A multi-time scales model and control for hybrid stochastic production systems with quadratic cost

Im Rahmen der stufenweisen Umsetzung von Industrie 4.0 erreicht die Vernetzung und Digitalisierung die gesamte Produktion. Den physischen Produktionsprozess nicht nur cyber-physisch zu begleiten, sondern durch eine virtuelle, digitale Kopie zu erfassen und zu optimieren, stellt ein enormes Potenzial für die Produktionssystemplanung und -steuerung dar. Zudem erlauben digitale Modelle die Anwendung intelligenter Produktionssteuerungsverfahren und leisten damit einen Beitrag zur Verbreitung optimierender adaptiver Systeme.   In the wake of implementing Industrie 4.0 both integration and digitalization affect the entire production. Physical production systems offer enormous potential for production planning and control through virtual, digital copies and their optimization, well beyond purely cyber-physical production system extensions. Furthermore, digital models enable the application of intelligent production control and hence contribute to the dissemination of adaptively optimizing systems.

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New Software Tool for Modeling and Control of Discrete-Event and Hybrid Systems Using Timed Interpreted Petri Nets

Applied Sciences ◽

10.3390/app10155027 ◽

2020 ◽

Vol 10 (15) ◽

pp. 5027 ◽

Cited By ~ 1

Author(s):

Erik Kučera ◽

Oto Haffner ◽

Peter Drahoš ◽

Ján Cigánek ◽

Roman Leskovský ◽

...

Keyword(s):

Petri Nets ◽

Hybrid Systems ◽

Industry 4.0 ◽

Discrete Event Systems ◽

Production Systems ◽

Discrete Event ◽

Software Tool ◽

Modeling And Control ◽

Event Systems ◽

And Control

For the development of modern complex production processes in Industry 4.0, it is appropriate to effectively use advanced mathematical models based on Petri nets. Due to their versatility in modeling discrete-event systems, Petri nets are an important support in creating new platforms for digitized production systems. The main aim of the proposed article is to design a new software tool for modeling and control of discrete-event and hybrid systems using Arduino and similar microcontrollers. To accomplish these tasks, a new tool called PN2ARDUINO based on Petri nets is proposed able to communicate with the microcontroller. Communication with the microcontroller is based on the modified Firmata protocol hence, the control algorithm can be implemented on all microcontrollers that support this type of protocol. The developed software tool was successfully verified in control of laboratory systems. In addition, it can be used for education and research purposes as it offers a graphical environment for designing control algorithms for hybrid and mainly discrete-event systems. The proposed software tool can improve education and practice in cyber-physical systems (Industry 4.0).

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The effect of preconditioning on production and antibiotic use in a South African beef feedlot

Animal Production Science ◽

10.1071/an19495 ◽

2020 ◽

Vol 60 (15) ◽

pp. 1822

Author(s):

A. H. R. Hentzen ◽

P. N. Thompson ◽

D. E. Holm

Keyword(s):

South African ◽

Antibiotic Treatment ◽

Cox Regression ◽

Production Systems ◽

Average Daily Gain ◽

Antibiotic Use ◽

Lung Lesion ◽

Lower Proportion ◽

Carcass Weight ◽

And Control

Context There is pressure on production veterinarians to reduce the use of antibiotics in intensive beef production systems. Aims The present study investigated whether preconditioning – the process whereby weaned calves destined for the feedlot are prepared over a period of time – reduced antibiotic treatment events, and improved health and production of calves in a South African feedlot. Methods Preconditioned calves (n = 301) and control calves (n = 332) were sourced from the same origin on two occasions, and arrived at the feedlot on the same day. Bovine respiratory disease (BRD) was defined as the ‘pulling’ of clinically sick calves from feedlot pens, followed by the standard protocol for treatment of BRD (including antibiotic treatment). Outcome variables related to health were BRD overall incidence (pulling), BRD re-pulling and lung lesion scores. Production outcome variables measured were carcass weight, carcass average daily gain (ADG) and days on feed (DOF). Initial carcass weight was estimated from shrunk liveweight in order to estimate the effect of preconditioning on carcass gain, the most economically relevant outcome. Statistical analyses were done using multiple linear, logistic and Cox regression. Predictor variables were preconditioning vs control, gender, starting weight, DOF, pulling for BRD and carcass ADG. Key results A lower proportion of preconditioned calves were pulled and a lower proportion of pulled calves were re-pulled for BRD compared with control calves (8 vs 17% and 8 vs 16%, respectively, P < 0.01). A higher proportion of preconditioned calves compared with control calves were market ready at 90 DOF (89 vs 67%, P < 0.01). In the multivariable models preconditioning was associated with a 200 g/d increase in carcass growth rate (P < 0.01) and with a 17.7 kg increase in overall carcass gain (P < 0.01) after adjusting for gender and DOF. Conclusions Preconditioning reduced the incidence and severity of BRD and feedlot standing time and improved production of calves in South African feedlots. Implications Preconditioning has the potential to add value to the beef feedlot by reducing the formation of antimicrobial resistance while improving the profitability of the feedlot.

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Production benefits of breeding for worm resistance in Merino sheep

Animal Production Science ◽

10.1071/an19368 ◽

2020 ◽

Vol 60 (13) ◽

pp. 1643

Author(s):

J. C. Greeff ◽

L. J. E. Karlsson

Keyword(s):

Mixed Model ◽

Production Systems ◽

Control Line ◽

Cross Contamination ◽

Resistant Line ◽

Merino Sheep ◽

Associated Production ◽

Sheep Production ◽

And Control ◽

Production Losses

Context Production losses, due to worms and anthelmintic costs to control the infection, can affect the profitability of sheep production systems. Aims This study was carried out to quantify the production benefits of worm-resistant sheep. Methods Genetically worm-resistant and unselected control Merino rams were mated annually to 150 ewes in each of the Resistant and Control lines respectively over an 8-year period. All ewes and their progeny were managed in small replicated paddocks to prevent any cross-contamination between paddocks and groups. Fertility, growth, wool production, wool quality and worm resistance were measured on the ewes and their progeny. The data were analysed using mixed model methodology. Key results The progeny of the Resistant sires were on average 21–25% more worm resistant than the progeny of the Control sires. No significant differences were recorded in reproduction between mature ewes of the Resistant and Control lines, or in the survival rate of their lambs. Resistant line progeny were on average 1.6 kg heavier at weaning, received 15–17% less drenching during the experiment and produced on average 0.3 μm finer wool at hogget shearing than the Control line progeny. Conclusions It is concluded that the Resistant line coped better with a worm challenge and that this resulted in increased production. Implications This study shows that apart from improved worm resistance, there are associated production benefits in breeding for worm resistance.

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Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications

Sustainability ◽

10.3390/su12093791 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3791 ◽

Cited By ~ 6

Author(s):

Olumide Emmanuel Oluyisola ◽

Fabio Sgarbossa ◽

Jan Ola Strandhagen

Keyword(s):

Production Planning ◽

Production Management ◽

Production Systems ◽

Production Planning And Control ◽

Market Uncertainty ◽

Planning And Control ◽

Make To Order ◽

Smart Technologies ◽

And Control ◽

Process Strategy

Many companies are struggling to manage their production systems due to increasing market uncertainty. While emerging ‘smart’ technologies such as the internet of things, machine learning, and cloud computing have been touted as having the potential to transform production management, the realities of their adoption and use have been much more challenging than anticipated. In this paper, we explore these challenges and present a conceptual model, a use-case matrix and a product–process framework for a smart production planning and control (smart PPC) system and illustrate the use of these artefacts through four case companies. The presented model adopts an incremental approach that companies with limited resources could employ in improving their PPC process in the context of industry 4.0 and sustainability. The results reveal that while make-to-order companies are more likely to derive greater benefits from a smart product strategy, make-to-stock companies are more likely to derive the most benefit from pursuing a smart process strategy, and consequently a smart PPC solution.

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