Reliability of a production system with intersectional lines

Abstract

This article addresses reliability evaluation for a production system with intersectional lines and multiple reworking actions, where the reliability is the probability of demand satisfaction. First, the production system is constructed as a capacitated-flow production network by the revised graphical transformation and decomposition techniques. Capacity analysis is implemented to determine the input flow of each workstation subsequently. Second, two algorithms, including a general algorithm, are proposed to generate all minimal capacity vectors that workstations should provide to satisfy demand. The reliability is derived in terms of such vectors accordingly. A real-world case of printed circuit board production system is utilized to demonstrate the performance evaluation procedure.

Assessment methods of production processes reliability – state of the art

“…wskaźnik wydajności zapewniający informacje o zdolności operacyjnej systemu (np. prace [32,33]), wskaźnik produktywności lub jakości (np. prace [9,15]), miara oceny czasu produkcji (np.…”

Probability of demand satisfaction for hybrid production networks using a topological technique

“…The deburring workstation a 3 comprising four machines has five capacity levels, say {0, 2500, 5000, 7500, 10,000}. 13 The lowest level 0 corresponds to complete malfunction of all machines, while 10,000 is the highest level, at which all machines operate successfully. The capacity distribution is in the form of probability mass function, indicating that each workstation can provide a certain capacity level with a corresponding probability.…”

“…9–11 Therefore, how repair affects the amount of output products is an important issue to consider. More recently, Lin and Chang 12,13 proposed an HPN model with only one line to measure the performance of a production network taking single repair into consideration. However, their works lack applicability to multiple lines in most real-life cases.…”

A scenario-based robust optimization approach for batch processing scheduling

“…Semiconductor burn-in operations; environmental stress-screening (ESS) chambers; chemical, food, and mineral processing; pharmaceutical and construction materials industries; and so on are examples of BPM. 1 This research is motivated by a BPM real-world application in a printed circuit board (PCB) 2 assembly line originally presented by Damodaran and Srihari. 3 Figure 1 shows a BPM where assemblies from in circuit testing (ICT) arrive at the ESS chambers; they should be gathered in batches and the batches should be scheduled on the chambers.…”