Using process-mining for understating the emergence of self-organizing manufacturing systems.

Big Data-Driven Assessment of Proposals to Improve Enterprise Flexibility Through Control Options Untested in Practice

“…but do not provide exhaustive commentary on how data processing can yield useful solutions. By contrast, while Khodabandelou et al (2013) and Jimenez et al (2018) discuss extracting information from data, this information does not benefit flexibility improvement.…”

“…For instance, Wang et al (2015) mention that the CPS technology allows for new ways of applying big data in the future, which is of great interest from the risk and cost analysis point of view. Whereas according to Jimenez et al (2018), when it comes to control system synthesis, there has been no detailed investigation into the issues of process mining. This might be happening because data mining has not really been focusing on process operations.…”

“…The process mining algorithms include: inference methods; a-algorithm; directed acyclic graphs; inductive workflow acquisition; hierarchical clustering; genetic algorithm; heuristic algorithm; petrify algorithm; and colored Petri nets. Process mining can be used for various tasks, such as (Jimenez et al, 2018;Khodabandelou et al, 2013):…”

“…The second group of theories also includes studies by Khodabandelou et al (2013) and Jimenez et al (2018), which do not create a single system mechanism integrated with Marketing Capabilities and are not focused on planning and increasing internal flexibility. Improvement is based on selecting the best control solutions from among those that have already been tested previously.…”

Indoor Positioning Systems Can Revolutionise Digital Lean

“…Lean management (LM) is a well-known concept that is widely accepted in manufacturing industries due to its effectiveness in cutting waste and improving operation performance [2][3][4][5]. The tools of Industry 4.0 that advance LM to the next level include simulation and optimization [6,7], process mining [8][9][10], data mining [11][12][13][14], data analytics [15,16], big data analysis [17,18], digital twins [19][20][21][22], machine learning [23,24], virtual reality [25][26][27][28] and cyber-physical systems (CPSs) [17,[29][30][31]]. An integrative model for LM and Industry 4.0 was studied in [32], which resulted in a flexible and reconfigurable manufacturing system.…”