Chemicals manufacturing 2030+
We see five global trends that will shift the industry.
1.
Growth rates will likely continue to diverge among China, US, and Europe; China will build new at-scale assets, while Europe and US will continue to use existing assets.
Reliance on existing assets may not prove a disadvantage for Europe and US, as "back-regionalization" of markets accelerates; Western assets tend to be better-performing even though Asia is catching up quickly.
2.
To fight labor-cost inflation, China and Eastern Europe will need significant productivity increases by applying Lean and Industry 4.0 techniques.
3.
Integrated sites will still be an advantage, as the basic economic reasons will continue to be relevant in a world of increasing digitization.
4.
Increasing volatility and potential crises will require companies to develop response scenarios emphasizing agile, end-to-end optimized supply chains.
5.
See how this impacts a chemical plant
Changes will happen mainly at the plant level, along 3 dimensions
Scale won’t necessarily be an advantage, given each plant requires a tailored optimization model.
Data management
Dive deeper
Maintenance technicians will use digital-workflow apps, increasing efficiency and productivity; control-room operators will continue to be present for safety reasons; and 40–60% of tasks will be replaced by automation.
People's tasks
Robotics, digital, and advanced analytics (AA) will change activities, not the fundamental design of assets; most solutions have a better business case when integrated into newly built assets, but can also be retrofitted easily.
Asset optimization
… and Lean will continue to be the foundation.
Scaling advanced analytics across multiple sites requires tailored optimization at every site
Contextual situation and external factors, such as temperature, humidity, and people, are inherently different for each plant and limit scalability of the AA algorithm. AA modeling has to be done at the plant level, as highly customized models are required. Simple replications or adaptions of a master and data across sites is not necessarily beneficial.
cement sites with comparable technology, covering 10+ countries in Europe
Example of a large cement manufacturer:
30+
Learn more:
Scale will not necessarily be an advantage in terms of the impact from data usage, because each plant will require a tailored optimization model; scale benefits will mainly come from database of failures.
Most data lakes will be built on-premise rather than in the cloud; limited comparability of sites, lack of speed, and data-security risks limit benefit of cross-site data pools.
Data will be managed by chemicals players, with access granted to externals on a need-to-know basis so they can leverage data to help reduce failures and increase service.
United Kingdom
Poland
Russia
Germany
Belgium
France
Spain
Moldavia
Romania
Czech Republic
Switzerland
Slovenia
Serbia
Greece
Cyprus
Austria
Hungary
SOURCE: McKinsey, press search
Average workload over an 8-hour shift for a high-performing specialty-chemicals plant
40% of value-adding operator time in specialty chemical plants (~60% in commodity chemical plant) can be saved through automation and applied towards more critical tasks that require humans; the limiting factor for reducing resources will be safety regulations
Maintenance technicians will use digital-workflow apps, increasing efficiency and productivity though improved planning, guidance, and performance management; in principle, tasks will stay the same
Control-room operators will remain for safety reasons; their tasks will evolve from “control” to “improve,” creating an enormous upskilling challenge.
Hours per operator
Breaks / non-value-adding work
Automatable workload
Human workload
Not automatable
Partially automatable
Automatable
Breaks/non-value- adding work
Total
Tasks that can only be carried out by humans, such as control walks, alarm management/alarm reaction, campaign change, and setup and shutdown.
A portion of current tasks involving human operators may see automation, such as standard-operating-procedure review, shift briefing, shift leader morning meeting, and new operator training.
Tasks that could be automated either with or without robots, including product sampling, in-process sampling, and catalyst preparation.
Value-adding time
3.0
1.5
2.2
1.3
8.0
1.0
.5
4.0 (50%)
2.7 (35%)
1.3 (15%)
People’s tasks
SOURCE: McKinsey
Based on a case study of a chemical company building a new plant. All of these levers can also be retrofitted into an existing plant, which would lead to a slight increase in payback times. We find that for most AA levers, payback times are typically less than 2 years, making them financially viable even when implementation costs are relatively high.
Value identified, mEUR
Implementation cost, mEUR
Payback
Selected key levers
Recurring
Capex savings
Plant steering
Reliability & maintenance execution
Operations
Capabilities
Core technical enablers
Total recurring
Digital project management
• Advanced analytics algorithm for steering • Optimization of energy flow at site level • Use of manufacturing intelligence
Regional consolidation of control rooms will only be implemented for a subset of asset archetypes, mostly because of safety regulations and risk limitations; consolidation of control rooms on site will be a significant improvement lever.
10
5
20
10-25
~1
~2
~3
Low
~6
3-10
>1 yr
1-2 yrs
• Digitization/automation of recurring maintenance activities
• Advanced analytics for reliability
Regional/global enabler–no separate value directly created, but precondition for achieving identified value
• Adoption of advanced project-management practices, Project Production Management
• Set-up of specific technologies against variability
