Adaptive Production Scheduling and Control in One-Of-A-Kind Production

Li, Wei; Tu, Yiliu

doi:10.5772/26771

Cited by 4 publications

(8 citation statements)

References 47 publications

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“…From our previous research on TFS problems, we found that the lever concept is suitable for flow shop production [24], which means that IDLE (or DELAY) in an earlier stage is worse for min(C max ) objective than in a later stage. Consider a lever where force F takes effect and causes a torque of F Â L, where F is the unit of force and L is the length of force arm.…”

Section: The Lever Conceptmentioning

confidence: 98%

“…The system, as illustrated in Fig. 5, consists of our SS heuristic and a simulation model that is called temporized hierarchical object-oriented coloured Petri nets with changeable structure (THOCPN-CS) [25]. High customization and dynamic uncertainties in OKP demand for a great effort on a simulation model.…”

Section: A Close-loop Production Scheduling and Control Structurementioning

confidence: 99%

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An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

Nault

Xue

et al. 2011

Computers & Operations Research

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Section: The Lever Conceptmentioning

confidence: 98%

Section: A Close-loop Production Scheduling and Control Structurementioning

confidence: 99%

An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

Nault

Xue

et al. 2011

Computers & Operations Research

Self Cite

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“…As an example, we present a typical integrated DDM problem based on a case study from [9] as follows 3 . As shown in Figure 1, a firm manufactures windows and doors for home builders as well as individual home owners.…”

Section: Figure 1 the Ddm Problem Setting In A Windows And Doors Companymentioning

confidence: 99%

“…As in most make-to-order cases, customers and the firm will expect repeated trade, it is appropriate to focus on market efficiency in our DDM formulation. 3 In [9] W. Li, X. Luo, Y. Tu, and D. Xue, " Adaptive production scheduling for one-of-a-kind production with mass customization," Transactions of the North American Manufacturing Research Institution of SME, vol. 35, pp.…”

Section: Figure 1 the Ddm Problem Setting In A Windows And Doors Companymentioning

confidence: 99%

“…1) Round #1: the agents use the reserve prices for their jobs as the bidding prices. Agent1 uses a simplified XOR-C-Bid and bids on due date 10:00, 〈 〉, which requires the time interval (8,10], and Agent2 bids on due date 9:00, 〈 〉, which requires the time interval (8,9], because, given the current bidding prices, these two due dates maximize agents' utilities. The auctioneer includes only Agent1 into the provisional schedule because the two bids cannot coexist in a schedule and Agent1's bid maximizes auctioneer's revenue.…”

Section: An Examplementioning

confidence: 99%

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Due-Date Management Through Iterative Bidding

Wang

Ghenniwa

et al. 2011

IEEE Trans. Syst., Man, Cybern. A

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This paper proposes an iterative bidding framework for integrated due date management decision making. We focus on a type of make-to-order environment, in which a firm needs to quote due dates and prices and to schedule the production of a variety of job orders required by a large group of customers. In most cases, customers prefer shorter due dates. However, given limited production capacity and various cost constraints, the firm has to balance the attractiveness of their due date quotations and the reliability in terms of scheduling and delivering accepted job orders. The key issue here is how to integrate due date management decisions such that high quality solutions which benefit both the firm and the customers can be obtained. We study the integrated due date management in an economic setting where customers are modeled as self-interested agents and the objective of the firm is to maximize social welfare.We present an iterative bidding framework as a decentralized decision support tool which enables the integration of key due date management decisions. Effective solutions are achieved through the automated negotiation between the firm and its customers. We provide analytical results on the application of the proposed framework to two special cases of the integrated due date management. We also evaluate the performance of the framework on general due date management problems through a computational study. the terms of the transactions, in particular, on the price and the due date. If the price or the due date quoted by the firm is too high compared to what the customer is willing to accept, the customer may choose not to place the order. Alternatively, if the price the customer is willing to pay is low or the due date requested is too short to make it a profitable transaction for the firm, the firm might decide not to accept the order. As the DDM decisions are tightly coupled, it is desirable to model the interrelations among them and consider them simultaneously. However, given the complexities of these decisions, in practice, they are often made sequentially. The way that a firm makes DDM decisions is reflected by the time-based competition strategy it adopts.There are three time-based competition strategies used by firms [3], (1) quick service with minimal wait; (2) "uniform" short lead time 1 guarantee; (3) due date quotation. The first strategy does not involve order acceptance and due date quotation decisions. The focus here is how to schedule job orders such that they can be served as fast as possible. The second strategy promises a uniform lead time guarantee to all customers. Although, a firm can influence the demand rate by adjusting the length of the guaranteed lead time, there is no direct integration between the decisions of order acceptance and scheduling. In fact, under this strategy, there is a risk that demand may exceed the firms' capacity to respond. Uniform lead time guarantee is widely adopted in the service and make-to-order manufacturing sectors [3,4]. While the strategy may be easy to ...

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Adaptive planning and control in cyber-physical production systems

Nikolakis¹,

Νικολάκης²

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Αντικείμενο αυτής της εργασίας είναι η μελέτη των συστημάτων παραγωγής ως κυβερνο-φυσικών συστημάτων επικεντρώνοντας στον προσαρμοστικό σχεδιασμό/προγραμματισμό κι έλεγχό τους. Απώτερος σκοπός είναι η δυνατότητα αναδιαμόρφωσής τους για την αύξηση της αυτοματοποίησης και της ευελιξίας στις συνθήκες εργασίας καθώς και σε μεταβαλλόμενες απαιτήσεις παραγωγής. Για αυτό το λόγο, μέθοδοι, που μεταφράζονται σε διαφορετικά επίπεδα της πυραμίδας αυτοματισμού, μέσω της αρχιτεκτονικής 5C για κυβερνο-φυσικά συστήματα, έχουν διερευνηθεί κι ενσωματωθεί σε υπό-μελέτη κυβερνο-φυσικά συστήματα. Πρώτον, μελετάται ο δυναμικός έλεγχος κλειστού βρόχου ενός κυβερνο-φυσικού συστήματος σχετικά με την ασφαλή συνεργασία ανθρώπου-ρομπότ σε ένα περιβάλλον εργασίας. Μια αρχική εφαρμογή αξιολογείται σε μια συγκεκριμένη περίπτωση χρήσης και συγκρίνονται τα αποτελέσματά της σχετικά με τη χρήση ενός ή περισσοτέρων αισθητήρων. Η σύγκριση πραγματοποιείται με βάση τον χρόνο απόκρισης του συστήματος για την ανίχνευση της ανθρώπινης παρουσίας εντός μιας προκαθορισμένης ζώνης ασφαλείας. Στη συνέχεια, εξετάζονται οι χειρωνακτικές εργασίες συναρμολόγησης, συζητείται ο προσαρμοστικός προγραμματισμός και ο επαναπροσδιορισμός του σταθμού συναρμολόγησης. Η εφαρμογή ψηφιακού διδύμου παρουσιάζεται για να κλείσει ψηφιακά το βρόχο μεταξύ φυσικού και εικονικού συστήματος, επιτρέποντας έτσι μια αποτελεσματική, από πλευράς κόστους, βελτίωση του σχεδιασμού, της ανάθεσης καθώς και ολόκληρου του κύκλου ζωής των διαδικασιών παραγωγής με βάση τον άνθρωπο. Μια μελέτη περίπτωσης σε χώρο αποθήκης καταδεικνύει τη σκοπιμότητα και αποτελεσματικότητα της προτεινόμενης προσέγγισης. Επίσης, στο πλαίσιο της τρίτης μελέτης, συζητείται ένα ολιστικό πλαίσιο για τα αναδιαμορφώσιμα κυβερνο-φυσικά συστήματα παραγωγής, που υλοποιούνται από τις τεχνολογίες των υπηρεσιών πακέτων λογισμικού (containers). Η παρουσιαζόμενη προσέγγιση ενισχύει την ευελιξία σε ένα κυβερνο-φυσικό σύστημα παραγωγής μέσω της δυναμικής αναδιάρθρωσης του συστήματος αυτοματισμού και του χρονοδιαγράμματος παραγωγής, με βάση τα συμβάντα. Η προτεινόμενη λύση υλοποιήθηκε σε μια εφαρμογή λογισμικού και εφαρμόστηκε σε ένα κυβερνο-φυσικό σύστημα παραγωγής μικρής κλίμακας που προέρχεται από την αυτοκινητοβιομηχανία. Τέλος, η συμβολή των στρωμάτων ολοκλήρωσης της αρχιτεκτονικής 5C για την υλοποίηση και την ανάπτυξη λειτουργιών CPPS, που μετατρέπει τις συμβατικές διαδικασίες παραγωγής σε έξυπνες, έχει αξιολογηθεί μέσω ενός συνόλου δεικτών επιπέδου ευελιξίας μέσω του αυτοματισμού και δεικτών χαρακτηριστικών των κυβερνο-φυσικών συστημάτων παραγωγής.

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Adaptive Production Scheduling and Control in One-Of-A-Kind Production

Cited by 4 publications

References 47 publications

An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

Due-Date Management Through Iterative Bidding

Adaptive planning and control in cyber-physical production systems

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