Shipbuilding and Offshore Plant cases

What is shipbuilding and offshore plant industry?

Shipbuilding and offshore plant industry refers to the industry that builds ships or builds, installs and supplies equipment required for developing marine resources such as petroleum and gas. In case of shipbuilding and offshore plant industry, the process from order to delivery usually takes about 2 years and it is characterized by the fact that order and production are strictly based on the demand of the ordering party.

Need for analyzing shipbuilding and offshore plant industry

In case of domestic shipbuilding and offshore plant industry, business losses worth tens of trillions of Korean Won have been recorded due to external factors such as suspension of new orders caused by global economic crisis, low-cost orders from China, drop in international oil prices and also due to internal factors such as absence of design technology caused by experience in special ship types, signing of wrong contract conditions in relation to design change and others. Recently, with the development of IT technology, manufacturing data is being accumulated through ERP, MES and others but in case of shipbuilding and offshore plant industry, analysis on these data are not being carried out effectively.

Data analysis detail technique

In this project, process data and schedule data analysis of offshore plant industry were carried out.

Process pattern analysis using Dotted Chart

Analyze pattern by each product (case) that pass through specific manufacturing process and analyze the characteristics of process by measuring the statistics such as number of events and total time taken with regard to such

Process model analysis

The process model analysis identifies process models by applying algorithm that extracts sequences of events between works based on transaction logs

Performance analysis

Visualization of basic performance analysis by work, number of frequencies by department, execution time, waiting time and time taken as well as result of 2-Dimension analysis, sequence of event analysis, matching rate and comparative analysis of sequence of events through various diagrams

Social network analysis

Analyzes not only the process model that indicates the flow of work, but also the flow of operators participating in the manufacturing process, the flow of working departments, and the flow between equipment, then identifies it into the social network

Identification of bottleneck points by identifying process model
  • Identification of process model of plan and performance
  • Execution of comparative analysis by item (case/department/process)
  • Discovery of re-work process which wasn’t in the plan

[Figure] Comparison of plan and performance process model

Result of key analysis
Comparison of delay parameter by item (case/department/process) through comparative analysis of plan and performance

[Figure] Analysis of process delay

Analysis of process load
  • Prediction of process load by department through comparative analysis of plan and performance data
  • Identification of department handling quantity that has increased by approximately two folds compared to plan

[Figure] Analysis of load comparison by department

Analysis of effect

It was possible to achieve advancement of production efficiency by predicting manufacturing process by analyzing process and schedule data.

  • 1% enhancement of productivity by reduction of process analysis time, 20% enhancement of process management work efficiency, reduction of process delay and reduction of production manhour
Reason for selecting Puzzle Data’s ProDiscovery in major shipbuilding and offshore plant in Korea

Malfunction and error prediction can be achieved through analysis of status data by parts required in manufacturing equipment and process of manufacturing process and data created in the operation of heavy machinery facilities or high-tech product equipment. Through this, enhancement of company’s production, such as drop in defect rate, reduction of individual period, optimization of production management and reduction of operation cost, can be expected.