Global Artificial Intelligence in Cement Production Market Size, Trends & Analysis - Forecasts to 2026 By Component (Solutions, and Services), By Application (Productivity Enhancement, Process Stabilization, Cost Effectiveness, and Other Applications) By Technology (Predictive Analysis, Data Analysis, Machine Learning, and Other Technologies), Competitive Landscape Company Market Share Analysis, and Competitor Analysis
The global artificial intelligence in cement production market is projected to grow at a CAGR value of 28.5% during the forecast period of 2021 to 2026. The basic supplies of construction, housing, and industrial construction come from the cement production sector.
Cement production companies hold significant importance in the manufacturing industry as they play the role of raw material supplies. However, due to the hard impact of COVID-19 pandemic and lockdown norms across the globe, the construction activities had come to a standstill which affected the cement production segment greatly. The return of investment is huge in cement production and hence, the segment has witnessed a rising demand in process enhancement to curb the cost of manual labor and traditional IT-based systems. Cement industries include a plethora of operations and activities that are very intricate, hence the cement industry needs a solution to smoothen the workflow in the industry.
Cement production companies across the developed and developing regions are facing issues related to lack of improvement in the production process, high cost associated with manual functioning, and high time consumption output process.
Hence, various AI-based software help manufacturers address the need for high-performance processes and offer maximum availability and flexibility of the process. These AI software are installed to execute high-performing quality assurance and quality control in order to increase the production volume and enhance cement quality.
Hence, the rising need for automation, as this industry is yet to transform into digitalization, increasing need to the rising cost of manual procedures, and rising need from the end-user industry for high-quality cement will help the AI in cement production market to grow rapidly. Evolution of industrial IoT and automation, rising demand for real-time data analysis of operational systems and business systems, increasing cases of human caused errors during QC and QA procedures, rising investment from government organizations to install and integrate AI based software solutions in manufacturing facilities, will help the market grow rapidly.
On the other hand, the market study also reveals that there would be an increase in unemployment due to the augmentation of software and intelligent robots and lack of awareness regarding AI based software in developing regions and third world countries. These factors will contribute to becoming a growth hindrance in the market from 2021 to 2026.
Based on the component, the market is segmented into solutions and services. The solutions segment will hold a lion’s share in the market owing to an increasing need for AI in enhancing the productivity, stabilization of the process, and cost effectiveness (from production to sales) in the downstream and upstream process of cement production. However, the services segment will be the fastest-growing segment in the market from 2021 to 2026.
Based on application, the market can be divided into productivity enhancement, process stabilization, cost effectiveness, and other applications. The cost effectiveness segment will foresee a faster growth rate as compared to other application segments from 2021 to 2026. Increasing demand for lowering operation cost and human resources, is the major factor affecting the volume production process. Also, cost curtailment for raw material extraction and reduction in clinker production cost are some of the factors leading to the growth of this segment in the market.
Based on the technology, the market can be split into predictive analysis, data analysis, machine learning and other technologies. The predictive analysis helps the manufacturer identify the hidden reason for inefficiencies in the production process, which ultimately affects production/ volume loss hampering expenses and positive financial return. Major manufacturers across the globe have started implementing predictive analysis technology in order to speed up the return of investment process. Hence, this segment will be the largest and fastest-growing segment in the AI in cement production market from 2021 to 2026.
As per the geographical analysis, the artificial intelligence in the cement production market can be classified into North America (the United States, Canada, and Mexico), Asia Pacific (India, China, Japan, Malaysia, Singapore, and the Rest of Asia Pacific), Europe (Germany, United Kingdom, Italy, France, Spain, Netherlands, and Rest of Europe), Middle East & Africa (Saudi Arabia, United Arab Emirates, and Rest of the Middle East & Africa) and Central & South America (Brazil, Argentina, and Rest of Central and South America). North America (the United States, Canada, and Mexico) will have a dominant share in the market from 2021 to 2026. This is mainly attributed to the increasing awareness regarding the successful integration of IoT and cement manufacturing process, rising expenditure on IT infrastructure of manufacturing facilities, and increasing launch of advanced AI software in the US market. However, on the contrary, the Asia Pacific (India, China, Japan, Malaysia, Singapore, and the Rest of Asia Pacific) segment will be the fastest growing segment in the AI in cement market from 2021 to 2026. This is mainly because of the presence of top cement manufacturing firms in countries like China, India, Japan and others. Also, with the dominant presence of world’s top cement end-users in China will help the Asia Pacific market grow rapidly.
Siemens, ES Processing, Petuum, Algomost, Seebo Interactive LTD, alcemy, ALGO8, Inc., FLSmidth, ABB, PEAKEDNESS, Lighthouse Info Systems Pvt. Ltd., Sabia, Inc., Oficemen, Halliburton, and thyssenkrupp among others are the players in the artificial intelligence in the cement production market.
Please note: This is not an exhaustive list of companies profiled in the report.
In December 2020, FLSmidth launched its AI based software namely ECS/ProcessExpert V8.5 software in order to gear up the process control of cement production and ultimately help launch smart cement plants in the region.
Chapter 1 Methodology
1.1 Market Scope & Definitions
1.2 Estimates & Forecast Calculation
1.3 Historical Data Overview and Validation
1.4 Data Sources
1.4.1 Secondary
1.4.2 Primary
Chapter 2 Report Outlook
2.1 Artificial Intelligence in Cement Production Industry Overview, 2020-2026
2.1.1 Industry Overview
2.1.2 Component Overview
2.1.3 Application Overview
2.1.4 Technology Overview
2.1.6 Regional Overview
Chapter 3 Artificial Intelligence in Cement Production Market Trends
3.1 Market Segmentation
3.2 Industry Background, 2020-2026
3.3 Market Key Trends
3.3.1 Positive Trends
3.3.1.1 Increasing need to curb the cost associated with production, sales and quality check of cement
3.3.2 Industry Challenges
3.3.2.1 Lack of adequate IOT infrastructure and automated systems in developing nations
3.4 Prospective Growth Scenario
3.4.1 Component Growth Scenario
3.4.2 Application Growth Scenario
3.4.3 Technology Growth Scenario
3.5 COVID-19 Influence over Industry Growth
3.6 Porter’s Analysis
3.7 PESTEL Analysis
3.8 Value Chain & Supply Chain Analysis
3.9 Regulatory Framework
3.9.1 North America
3.9.2 Europe
3.9.3 APAC
3.9.4 LATAM
3.9.5 MEA
3.10 Technology Overview
3.11 Market Share Analysis, 2020
3.11.1 Company Positioning Overview, 2020
Chapter 4 Artificial Intelligence in Cement Production Market, By Component
4.1 Component Outlook
4.2 Solutions
4.2.1 Market Size, By Region, 2020-2026 (USD Million)
4.3 Services
4.3.1 Market Size, By Region, 2020-2026 (USD Million)
Chapter 5 Artificial Intelligence in Cement Production Market, By Application
5.1 Application Outlook
5.2 Productivity Enhancement
5.2.1 Market Size, By Region, 2020-2026 (USD Million)
5.3 Process Stabilization
5.3.1 Market Size, By Region, 2020-2026 (USD Million)
5.4 Cost Effectiveness
5.4.1 Market Size, By Region, 2020-2026 (USD Million)
5.5 Other Applications
5.5.1 Market Size, By Region, 2020-2026 (USD Million)
Chapter 6 Artificial Intelligence in Cement Production Market, By Technology
6.1 Predictive Analysis
6.1.1 Market Size, By Region, 2020-2026 (USD Million)
6.2 Data Analysis
6.2.1 Market Size, By Region, 2020-2026 (USD Million)
6.3 Machine Learning
6.3.1 Market Size, By Region, 2020-2026 (USD Million)
6.4 Other Technologies
6.4.1 Market Size, By Region, 2020-2026 (USD Million)
Chapter 7 Artificial Intelligence in Cement Production Market, By Region
7.1 Regional outlook
7.2 North America
7.2.1 Market Size, By Country 2020-2026 (USD Million)
7.2.2 Market Size, By Component, 2020-2026 (USD Million)
7.2.3 Market Size, By Application, 2020-2026 (USD Million)
7.2.4 Market Size, By Technology, 2020-2026 (USD Million)
7.2.5 U.S.
7.2.5.1 Market Size, By Component, 2020-2026 (USD Million)
7.2.5.2 Market Size, By Application, 2020-2026 (USD Million)
7.2.5.3 Market Size, By Technology, 2020-2026 (USD Million)
7.2.6 Canada
7.2.6.1 Market Size, By Component, 2020-2026 (USD Million)
7.2.6.2 Market Size, By Application, 2020-2026 (USD Million)
7.2.6.3 Market Size, By Technology, 2020-2026 (USD Million)
7.2.7 Mexico
7.2.7.1 Market Size, By Component, 2020-2026 (USD Million)
7.2.7.2 Market Size, By Application, 2020-2026 (USD Million)
7.2.7.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3 Europe
7.3.1 Market Size, By Country 2020-2026 (USD Million)
7.3.2 Market Size, By Component, 2020-2026 (USD Million)
7.3.3 Market Size, By Application, 2020-2026 (USD Million)
7.3.4 Market Size, By Technology, 2020-2026 (USD Million)
7.3.5 Germany
7.3.5.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.5.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.5.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3.6 UK
7.3.6.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.6.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.6.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3.7 France
7.3.7.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.7.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.7.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3.8 Italy
7.3.8.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.8.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.8.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3.9 Spain
7.3.9.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.9.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.9.3 Market Size, By Technology, 2020-2026 (USD Million)
7.3.10 Russia
7.3.10.1 Market Size, By Component, 2020-2026 (USD Million)
7.3.10.2 Market Size, By Application, 2020-2026 (USD Million)
7.3.10.3 Market Size, By Technology, 2020-2026 (USD Million)
7.4 Asia Pacific
7.4.1 Market Size, By Country 2020-2026 (USD Million)
7.4.2 Market Size, By Component, 2020-2026 (USD Million)
7.4.3 Market Size, By Application, 2020-2026 (USD Million)
7.4.4 Market Size, By Technology, 2020-2026 (USD Million)
7.4.5 China
7.4.5.1 Market Size, By Component, 2020-2026 (USD Million)
7.4.5.2 Market Size, By Application, 2020-2026 (USD Million)
7.4.5.3 Market Size, By Technology, 2020-2026 (USD Million)
7.4.6 India
7.4.6.1 Market Size, By Component, 2020-2026 (USD Million)
7.4.6.2 Market Size, By Application, 2020-2026 (USD Million)
7.4.6.3 Market Size, By Technology, 2020-2026 (USD Million)
7.4.7 Japan
7.4.7.1 Market Size, By Component, 2020-2026 (USD Million)
7.4.7.2 Market Size, By Application, 2020-2026 (USD Million)
7.4.7.3 Market Size, By Technology, 2020-2026 (USD Million)
7.4.8 Australia
7.4.8.1 Market Size, By Component, 2020-2026 (USD Million)
7.4.8.2 Market size, By Application, 2020-2026 (USD Million)
7.4.8.3 Market Size, By Technology, 2020-2026 (USD Million)
7.5 Latin America
7.5.1 Market Size, By Country 2020-2026 (USD Million)
7.5.2 Market Size, By Component, 2020-2026 (USD Million)
7.5.3 Market Size, By Application, 2020-2026 (USD Million)
7.5.4 Market Size, By Technology, 2020-2026 (USD Million)
7.5.5 Brazil
7.5.5.1 Market Size, By Component, 2020-2026 (USD Million)
7.5.5.2 Market Size, By Application, 2020-2026 (USD Million)
7.5.5.3 Market Size, By Technology, 2020-2026 (USD Million)
7.5.6 Mexico
7.5.6.1 Market Size, By Component, 2020-2026 (USD Million)
7.5.6.2 Market Size, By Application, 2020-2026 (USD Million)
7.5.6.3 Market Size, By Technology, 2020-2026 (USD Million)
7.5.7 Argentina
7.5.7.1 Market Size, By Component, 2020-2026 (USD Million)
7.5.7.2 Market Size, By Application, 2020-2026 (USD Million)
7.5.7.3 Market Size, By Technology, 2020-2026 (USD Million)
7.6 MEA
7.6.1 Market Size, By Country 2020-2026 (USD Million)
7.6.2 Market Size, By Component, 2020-2026 (USD Million)
7.6.3 Market Size, By Application, 2020-2026 (USD Million)
7.6.4 Market Size, By Technology, 2020-2026 (USD Million)
7.6.5 Saudi Arabia
7.6.5.1 Market Size, By Component, 2020-2026 (USD Million)
7.6.5.2 Market Size, By Application, 2020-2026 (USD Million)
7.6.5.3 Market Size, By Technology, 2020-2026 (USD Million)
7.6.6 UAE
7.6.6.1 Market Size, By Component, 2020-2026 (USD Million)
7.6.6.2 Market Size, By Application, 2020-2026 (USD Million)
7.6.6.3 Market Size, By Technology, 2020-2026 (USD Million)
7.6.7 South Africa
7.6.7.1 Market Size, By Component, 2020-2026 (USD Million)
7.6.7.2 Market Size, By Application, 2020-2026 (USD Million)
7.6.7.3 Market Size, By Technology, 2020-2026 (USD Million)
Chapter 8 Company Landscape
8.1 Competitive Analysis, 2020
8.2 Thyssenkrupp.
8.2.1 Company Overview
8.2.2 Financial Analysis
8.2.3 Strategic Positioning
8.2.4 Info Graphic Analysis
8.3 Siemens
8.3.1 Company Overview
8.3.2 Financial Analysis
8.3.3 Strategic Positioning
8.3.4 Info Graphic Analysis
8.4 ES Processing
8.4.1 Company Overview
8.4.2 Financial Analysis
8.4.3 Strategic Positioning
8.4.4 Info Graphic Analysis
8.5 Petuum
8.5.1 Company Overview
8.5.2 Financial Analysis
8.5.3 Strategic Positioning
8.5.4 Info Graphic Analysis
8.6 Algomost
8.6.1 Company Overview
8.6.2 Financial Analysis
8.6.3 Strategic Positioning
8.6.4 Info Graphic Analysis
8.7 Seebo Interactive LTD
8.7.1 Company Overview
8.7.2 Financial Analysis
8.7.3 Strategic Positioning
8.7.4 Info Graphic Analysis
8.8 alcemy
8.8.1 Company Overview
8.8.2 Financial Analysis
8.8.3 Strategic Positioning
8.8.4 Info Graphic Analysis
8.9 ALGO8, Inc.
8.8.1 Company Overview
8.8.2 Financial Analysis
8.8.3 Strategic Positioning
8.8.4 Info Graphic Analysis
8.10 FLSmidth
8.10.1 Company Overview
8.10.2 Financial Analysis
8.10.3 Strategic Positioning
8.10.4 Info Graphic Analysis
8.11 Other Companies
8.11.1 Company Overview
8.11.2 Financial Analysis
8.11.3 Strategic Positioning
8.11.4 Info Graphic Analysis
The Global Artificial Intelligence in Cement Production Market has been studied from the year 2019 till 2026. However, the CAGR provided in the report is from the year 2021 to 2026. The research methodology involved three stages: Desk research, Primary research, and Analysis & Output from the entire research process.
The desk research involved a robust background study which meant referring to paid and unpaid databases to understand the market dynamics; mapping contracts from press releases; identifying the key players in the market, studying their product portfolio, competition level, annual reports/SEC filings & investor presentations; and learning the demand and supply-side analysis for the Artificial Intelligence in Cement Production Market.
The primary research activity included telephonic conversations with more than 50 tier 1 industry consultants, distributors, and end-use product manufacturers.
Finally, based on the above thorough research process, an in-depth analysis was carried out considering the following aspects: market attractiveness, current & future market trends, market share analysis, SWOT analysis of the company and customer analytics.
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