Workers benchmarking using multi-directional efficiency analysis in a manufacturing production system

Breda, Ana; Brochado, Ângela F.; Moura, Ana

doi:10.1016/j.procs.2022.01.346

Cited by 3 publications

(1 citation statement)

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“…Step 9 in the protocol described above suggested looking, along time, to the parameters as time series and proceeding with a time series decomposition into three component functions: seasonality, trend, and noise. This step is somehow a continuation of previous work from the authors, where a benchmark study relative to the performance of manufacturing line workers was conducted using multi-directional efficiency analysis (Rocha et al 2022). Driven by data, this study allowed the benchmark of human-related factors (experience time, wage, delay time and response time) that had a major impact on a manufacturing line performance, namely the number of reworks and bottleneck occurrence.…”

Section: Protocol Step Nine -The Time Series Decompositionmentioning

confidence: 95%

PDCA Protocol to ensure a Data-Driven Approach for Problem-Solving

Proceedings of the International Conference on Industrial Engineering and Operations Management

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Problem-solving based, as much as possible, on real data, expert knowledge, and on-field observation are quite desired objectives. However, it creates several difficulties on deployment in real situations. In this work, a data-driven version of the well-known PDCA cycle is proposed for continuous improvement within a general class of problems represented by key performance indicators (KPI). Such class is wide enough to accommodate several real problems but still has a controlled level of complexity that allows defining a general data-driven protocol that covers all the (sub)steps of the cycle. New approaches and alternatives in the literature are discussed. A brief example of one of the steps of the protocol is given with real data from a company that adopts many of the new Industry 4.0 technologies.

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Section: Protocol Step Nine -The Time Series Decompositionmentioning

confidence: 95%