Managerial learning: a neglected dimension in decision support systems

Santana, Martín

doi:10.1109/hicss.1995.375741

Cited by 12 publications

(7 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed decision support framework can enhance the decision-making quality of maintenance engineers and managers to run an effective production system (Santana 1995). Production system effectiveness also depends on the crossfunctional collaboration with production organizations.…”

Section: Data-driven Decision Support Toolmentioning

confidence: 99%

See 1 more Smart Citation

Data-driven machine criticality assessment – maintenance decision support for increased productivity

Gopalakrishnan

Subramaniyan

Skoogh

2020

Production Planning & Control

View full text Add to dashboard Cite

Data-driven decision support for maintenance management is necessary for modern digitalized production systems. The data-driven approach enables analyzing the dynamic production system in realtime. Common problems within maintenance management are that maintenance decisions are experience-driven, narrow-focussed and static. Specifically, machine criticality assessment is a tool that is used in manufacturing companies to plan and prioritize maintenance activities. The maintenance problems are well exemplified by this tool in industrial practice. The tool is not trustworthy, seldom updated and focuses on individual machines. Therefore, this paper aims at the development and validation of a framework for a data-driven machine criticality assessment tool. The tool supports prioritization and planning of maintenance decisions with a clear goal of increasing productivity. Four empirical cases were studied by employing a multiple case study methodology. The framework provides guidelines for maintenance decision-making by combining the Manufacturing Execution System (MES) and Computerized Maintenance Management System (CMMS) data with a systems perspective. The results show that by employing data-driven decision support within the maintenance organization, it can truly enable modern digitalized production systems to achieve higher levels of productivity.

show abstract

Section: Data-driven Decision Support Toolmentioning

confidence: 99%

“…Therefore, in order to provide maintenance prioritization decision support not only on a strategic level but also on an operational level, a data-driven machine criticality assessment is needed. This assessment tool will aid decision-making for the maintenance engineers and planners by making the problem recognition easier (Santana 1995).…”

Section: Introductionmentioning

confidence: 99%

Data-driven machine criticality assessment – maintenance decision support for increased productivity

Gopalakrishnan

Subramaniyan

Skoogh

2020

Production Planning & Control

View full text Add to dashboard Cite

show abstract

“…The complexity of maintenance planning decisions regards an online decision support systems to assist the maintenance decision maker [39]. Thus, the main role of a DSS is to enhance the decision making by an individual through easier access to problem recognition, problem structure, information management, statistical tools, and the application of knowledge [60]. Usually, DSS for maintenance is defined as a systematic way of selecting a set of diagnostic and/or prognostic tools to monitor the condition of a single component or machine [39].…”

Section: Decision Support Systems In Transportation Systems Performanmentioning

confidence: 99%

Uncertainty Problem in Decision Support System for Means of Transport Maintenance Processes Performance Development / Problem Niepewności W Systemie Wsparcia Decyzyjnego Procesów Utrzymania W Stanie Zdatności Środków Transportu

Nowakowski¹,

Werbińska-Wojciechowska²

2012

Journal of KONBiN

View full text Add to dashboard Cite

In this paper, the authors’ research work is focused on uncertainty analysis implementation in the developed DSS for transportation means’ maintenance processes performance. Thus, in the Introduction section, the transportation means’ maintenance processes issues and the uncertainty problem are described. Later, there is briefly literature overview in the research area discussed. In the next Section, the expert system for means of transport maintenance processes performance is also investigated. Following this, the uncertainty analysis is developed and the examples of expert system implementation are given. The work ends up with summary and directions for further research.

show abstract

“…Ni and Jin (2012) state that current computerized maintenance management system cannot adhere to the dynamic maintenance needs and that new decision support tools are needed for effective maintenance operations. A decision support tool enhances decision-making capability through easier identification of the core problem (Santana, 1995). Therefore, maintenance prioritization can be an important decision support tool for planning maintenance operations (Li and Ni, 2009; Li, Ambani and Ni, 2009) when prioritization is set for the most critical machines.…”

Section: Introductionmentioning

confidence: 99%

Machine criticality based maintenance prioritization

Gopalakrishnan

Skoogh

2018

IJPPM

View full text Add to dashboard Cite

Purpose-The purpose of this paper is to identify the productivity improvement potentials from maintenance planning practices in manufacturing companies. In particular, the paper aims at understanding the connection between machine criticality assessment and maintenance prioritization in industrial practice, as well as providing the improvement potentials. Design/methodology/approach-An explanatory mixed method research design was used in this study. Data from literature analysis, a web-based questionnaire survey, and semi-structured interviews were gathered and triangulated. Additionally, simulation experimentation was used to evaluate the productivity potential. Findings-The connection between machine criticality and maintenance prioritization is assessed in an industrial setup. The empirical findings show that maintenance prioritization is not based on machine criticality, as criticality assessment is non-factual, static, and lacks system view. It is with respect to these finding that the ways to increase system productivity and future directions are charted. Originality/value-In addition to the empirical results showing productivity improvement potentials, the paper emphasizes on the need for a systems view for solving maintenance problems, i.e. solving maintenance problems for the whole factory. This contribution is equally important for both industry and academics, as the maintenance organization needs to solve this problem with the help of the right decision support.

show abstract

Managerial learning: a neglected dimension in decision support systems

Cited by 12 publications

References 35 publications

Data-driven machine criticality assessment – maintenance decision support for increased productivity

Data-driven machine criticality assessment – maintenance decision support for increased productivity

Uncertainty Problem in Decision Support System for Means of Transport Maintenance Processes Performance Development / Problem Niepewności W Systemie Wsparcia Decyzyjnego Procesów Utrzymania W Stanie Zdatności Środków Transportu

Machine criticality based maintenance prioritization

Contact Info

Product

Resources

About