A Systematic Simulation-Based Multi-Criteria Decision-Making Approach for the Evaluation of Semi–Fully Flexible Machine System Process Parameters

Current manufacturing system health management is of prime importance due to the emergence of recent cost-effective and -efficient prognostics and diagnostics capabilities. This paper investigates the most used performance measures viz. Throughput Rate, Throughput Time, System Use, Availability, Average Stay Time, and Maximum Stay Time as alternatives that are responsible for the diagnostics of manufacturing systems during real-time disruptions. We have considered four different configurations as criteria on which to test with the proposed integrated MCDM (Multi-Criteria Decision-Making)-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)-based simulation approach. The main objective of this proposed model is to improve the performance of semi–fully flexible systems and to maximize the production rate by ranking the parameters from most influenced to least. In this study, first, the performance of the considered process parameters are analyzed using a simulation approach, and furthermore the obtained results are validated using real-time experimental results. Thereafter, using an Entropy method, the weights of each parameter are identified and then the MCDM-based TOPSIS is applied to rank the parameters. The results show that Throughput tTme is the most affected parameter and that Availability, average stay time, and max stay time are least affected in the case of no breakdown of machine condition. Similarly, Throughput Time is the most affected parameter and Maximum Stay Time is the least affected parameter in the case of the breakdown of machine condition. Finally, the rankings from the TOPSIS method are compared with the PROMETHEE method rankings. The results demonstrate the ability to understand system behavior in both normal and uncertain conditions.

Costs, throughput time, and proportion of valid test results, a model-based analysis of liquid biopsies for stage IV non-small cell lung cancer.

e18844 Background: Tissue diagnostics for metastasized non-small cell lung cancer (NSCLC) is hampered by the difficulty of obtaining tissue biopsies, and sequential testing. This leads to patient burden, and a time-consuming diagnostic trajectory, sometimes without valid test results. We analyzed the diagnostic process of liquid biopsies (ctDNA) as an addition to tissue diagnostics, for patients with stage IV NSCLC. Methods: Data was retrieved from stage IV patients (N=209) included in the observational, Lung cancer Early Molecular Assessment trial (LEMA; NCT02894853). Within this study, plasma and tissue was collected upfront. Sequencing of ctDNA was performed retrospectively, and compared to results from tissue diagnostics, as performed in the including hospital, including test results, success-rates, and identified targets per patient. Throughput time for tissue, and costs for diagnostics were calculated within a single specialized institute. Because of the retrospective nature of the ctDNA assessment, diagnostics for implementation of ctDNA was modelled (1 run per week), based on estimations for the trajectory and throughput time. A discrete-event simulation model was developed with three scenarios: 1) diagnostics with tissue biopsy alone (comparator); 2) diagnostics with ctDNA first, and tissue biopsy if required; 3) ctDNA if biopsy failed. The process scope ranged from tissue/blood retrieval to outcome in terms of targets. Simulation analysis was performed, calculating mean price per patient (pp), median throughput time pp, and targets found per scenario. Results: In scenario 1, 85% of the patients had a clinically relevant test result, compared to 93% and 92% when ctDNA was added in scenario 2 and 3, respectively. Scenario 2 was the fastest, but also the costliest scenario: median throughput time 15 days pp (IQR 8-30) and mean costs of €2.716 pp (standard deviation [SD] €789) (Table). In this scenario, 9.9% of the biopsies could be cancelled, and in 39.6% a simple biopsy with immunohistochemistry was sufficient. Conclusions: The addition of ctDNA may lead to better informed treatment decisions in patients with stage IV NSCLC. Discrete-event simulation analysis showed that the addition of ctDNA in the diagnostic process increased proportion of patients with a clinically relevant test-result in both scenarios. Throughput time is faster, and additional costs per patient are limited, especially when ctDNA is added after biopsy failure. Clinical trial information: NCT02894853. [Table: see text]

Patient Throughput Times for Supplemental Breast Cancer Screening Exams

Background: To optimize screening abbreviated breast MRI (ABMR) operations, patient throughput times of ABMR were compared to breast ultrasound (US) and full protocol breast MRI (FPMR).Methods: Patient throughput times (mean ± standard error) and its subcomponents were analyzed for 95 ABMRs, 90 breast US exams, and 50 FPMRs. Total patient throughput was measured from registration time to the time of the last acquired image. Actual exam time was time difference between the first and last acquired images and pre-examination time was the calculated difference between throughput and actual exam times. Results: ABMR total patient throughput time was shorter than FPMR (55.7 ± 1.7 vs. 63.1 ± 2.0 min; difference, 7.4 min, 13%; p<0.001), but longer than breast US (39.1 ± 1.3 min; difference, 16.6 min, 30%; p<0.001). ABMR had shorter actual scan times than FPMR (13.4 ± 0.14 vs. 18.6 ± 0.25 min; p<0.001), but longer than US (9.6 ± 0.46 minutes; p<0.001). There was no difference in the pre-examination times between ABMR and FPMR (42.3 ± 1.7 vs. 44.6 ± 1.9 min; p = 0.357); pre-examination times were longer for both MR exam types compared to US (29.5 ± 1.3 minutes; p<0.001). Conclusion: ABMR patient throughput times are faster than FPMR, but these gains are limited as they have no impact on pre-examination activities which comprise the lengthiest components of the patient flow process. US patient flow currently remains faster than ABMR; however, comparable ABMR times could be achieved by further omitting certain sequences and optimizing pre-examination processes.