Shipbuilding and offshore plant

Hyundai Heavy Industries, Daewoo Shipbuilding & Marine Engineering, Samsung Heavy Industries

Fields of application

Need for measures for process delay and efficient utilization of resources through effective analysis of manufacturing process data
  • Although massive manufacturing data is being accumulated through system related to ERP, MES and POP that support the manufacturing process, efficient analysis is not being carried out. There is a big difficulty in data analysis and creation of report on results.
  • In the shipbuilding and offshore plant industry, large-scale projects are implemented simultaneously so it is difficult to analyze the current status of process’s progress and work load. In addition, in case process’s progress is delayed, it is difficult to analyze the mutual relationship between production plan and performance data and to analyze the root cause.

Application method

Process analysis based on process mining
  • The process pattern by each product (case) that passes through the manufacturing process can be analyzed and through basic analysis, the characteristics of the process can be analyzed by measuring the basic statistics such as number of events and work time. By using transaction logs, the process model is identified by analyzing the process model and by considering the relationship between works.
  • Process pattern analysis, process model analysis, performance analysis, social network analysis and the like can be carried out by using Dotted Chart by utilizing process analysis based on process mining. Not only the process model indicating the flow of work but the flow between workers participating in the manufacturing process, working department or between equipment can be analyzed through social network analysis.
  • Process model can be identified and the bottleneck point can be identified by using the process plan and performance data. Re-work process can be checked and the planned schedule of delayed process can be adjusted.

Analysis effect

  Effect of reducing cost of KRW 5.3 billion a year through enhancement of process management work, reduction of process delay and reduction of production manhour