P-graph approach to human resource reallocation in industrial plants under crisis conditions
Added Title
International Symposium on Advanced Control of Industrial Processes (6th : 2017)
AdCONIP 2017
College
Gokongwei College of Engineering
Department/Unit
Chemical Engineering
Document Type
Conference Proceeding
Source Title
2017 6th International Symposium on Advanced Control of Industrial Processes, AdCONIP 2017
First Page
131
Last Page
136
Publication Date
7-18-2017
Abstract
P-graph methodology was originally proposed as a systematic approach to process network synthesis (PNS). However, this graph theoretic approach has also been applied to a broad range of problems with similar structure as PNS. In particular, recent work has demonstrated the similarity of PNS problems to input-output (IO) optimization problems; the latter class of problems has been applied for physical flows at scales ranging from process plant level to supply chain level. IO models have also been proposed to plan the allocation of human resource in organizations. In this work, a P-graph based approach to reallocation of human resources in an industrial plant during a transient crisis is presented. The model determines how personnel can be reassigned to allow a plant to operate at an alternative temporary steady state when the plant becomes short-handed due to a disruptive external event. This methodology is demonstrated using a representative case study involving an instant coffee plant. Results show that in the occasion that a reduction in available workforce is experienced, workforce is allocated in more critical areas and productivity is maximized by minimizing interaction with less critical departments.
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Digitial Object Identifier (DOI)
10.1109/ADCONIP.2017.7983768
Recommended Citation
Aviso, K. B., Cayamanda, C. D., Mayol, A., & Tan, R. R. (2017). P-graph approach to human resource reallocation in industrial plants under crisis conditions. 2017 6th International Symposium on Advanced Control of Industrial Processes, AdCONIP 2017, 131-136. https://doi.org/10.1109/ADCONIP.2017.7983768
Disciplines
Engineering
Keywords
Manpower planning
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