Ontology-based expert system for process supervision

Musulin, Estanislao; Roda, Fernando; Basualdo, Marta

doi:10.1016/b978-0-444-59520-1.50050-6

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…Issues with scheduling caused by machines being unavailable, broken, or undergoing maintenance have been reported previously [19], [20]. Using information about plant activities and variable conditions, Musulin et al [21] address disruption and risk assessment with reactive, dynamic, online methods. In [4], [22], and [23], researchers examine the transition (transient) of buffer level from a probability distribution to a stationary distribution.…”

Section: Literature Reviewmentioning

confidence: 99%

Implementing the Concept of Alarm Flexibility During Production

Haq¹,

Khan²,

Khan³

2022

PakJET

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An interruption at a workstation is a major cause of production downtime, which has negative effects on performance, cost, consumer-centric value, and efficiency. Blockage and starvation brought on by broken workstations have a domino effect on the entire production line. To allocate resources effectively and minimize downtime, it is crucial to thoroughly analyze each disruption's effects. Quantitative analysis of disruption at a single workstation and its effects on neighbouring workstations are performed in the work presented. Faulty workstations have an additional threshold value added to the Alarm Trip Point (ATP), depending on their current state. This one significantly improves upon downtime mitigation and batch rejection reduction compared to previous approaches. A more general model based on multiple workstations has been developed by expanding the analysis for a single workstation. The proposed work is demonstrated in an experimental case study, an Asphalt-Processing Plant. It is applied in addition to developing a theoretical model to reduce downtime, multiple starts and stops, and numerous rejections. The proposed method reduces start-stop events by 60%, reducing rejections and downtime while increasing consumer-centric value and efficiency.

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Section: Literature Reviewmentioning

confidence: 99%

Implementing the Concept of Alarm Flexibility During Production

Haq¹,

Khan²,

Khan³

2022

PakJET

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“…Disruption management increases productivity and production capacity and reduces waste such as defects in the production system (Zhu, Li, & Mishra, 2023). Musulin et al (2012), emphasized the need for a dynamic and reactive, online approach that meets standards and provides accurate information concerning plant activities and changing conditions. Fernández 2015), researched the monitoring approach in 3 criteria, namely predictive ability (predictive or reactive), sources of observed events (resources or orders), and generalization of processes that take into account the ability to apply different monitoring models possessed by the various application domain.…”

Section: Introductionmentioning

confidence: 99%

Cost Optimization in Disruption Conditions: A Case Study in Small Medium Enterprise

Tengtarto¹,

Singgih²,

Siswanto³

2023

J. Professional Business Review

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Purpose: The objective of this study was to design a cost optimization model that offers production improvement for SMEs. Theoretical framework: Several studies related to production system disruption management have been conducted, with the majority focusing on large companies. However, small and medium enterprises (SMEs) have limitations compared to large companies. Repairability is considered for cost optimization. Design/methodology/approach: This research designed a cost optimization model that offers production improvement with repairability process for SME. Findings: There is a need for repairability given the disruption caused by defective products in SMEs. There is a clear difference in total profit between the current state without repairability and proposed conditions with repairability. SMEs suffer massive losses in the absence of repairs, assuming they do not consider repairing defective products with a production defect rate of approximately 15%. The current state produces many downgraded products. However, repairability still needs to be improved to increase profits. Research, Practical & Social implications: The study implied that there is a need to consider repairability for product defects at SMEs, especially those with a 15% product defect rate. The use of the proposed model optimizes profit and is designed to increase production capacity based on product improvements. Repairability was considered in this research, considering that SMEs are more susceptible to disruptions compared to large companies. Originality/value: The novelty of this paper is adding process repairability to the cost optimization model for SMEs in the textile sector, then considering the product downgrade under the conditions in SMEs.

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