Study
Commercial ProductionHigh ImpactStrong effect

Smart Manufacturing Boosts Petrochemical Efficiency and Competitiveness

Implementing smart manufacturing principles in the oil refining and petrochemical industry leads to significant improvements in operational efficiency, sustainability, and economic viability.

Engineering · 2017

01

Key Findings

  • 01Smart manufacturing enables a connected, information-driven environment for the petrochemical sector.
  • 02Applications include big data-driven fault detection and advanced optimization for planning and scheduling.
  • 03Key benefits include improved sustainability, productivity, innovation, and economic competitiveness.
  • 04Challenges exist in scientific factors and implementation for further smart manufacturing adoption.
02

Application

Design takeaway

Integrate data-driven insights and automation into the design of manufacturing processes to enhance efficiency, sustainability, and responsiveness to market demands.

How to apply

When designing or redesigning manufacturing systems, incorporate sensors for real-time data collection, utilize big data analytics for predictive maintenance and process optimization, and implement advanced scheduling and control systems.

Project actions

  • 01Consider how data can inform your design decisions.
  • 02Explore how automation can improve the efficiency of a product or system.
  • 03Think about the environmental impact of your design and how it can be minimized through smart processes.
03

Method & Evidence

AimWhat are the key applications and challenges of implementing smart manufacturing in the oil refining and petrochemical industry?
MethodLiterature Review and Case Study Analysis
ProcedureThe paper reviews existing literature and presents examples of smart manufacturing applications within the petrochemical sector, including fault detection using big data and advanced optimization for planning and scheduling. It also identifies scientific factors and challenges for future implementation.
ContextOil Refining and Petrochemical Industry

Variables

IV["Implementation of smart manufacturing technologies (e.g., big data analytics, advanced optimization)","Level of connectivity and information-driven processes"]
DV["Operational efficiency (e.g., productivity, throughput)","Sustainability metrics (e.g., energy usage, material waste)","Economic competitiveness (e.g., cost reduction, market responsiveness)","Innovation rate"]
CV["Specific industry sector (oil refining and petrochemical)","Type of manufacturing process","Existing infrastructure and technology base"]
04

Strengths & Limitations

Strengths

  • +Provides a forward-looking perspective on industrial automation.
  • +Highlights tangible benefits and specific application areas.

Limitations

The complexity and cost of implementing full-scale smart manufacturing systems can be a barrier.

Reliability & validity

The findings are based on a review of existing literature and case studies, suggesting moderate reliability. Validity is strong within the context of the oil refining and petrochemical industry but may vary when applied to other sectors.

Think critically

To what extent can the principles of smart manufacturing be applied to smaller-scale or less complex design projects, and what are the trade-offs?

05

Design Principles

"Leverage real-time data and advanced analytics to optimize manufacturing processes for improved performance and resource efficiency."

This approach integrates real-time data and advanced support systems to create a responsive and performance-driven manufacturing environment. By optimizing resource usage and production processes, companies can achieve higher productivity, foster innovation, and gain a competitive edge in the market.

06

What This Means for Your Design

Making factories smarter with computers and data helps the oil and chemical industry work better, use less energy, and be more environmentally friendly.

How to use in your project

  • 1.Reference this paper when discussing the benefits of data integration and automation in your design process.
  • 2.Use the examples of fault detection and optimization to justify the inclusion of similar features in your own design project.
07

Add to My Project

08

Quick Cite

(2017). Smart Manufacturing for the Oil Refining and Petrochemical Industry. Engineering. https://doi.org/10.1016/j.eng.2017.02.012 Retrieved from https://designdex.org/study/0d3adb0b-5ea8-457c-9037-24d4fc3a439d/smart-manufacturing-boosts-petrochemical-efficiency-and-competitiveness

Paragraph starter

The integration of smart manufacturing principles, as highlighted by Yuan et al. (2017), offers a pathway to significantly enhance operational efficiency and sustainability within industrial settings. By leveraging real-time data and advanced analytics for fault detection and process optimization, designers can create systems that are more responsive, resource-efficient, and economically competitive.

09

Source

Engineering

Smart Manufacturing for the Oil Refining and Petrochemical Industry

journal · 2017

View source

Questions about this research

What does the research say about smart manufacturing boosts petrochemical efficiency and competitiveness?
Integrate data-driven insights and automation into the design of manufacturing processes to enhance efficiency, sustainability, and responsiveness to market demands. Evidence: Engineering (2017).
Why does "Smart Manufacturing Boosts Petrochemical Efficiency and Competitiveness" matter for design?
This approach integrates real-time data and advanced support systems to create a responsive and performance-driven manufacturing environment. By optimizing resource usage and production processes, companies can achieve higher productivity, foster innovation, and gain a competitive edge in the market.
How can designers apply this research?
Integrate data-driven insights and automation into the design of manufacturing processes to enhance efficiency, sustainability, and responsiveness to market demands.
What were the main findings?
Smart manufacturing enables a connected, information-driven environment for the petrochemical sector.. Applications include big data-driven fault detection and advanced optimization for planning and scheduling.. Key benefits include improved sustainability, productivity, innovation, and economic competitiveness.. Challenges exist in scientific factors and implementation for further smart manufacturing adoption.
What research method was used?
Literature Review and Case Study Analysis.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2017 journal from Engineering.
What should I do differently in my next project?
When designing or redesigning manufacturing systems, incorporate sensors for real-time data collection, utilize big data analytics for predictive maintenance and process optimization, and implement advanced scheduling and control systems.
What are the limitations?
The paper focuses on specific applications and may not cover all aspects of smart manufacturing across the entire industry. The identified challenges might require further in-depth research.
Is there evidence that smart manufacturing affects design outcomes?
Smart manufacturing, through technologies like big data analytics and advanced optimization, can significantly enhance efficiency, sustainability, and profitability in the petrochemical industry, though challenges remain for widespread adoption. This approach integrates real-time data and advanced support systems to cr Source: Engineering (2017).
Where does this petrochemical industry research apply?
Oil Refining and Petrochemical Industry It sits within commercial production research on designdex.org.

Related research topics

smart manufacturing design research · evidence on smart manufacturing · does smart manufacturing improve design outcomes · petrochemical industry studies for designers · smart manufacturing and petrochemical industry findings · commercial production research evidence