산업 자동화 시장 조사

What is Industrial Automation

산업 자동화는 인간을 대체하기 위해 기계와 프로세스를 관리하기 위해 로봇과 IT 시스템을 사용합니다.

처음에는 인력과 관련된 비용을 줄이는 것이 목적이었습니다. 기업들은 생산량을 늘리기 위해 이를 활용하기도 했습니다. 하지만 오늘은 초점이 바뀌었습니다. 이제 기업에서는 이를 사용하여 변화에 적응할 수 있습니다. 그들은 또한 생산 과정의 품질을 향상시키기 위해 이를 사용하고 있습니다.

자동화는 오늘날 거의 모든 공장과 작업 현장에 적용됩니다. 그것이 없는 생산 라인은 상상하기 어렵습니다. 우리는 그것을 세 가지 클래스로 나눌 수 있습니다:

1. 결정된: 회사에서는 지루한 작업에 이 유형을 자주 사용합니다. 이는 프로세스를 효율적으로 만들고 처리 속도를 향상시킵니다.
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산업 자동화에는 현대 기술을 활용하여 산업 환경에서 제조 프로세스 및 운영의 자동화를 추진하는 것이 포함됩니다. 이 시장은 인공지능(AI), 로봇 공학, IoT 등 첨단 기술이 산업 공정에 도입되면서 향후 몇 년 동안 상당한 성장을 보일 것으로 예상됩니다.

This means that industrial automation market research is a rapidly expanding area because the tools of this sector are being continuously upgraded, and researchers must implement new strategies to keep pace with the industry, readjusting the approach of market analysts.

Industrial Automation Market Research: How Leading Manufacturers Capture Growth

Industrial automation is entering a phase where competitive position is set by intelligence, not capital. Capex alone no longer separates leaders from followers. The firms gaining share are reading demand signals, supplier shifts, and end-user adoption curves earlier than peers. That is the work of industrial automation market research.

The category now spans far more than PLCs and robotic arms. It includes machine vision, edge compute, predictive maintenance platforms, autonomous mobile robots, digital twins, and AI-driven process optimization. Buyers evaluating these systems run multi-year procurement cycles with cross-functional committees. Vendors who win understand the buying logic at each stage.

Why Industrial Automation Market Research Drives Strategic Advantage

The conventional approach treats automation research as a sizing exercise. Teams commission a TAM study, segment by end-use vertical, and stop there. The output is a deck with growth rates and a vendor map. It rarely changes a roadmap decision.

The better approach treats research as a continuous decision system tied to specific bets: which adjacency to enter, which OEM relationship to deepen, which control architecture to standardize on. Leading firms run installed base analytics alongside total cost of ownership modeling for each platform under consideration. They quantify aftermarket revenue strategy across the asset lifecycle, not just the initial sale.

According to SIS International Research, automation buyers in energy and chemical sectors weight reference installations and field service density more heavily than feature parity when selecting between competing platforms. Brand reputation among plant engineers, built over decades of uptime performance, predicts win rates more reliably than product specifications. That insight reshapes how challenger brands should sequence market entry.

The Buying Committee Behind Capital Equipment Decisions

Automation purchases involve four distinct stakeholder groups. Plant engineers care about reliability and integration with legacy DCS environments. Operations leaders care about throughput and OEE gains. Procurement evaluates supplier qualification audits and bill of materials optimization. Corporate IT increasingly weighs in on cybersecurity posture and data architecture.

Each group reads different sources, attends different conferences, and trusts different voices. Research that surveys only one layer produces incomplete intelligence. B2B expert interviews across all four roles, conducted in sequence, surface the actual decision criteria and the veto points that kill deals late.

Rockwell Automation, Siemens, ABB, Schneider Electric, Emerson, Honeywell, and Yokogawa each occupy distinct positions in this committee map. Strength with one role does not transfer automatically to others. Mapping the gaps is where share is won.

Where the Growth Is Concentrated

Three vectors are pulling capital into automation faster than the broader industrial average. Reshoring feasibility studies are converting into capex commitments across semiconductors, pharmaceuticals, and battery manufacturing. Predictive maintenance sizing models show payback windows compressing as sensor and edge compute costs decline. Labor scarcity in food processing, logistics, and metal fabrication is forcing automation onto roadmaps that resisted it for years.

Each vector carries a different research requirement. Reshoring decisions need site selection intelligence and incentive package benchmarking. Predictive maintenance opportunities need installed base analytics by asset class. Labor-driven automation needs workflow-level task analysis to identify which steps can be automated economically.

Source: SIS International Research

What Separates Sharp Competitive Intelligence From Surface Mapping

Most competitive intelligence in this category catalogs product lines and pricing. That is the entry point, not the deliverable. The intelligence that changes commercial outcomes maps three deeper layers: channel economics, integrator relationships, and switching cost structures.

Channel economics determine whether a competitor can sustain price aggression in a given region. System integrators control which platforms get specified on greenfield projects, and their loyalties shift based on margin support and training investment. Switching costs in automation are dominated by engineering time, not equipment write-downs, which means displacement strategies must address engineering hours saved, not unit price.

SIS International’s structured expert interviews with senior automation engineers across North America and Europe consistently show that integrator relationships and field service density predict account retention more strongly than product roadmap quality. Vendors investing in integrator certification programs and regional service depth retain accounts through multi-cycle refreshes.

The SIS Approach to Industrial Automation Market Research

SIS International has conducted automation studies across energy, chemicals, oil and gas, food processing, and discrete manufacturing in more than 135 countries. The work typically combines four components: desk research and market sizing, B2B expert interviews with plant engineers and operations leaders, customer and competitor mapping with installed base analysis, and strategic analysis tied to a named decision.

The output is not a report. It is a position on a specific question: enter or not, acquire or build, standardize on platform A or B, price at premium or parity. SIS International’s proprietary research in industrial automation indicates that buyers narrow consideration sets within the first two vendor conversations, which means messaging and reference architecture must be sharp before the first sales call, not refined during the cycle.

A Framework for Prioritizing Automation Research Investment

Not every decision warrants the same research depth. The framework below sorts automation questions by capital exposure and reversibility, then matches each quadrant to a research intensity.

Source: SIS International Research

The discipline is matching research investment to decision weight. Over-researching reversible decisions burns budget. Under-researching irreversible ones destroys it.

What VP-Level Decision Makers Should Demand From Research

Automation research has value when it reduces uncertainty on a specific bet. The questions that matter at the VP level are concrete. Which segments will reward premium positioning over the next cycle? Where are integrator loyalties shifting? Which legacy installed bases are approaching forced refresh windows? What does the actual decision sequence look like inside a typical buying committee?

Generic market reports cannot answer these. Custom industrial automation market research, grounded in primary interviews with the engineers and operations leaders who write the specifications, can. The firms compounding share in this category are the ones treating research as an operating capability, not a procurement event.

Key Questions

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