38,372 research outputs found
Realising the open virtual commissioning of modular automation systems
To address the challenges in the automotive industry posed by the need to rapidly manufacture more
product variants, and the resultant need for more adaptable production systems, radical changes are
now required in the way in which such systems are developed and implemented. In this context, two
enabling approaches for achieving more agile manufacturing, namely modular automation systems
and virtual commissioning, are briefly reviewed in this contribution. Ongoing research conducted at
Loughborough University which aims to provide a modular approach to automation systems design
coupled with a virtual engineering toolset for the (re)configuration of such manufacturing
automation systems is reported. The problems faced in the virtual commissioning of modular
automation systems are outlined. AutomationML - an emerging neutral data format which has
potential to address integration problems is discussed. The paper proposes and illustrates a
collaborative framework in which AutomationML is adopted for the data exchange and data
representation of related models to enable efficient open virtual prototype construction and virtual
commissioning of modular automation systems. A case study is provided to show how to create the
data model based on AutomationML for describing a modular automation system
Scheduling of non-repetitive lean manufacturing systems under uncertainty using intelligent agent simulation
World-class manufacturing paradigms emerge from specific types of manufacturing systems with which they remain associated until they are obsolete. Since its introduction the lean paradigm is almost exclusively implemented in repetitive manufacturing systems employing flow-shop layout configurations. Due to its inherent complexity and combinatorial nature, scheduling is one application domain whereby the implementation of manufacturing philosophies and best practices is particularly challenging. The study of the limited reported attempts to extend leanness into the scheduling of non-repetitive manufacturing systems with functional shop-floor configurations confirms that these works have adopted a similar approach which aims to transform the system mainly through reconfiguration in order to increase the degree of manufacturing repetitiveness and thus facilitate the adoption of leanness. This research proposes the use of leading edge intelligent agent simulation to extend the lean principles and techniques to the scheduling of non-repetitive production environments with functional layouts and no prior reconfiguration of any form. The simulated system is a dynamic job-shop with stochastic order arrivals and processing times operating under a variety of dispatching rules. The modelled job-shop is subject to uncertainty expressed in the form of high priority orders unexpectedly arriving at the system, order cancellations and machine breakdowns. The effect of the various forms of the stochastic disruptions considered in this study on system performance prior and post the introduction of leanness is analysed in terms of a number of time, due date and work-in-progress related performance metrics
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling
Copyright @ 2001 Elsevier Science LtdA new adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving the feasible solution. Two heuristics are presented, which can be combined with the neural network. One heuristic is used to accelerate the solving process of the neural network and guarantee its convergence, the other heuristic is used to obtain non-delay schedules from the feasible solutions gained by the neural network. Computer simulations have shown that the proposed hybrid approach is of high speed and efficiency. The strategy for solving practical job-shop scheduling problems is provided.This work is supported by the National Nature Science Foundation (No. 69684005)
and National High -Tech Program of P. R. China (No. 863-511-9609-003)
Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling
Copyright @ 2000 IEEEThis paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several
heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve
the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed
neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.This work was supported by the Chinese National Natural Science Foundation under Grant 69684005 and the Chinese National High-Tech Program under Grant 863-511-9609-003, the EPSRC under Grant GR/L81468
An O(nlogn) algorithm for the two-machine flow shop problem with controllable machine speeds
Production Planning;Scheduling;produktieleer/ produktieplanning
Pembangunan Modul Pengajaran Kendiri (MPK) keusahawanan dalam topik isu keusahawanan bagi pelajar diploma di politeknik
Terdapat pelbagai kaedah pembelajaran yang telah diperkenalkan termasuklah
kaedah pembelajaran yang menggunakan pendekatan pembelajaran bermodul secara
kendiri. Kajian ini adalah bertujuan untuk mengkaji kesesuaian Modul Pengajaran
Kendiri Keusahawanan dalam topik Isu Keusahawanan yang telah dihasilkan bagi
pelajar yang mengikuti pengajian Diploma di Jabatan Perdagangan Politeknik. Antara
aspek yang dikaji ialah untuk menilai sama ada rekabentuk modul yang dihasilkan dapat
memenuhi ciri-ciri modul yang baik, MPK yang dihasilkan dapat membantu mencapai
objektif pembelajaran, MPK ini bersifat mesra pengguna dan MPK yang dihasilkan
membantu pensyarah menyampaikan pengajarannya dengan lebih berkesan. Kajian ini
dilakukan ke atas 110 orang pelajar semester en am yang mengikuti pengajian diploma
dan 4 orang pensyarah yang mengajar subjek Keusahawanan di Jabatan Perdagangan
Politeknik Sultan Salahuddin Abdul Aziz Shah, Selangor. Kaedah analisa data yang
digunakan dalam kajian ini ialah skor min dan peratus. Hasil daripada kajian ini
menunjukkan bahawa rekabentuk modul yang dihasilkan memenuhi ciri-ciri modul
yang baik, MPK ini membantu untuk mencapai objektif pembelajaran, MPK ini
bersifat mesra pengguna dan MPK yang dihasilkan dapat membantu pensyarah
menyampaikan pengajarannya dengan lebih berkesan. Ini bermakna secara
keseluruhannya, hasil kajian menunjukkan bahawa modul yang dihasilkan oleh pengkaji
adalah sesuai digunakan oleh pelajar-pelajar semester enam yang mengikuti pengajian
diploma di Jabatan Perdagangan peringkat politeknik. Seterusnya, beberapa pandangan
telah dikemukakan bagi meningkatkan rnutu dan kualiti MPK yang dihasilkan. Semoga
kajian ini dapat memberi manfaat kepada mereka yang terlibat dalam bidang
pendidikan
A generic method for energy-efficient and energy-cost-effective production at the unit process level
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