560374
Carlos Franco, V. Augusto, Thierry Garaix, Edgar Alfonso-Lizarazo, M. Bourdelin, H. Bontemps
Automation in healthcare is a major challenge to improve quality of service while compressing costs. In particular, correct administration of medicines to patients is crucial to ensure quality of care during hospitalization and minimize medication errors. Mistakes are more likely to happen when medicine administration is done manually (dispensing, ordering or administrating). To reduce the risks related to medication errors, automation of the pharmacy processes appears as an appropriately tool to solve this situation. In this paper, we have proposed a new mathematical model to optimize the processes related to unit-doses management and prescriptions preparation in a network of hospitals. To model the uncertainty associated with the demand of medicines, the concept of p-robustness is included; the concept of resilience is also considered to model the risk of centralized distribution processes.
{"title":"Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach","authors":"Carlos Franco, V. Augusto, Thierry Garaix, Edgar Alfonso-Lizarazo, M. Bourdelin, H. Bontemps","doi":"10.1109/COASE.2018.8560374","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560374","url":null,"abstract":"Automation in healthcare is a major challenge to improve quality of service while compressing costs. In particular, correct administration of medicines to patients is crucial to ensure quality of care during hospitalization and minimize medication errors. Mistakes are more likely to happen when medicine administration is done manually (dispensing, ordering or administrating). To reduce the risks related to medication errors, automation of the pharmacy processes appears as an appropriately tool to solve this situation. In this paper, we have proposed a new mathematical model to optimize the processes related to unit-doses management and prescriptions preparation in a network of hospitals. To model the uncertainty associated with the demand of medicines, the concept of p-robustness is included; the concept of resilience is also considered to model the risk of centralized distribution processes.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"18 1","pages":"390-395"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87617171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560481
Xin Luo, Mengchu Zhou
Non-negativity is vital for latent factor models to preserve the important feature of most high-dimensional and sparse (HiDS) matrices, e.g., none of their entries is negative. With the consideration of non-negativity, the training process of a latent factor model should be specified to achieve constraints-incorporated learning schemes. However, such schemes are neither flexible nor extensible. This work investigates algorithms of inherently non-negative latent factor analysis, which separates non-negativity constraints from the training process. Based on a deep investigation into the learning objective of a non-negative latent factor model, we separate the desired latent factors from decision variables involved in the training process via a single-element-dependent mapping function that makes the output factors inherently non-negative. Then we theoretically prove that the resultant model is able to represent the original one effectively. As a result, we design a highly efficient algorithm to bring the Inherently Non-negative Latent Factor model into practice. Experimental results on three HiDS matrices from industrial recommender systems show that compared with state-of-the-art non-negative latent factor models, the proposed one is able to obtain advantage in prediction accuracy with comparable or higher computational efficiency. Moreover, such high performance is achieved through its unconstrained optimization process on the premise of fulfilling the non-negativity constraints. Hence, the proposed model is highly valuable for industrial applications required to handle HiDS matrices subject to non-negativity constraints.
{"title":"Unconstrained Non-negative Factorization of High-dimensional and Sparse Matrices in Recommender Systems","authors":"Xin Luo, Mengchu Zhou","doi":"10.1109/COASE.2018.8560481","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560481","url":null,"abstract":"Non-negativity is vital for latent factor models to preserve the important feature of most high-dimensional and sparse (HiDS) matrices, e.g., none of their entries is negative. With the consideration of non-negativity, the training process of a latent factor model should be specified to achieve constraints-incorporated learning schemes. However, such schemes are neither flexible nor extensible. This work investigates algorithms of inherently non-negative latent factor analysis, which separates non-negativity constraints from the training process. Based on a deep investigation into the learning objective of a non-negative latent factor model, we separate the desired latent factors from decision variables involved in the training process via a single-element-dependent mapping function that makes the output factors inherently non-negative. Then we theoretically prove that the resultant model is able to represent the original one effectively. As a result, we design a highly efficient algorithm to bring the Inherently Non-negative Latent Factor model into practice. Experimental results on three HiDS matrices from industrial recommender systems show that compared with state-of-the-art non-negative latent factor models, the proposed one is able to obtain advantage in prediction accuracy with comparable or higher computational efficiency. Moreover, such high performance is achieved through its unconstrained optimization process on the premise of fulfilling the non-negativity constraints. Hence, the proposed model is highly valuable for industrial applications required to handle HiDS matrices subject to non-negativity constraints.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"14 1","pages":"1406-1413"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87116926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Implementing intelligent manufacturing services on factory-wide edge devices connected with production equipment efficiently so that those manufacturing services are pluggable, plug-and-play, and manageable through the network is a challenging task and is highly beneficial for facilitating realizing a smart factory. This paper proposes a cloud-based pluggable manufacturing service scheme (called CPMSS) by leveraging cloud computing, edge computing, and RESTful Web Service to address this issue. By using a two-layer-RESTful-service mechanism, the manufacturing services can be built in the form of pluggable application module (PAM). The proposed CPMSS allows the engineers to deploy selected PAMs from the cloud to target edge devices efficiently and to run and manage the plugged PAMs remotely through the cloud platform using Web-based GUIs for supporting intelligent manufacturing activities on target production equipment. Thereby, CPMSS can facilitate fast and factory-wide deployment of intelligent manufacturing services on edge devices for supporting smart manufacturing. Finally, an industrial case study performing predictive maintenance (PdM) on PECVD equipment of a solar cell manufacturing factory is used to demonstrate the effectiveness of the CPMSS.
在工厂范围内的边缘设备上实现与生产设备连接的智能制造服务，使这些制造服务可插拔、即插即用，并通过网络进行管理，这是一项具有挑战性的任务，对实现智能工厂非常有益。本文提出了一种基于云的可插拔制造服务方案(CPMSS)，利用云计算、边缘计算和RESTful Web service来解决这一问题。通过使用两层restful服务机制，可以以可插拔应用程序模块(PAM)的形式构建制造服务。提出的CPMSS允许工程师将选定的PAMs从云有效地部署到目标边缘设备，并通过云平台使用基于web的gui远程运行和管理插入的PAMs，以支持目标生产设备上的智能制造活动。因此，CPMSS可以促进在边缘设备上快速和工厂范围内部署智能制造服务，以支持智能制造。最后，通过对某太阳能电池制造工厂的PECVD设备进行预测性维护(PdM)的工业案例研究，验证了CPMSS的有效性。
{"title":"A Cloud-based Pluggable Manufacturing Service Scheme for Smart Factory","authors":"Yu-Yang Liu, Min-Hsiung Hung, Yu-Chuan Lin, Chao-Chun Chen, Wei-Lun Gao, F. Cheng","doi":"10.1109/COASE.2018.8560401","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560401","url":null,"abstract":"Implementing intelligent manufacturing services on factory-wide edge devices connected with production equipment efficiently so that those manufacturing services are pluggable, plug-and-play, and manageable through the network is a challenging task and is highly beneficial for facilitating realizing a smart factory. This paper proposes a cloud-based pluggable manufacturing service scheme (called CPMSS) by leveraging cloud computing, edge computing, and RESTful Web Service to address this issue. By using a two-layer-RESTful-service mechanism, the manufacturing services can be built in the form of pluggable application module (PAM). The proposed CPMSS allows the engineers to deploy selected PAMs from the cloud to target edge devices efficiently and to run and manage the plugged PAMs remotely through the cloud platform using Web-based GUIs for supporting intelligent manufacturing activities on target production equipment. Thereby, CPMSS can facilitate fast and factory-wide deployment of intelligent manufacturing services on edge devices for supporting smart manufacturing. Finally, an industrial case study performing predictive maintenance (PdM) on PECVD equipment of a solar cell manufacturing factory is used to demonstrate the effectiveness of the CPMSS.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"51 1","pages":"1040-1045"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90058232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560603
Ping Yang, S. Hsu
In this paper we consider the Laplacian controllability problem of combining two special threshold graphs. We form this combination by connecting two identical and connected threshold graphs which have exactly one repeated degree. With appropriate selection of connecting vertices for combination we show how to use the minimum number of inputs to render the combined graph Laplacian controllable. Numerical examples are provided to demonstrate our work.
{"title":"On a class of multi-input laplacian controllable graphs","authors":"Ping Yang, S. Hsu","doi":"10.1109/COASE.2018.8560603","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560603","url":null,"abstract":"In this paper we consider the Laplacian controllability problem of combining two special threshold graphs. We form this combination by connecting two identical and connected threshold graphs which have exactly one repeated degree. With appropriate selection of connecting vertices for combination we show how to use the minimum number of inputs to render the combined graph Laplacian controllable. Numerical examples are provided to demonstrate our work.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"54 1","pages":"310-315"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86521644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560516
Tadeu K. Zubaran, M. Ritt
In this work we consider a job shop scheduling problem with the objective of minimizing the makespan. As in the standard job shop problem, the operations of each job have to be processed on different stages in a given order, but in the problem variant studied here each stage disposes of parallel machines. The number of parallel machines may vary from stage to stage, yet if all stages have a single machine we have the standard job shop problem. We propose a tabu search to solve this problem, which searches for good job-stage assignments, and combine it with an effective heuristic rule to derive a complete schedule from them.
{"title":"An effective tabu search for job shop scheduling with parallel machines","authors":"Tadeu K. Zubaran, M. Ritt","doi":"10.1109/COASE.2018.8560516","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560516","url":null,"abstract":"In this work we consider a job shop scheduling problem with the objective of minimizing the makespan. As in the standard job shop problem, the operations of each job have to be processed on different stages in a given order, but in the problem variant studied here each stage disposes of parallel machines. The number of parallel machines may vary from stage to stage, yet if all stages have a single machine we have the standard job shop problem. We propose a tabu search to solve this problem, which searches for good job-stage assignments, and combine it with an effective heuristic rule to derive a complete schedule from them.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"62 1","pages":"913-919"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81348210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560405
S. Scholz, A. Elkaseer, Tobias Muller, U. Gengenbach, V. Hagenmeyer
This paper presents an innovative approach to the development of a smart fully-digital manufacturing system based on a modular and reconfigurable production concept. In particular, multiple “plug and play” manufacturing modules, i.e. functional printing, laser processing and welding, in addition to a positioning control unit and quality inspection system, are exploited in an agile manufacturing platform combined with a knowledge-based framework, termed “3D-I”. This enables the production of tailored laminated parts, made up of stacks of functionalised layers of polymer films, with intricate 3D micro features. However, since no tool or mask making is needed, a medium to small lot-size and even one-off parts can be produced in a cost-effective manner. For the evaluation of the “3D-I” approach, a case study of micro-fluidic chips, exemplifying functional parts, are fabricated. The results prove the feasibility of the developed smart system to produce micro-devices with pre-defined specifications. In addition, the knowledge-based manufacturing system demonstrates its potential to offer profitable production scenarios of microdevices, with high flexibility and scalability, outside the area of mass production.
{"title":"Smart modular reconfigurable fully-digital manufacturing system with a knowledge-based framework: example of a fabrication of microfluidic chips","authors":"S. Scholz, A. Elkaseer, Tobias Muller, U. Gengenbach, V. Hagenmeyer","doi":"10.1109/COASE.2018.8560405","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560405","url":null,"abstract":"This paper presents an innovative approach to the development of a smart fully-digital manufacturing system based on a modular and reconfigurable production concept. In particular, multiple “plug and play” manufacturing modules, i.e. functional printing, laser processing and welding, in addition to a positioning control unit and quality inspection system, are exploited in an agile manufacturing platform combined with a knowledge-based framework, termed “3D-I”. This enables the production of tailored laminated parts, made up of stacks of functionalised layers of polymer films, with intricate 3D micro features. However, since no tool or mask making is needed, a medium to small lot-size and even one-off parts can be produced in a cost-effective manner. For the evaluation of the “3D-I” approach, a case study of micro-fluidic chips, exemplifying functional parts, are fabricated. The results prove the feasibility of the developed smart system to produce micro-devices with pre-defined specifications. In addition, the knowledge-based manufacturing system demonstrates its potential to offer profitable production scenarios of microdevices, with high flexibility and scalability, outside the area of mass production.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"67 1","pages":"1012-1017"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90768932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560499
A. Petitti, Donato Di Paola, R. Colella, A. Milella, E. Stella, Antonio Coratelli, D. Naso
The field of multi-robot systems is one of the main research topics in robotics, as robot networks offer great advantages in terms of reliability and efficiency in many application domains. This paper focuses on the problem of mutual localization and 3D cooperative environment mapping using a heterogeneous multi-robot team. The proposed algorithm relies on the exchange of local maps and is totally distributed; no assumption on a common reference frame is done. The developed strategy is robust to failures, scalable with the number of the robots in the network, and has been validated through an experimental campaign.
{"title":"A Distributed Map Building Approach for Mobile Robotic Networks","authors":"A. Petitti, Donato Di Paola, R. Colella, A. Milella, E. Stella, Antonio Coratelli, D. Naso","doi":"10.1109/COASE.2018.8560499","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560499","url":null,"abstract":"The field of multi-robot systems is one of the main research topics in robotics, as robot networks offer great advantages in terms of reliability and efficiency in many application domains. This paper focuses on the problem of mutual localization and 3D cooperative environment mapping using a heterogeneous multi-robot team. The proposed algorithm relies on the exchange of local maps and is totally distributed; no assumption on a common reference frame is done. The developed strategy is robust to failures, scalable with the number of the robots in the network, and has been validated through an experimental campaign.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"109 5 1","pages":"116-121"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89737139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/COASE.2018.8560523
Florian Pfitzer, Julien Provost, Carina Mieth, Wolfgang Liertz
Unpredictable incoming orders and the required nesting process highly complicate production planning and scheduling in sheet metal job shop environments and cause extremely high lead times as well as intermediate stocks. For this, numerous advanced planning and scheduling (APS) algorithms exist, aiming at creating a globally optimized production schedule. Due to the complexity of the multi-objective optimization and the large amount of unforeseen shop-floor events, effective and applicable solutions have not been presented so far. This work introduces an event-driven rescheduling concept based on lean principles leading to a high responsiveness of the production process to any kind of deviation. The achieved, significantly smaller buffer occupancies enable shorter lead times and improved delivery time estimations. Excellent performance results of the rescheduling concept are shown in different simulation experiments. The presented concept can easily be implemented in any kind of sheet metal job shop and its respective IT infrastructure.
{"title":"Event-Driven Production Rescheduling in Job Shop Environments","authors":"Florian Pfitzer, Julien Provost, Carina Mieth, Wolfgang Liertz","doi":"10.1109/COASE.2018.8560523","DOIUrl":"https://doi.org/10.1109/COASE.2018.8560523","url":null,"abstract":"Unpredictable incoming orders and the required nesting process highly complicate production planning and scheduling in sheet metal job shop environments and cause extremely high lead times as well as intermediate stocks. For this, numerous advanced planning and scheduling (APS) algorithms exist, aiming at creating a globally optimized production schedule. Due to the complexity of the multi-objective optimization and the large amount of unforeseen shop-floor events, effective and applicable solutions have not been presented so far. This work introduces an event-driven rescheduling concept based on lean principles leading to a high responsiveness of the production process to any kind of deviation. The achieved, significantly smaller buffer occupancies enable shorter lead times and improved delivery time estimations. Excellent performance results of the rescheduling concept are shown in different simulation experiments. The presented concept can easily be implemented in any kind of sheet metal job shop and its respective IT infrastructure.","PeriodicalId":6518,"journal":{"name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","volume":"83 1","pages":"939-944"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84030268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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