Integrated prognostics, maintenance and life-extending control of continuous-time production processes

1999 ◽  
pp. 136-169
Author(s):  
Asok Ray ◽  
Shashi Phoha
Keyword(s):  
Continuous Time ◽  
Time Production ◽  
Production Processes ◽  
Life Extending Control

scholarly journals Handling Discrete Demand in Continuous-Time Production Planning

1998 ◽  
Vol 31 (15) ◽  
pp. 463-468
Author(s):  
Stéphane Dauzère-Pérès ◽  
Marc Sevaux
Keyword(s):  
Production Planning ◽  
Continuous Time ◽  
Time Production

Nonlinear Control in Continuous-Time Production Systems and in Economics

2020 ◽  
Author(s):  
Gerasimos Rigatos ◽  
Pierluigi Siano ◽  
Taniya Ghosh
Keyword(s):  
Nonlinear Control ◽  
Continuous Time ◽  
Production Systems ◽  
Time Production

Models and solving procedures for continuous-time production planning

2000 ◽  
Vol 32 (2) ◽  
pp. 93-103 ◽  
Author(s):  
STEPHANE DAUZERE-PERES ◽  
STANLEY B. GERSHWIN ◽  
MARC SEVAUX
Keyword(s):  
Production Planning ◽  
Continuous Time ◽  
Time Production

Simulating Continuous Time Production Flows in Food Industry by Means of Discrete Event Simulation

2015 ◽  
Vol 11 (1) ◽  
pp. 139-150 ◽  
Author(s):  
Fabio Bursi ◽  
Andrea Ferrara ◽  
Andrea Grassi ◽  
Chiara Ronzoni
Keyword(s):  
Continuous Time ◽  
High Speed ◽  
Discrete Event ◽  
System Specification ◽  
Production Processes ◽  
Beverage Industry ◽  
Food And Beverage ◽  
Flowing Material ◽  
Devs Formalism ◽  
Over Time

Abstract The paper presents a new framework for carrying out simulations of continuous-time stochastic processes by exploiting a discrete event approach. The application scope of this work mainly refers to industrial production processes executed on a continuous flow of material (e.g. food and beverage industry) as well as production processes working on discrete units but characterized by a high speed flow (e.g. automated packaging lines). The proposed model, developed adopting the Discrete EVent system Specification (DEVS) formalism, defines a single generalized base unit able to represent, by means of an event scheme generated by state changes, the base behaviors needed for the modeling of a generic manufacturing unit, that is, (i) breakdowns and repairs, (ii) speed and accumulation, and (iii) throughput time. Moreover, the possibility to keep trace of additional measures of parameters related to the process and the flowing material (i.e. temperature, concentration of pollutant, and so on) is also considered. Since these parameters can change over time in a continuous manner, a specific discretization approach has been introduced to avoid the need to integrate parameter variation functions over time.

Heavy Tails of Discounted Aggregate Claims in the Continuous-Time Renewal Model

2007 ◽  
Vol 44 (02) ◽  
pp. 285-294 ◽  
Author(s):  
Qihe Tang
Keyword(s):  
Asymptotic Formula ◽  
Continuous Time ◽  
Heavy Tails ◽  
Tail Behavior ◽  
Renewal Model ◽  
Discounted Aggregate Claims ◽  
Aggregate Claims ◽  
Tail Asymptotic

We study the tail behavior of discounted aggregate claims in a continuous-time renewal model. For the case of Pareto-type claims, we establish a tail asymptotic formula, which holds uniformly in time.

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