An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning

The uncertainty of demand has led production systems to become increasingly complex; this can affect the availability of the machines and thus their maintenance. Therefore, it is necessary to adequately manage the information that facilitates decision-making. This paper presents a system for making decisions related to the design of customized maintenance plans in a production plant. This paper addresses this tactical goal and aims to provide greater knowledge and better predictions by projecting reliable behavior in the medium-term, integrating this new functionality into classic Balance Scorecards, and making it possible to extend their current measuring function to a new aptitude: predicting evolution based on historical data. In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. This new extension allows better control over the maintenance function of an industrial plant in the medium-term with a yearly horizon taken over monthly intervals which allows the measurement of the indicators of strategic productive areas and the discovery of hidden behavior patterns in work orders. In addition, this extension enables the prediction of indicator outcomes such as overall equipment efficiency and mean time to failure

Influence of the length of hospitalisation in post-discharge outcomes in patients with acute heart failure: Results of the LOHRCA study.

To investigate the relationship between length of hospitalisation (LOH) and post-discharge outcomes in acute heart failure (AHF) patients and to ascertain whether there are different patterns according to department of initial hospitalisation. Consecutive AHF patients hospitalised in 41 Spanish centres were grouped based on the LOH (15 days). Outcomes were defined as 90-day post-discharge all-cause mortality, AHF readmissions, and the combination of both. Hazard ratios (HRs), adjusted by chronic conditions and severity of decompensation, were calculated for groups with LOH >6 days vs. LOH 6 days vs. LOH We included 8563 patients (mean age: 80 (SD = 10) years, 55.5% women), with a median LOH of 7 days (IQR 4-11): 2934 (34.3%) had a LOH 15 days. The 90-day post-discharge mortality was 11.4%, readmission 32.2%, and combined endpoint 37.4%. Mortality was increased by 36.5% (95%CI = 13.0-64.9) when LOH was 11-15 days, and by 72.0% (95%CI = 42.6-107.5) when >15 days. Conversely, no differences were found in readmission risk, and the combined endpoint only increased 21.6% (95%CI = 8.4-36.4) for LOH >15 days. Stratified analysis by hospitalisation departments rendered similar post-discharge outcomes, with all exhibiting increased mortality for LOH >15 days and no significant increments in readmission risk. Short hospitalisations are not associated with worse outcomes. While post-discharge readmissions are not affected by LOH, mortality risk increases as the LOH lengthens. These findings were similar across hospitalisation departments