Page 18 - IMDR Journal 2025

Research Article
6. Vendor Lock-In: Reliance on proprietary equipment or such as manufacturing automation, predictive maintenance,
one vendor can lead to long-term dependence, less flexible. and process optimization. However, this has its drawbacks
such as high cost of investment, integration problems, and
Use of IoT in smart manufacturing is no longer a future
vision—it is a ongoing training of the staff. For example, firms such as
Bosch and Wipro, the experts in automation and AI-driven
the requirement of today for these companies to stay current operations, will have to constantly upgrade their systems to
in a more interconnected world. Although the benefits are keep up with the speed of evolving technologies. As
great—everything from data-driven real-time decision- technology accelerates, firms have to be adaptable to
making to operations optimization—the risks involved transform and implement the latest technologies.
cannot be dismissed. Businesses have to go into this change
Analysis Depends on Secondary Data Sources: The research
strategically, with defined goals, robust cybersecurity
in this case depends on secondary data sources and not
mechanisms, and continuous employee training. That way,
they can maximize the potential of IoT while reducing its primary research methods. Data is gathered from company
downsides. reports, trade journals, research, share exchange filings, case
studies, and news coverage, and provide an overall sense of
the impact of Industry 4.0 on financial performance.
OBJECTIVES Unlike primary research, where direct questioning or
● To evaluate the impact of deep tech on the adoption of IoT interviewing people from the industry is conducted
in smart manufacturing and its effect on operational secondary data offers macro-level trend analysis and
efficiency. business performance. For example, financial
advancements by Vedanta, Hindalco, and Tata Motors are
● To assess the cost advantages of smart manufacturing
through IoT, such as cost savings, enhanced asset examined based on publicly available earnings reports and
market analysis instead of firsthand evidence collection
performance, and enhanced ROI.
from individual plants. The method provides a general, non-
● To determine the most significant risks and challenges selective view of how the Implementation of Industry 4.0
confronting the implementation of IoT and deep tech in impacts the different industries.
manufacturing, including cybersecurity risks, data privacy
issues, and integration issues.
● To study the impact of government policies and industry ASSUMPTIONS
standards on the secure and efficient integration of IoT in ● The Date Chosen for Cost-Benefit Analysis is Tentative
manufacturing. because Organizations Typically Take More than a Year to
Feel the Impact of Industry 4.0: In measuring the monetary
benefits of adopting Industry 4.0, the time for cost reduction
LIMITATIONS and revenue uplift is not overnight. Typically, an
organization takes at least 12 to 18 months to complete the
● Corporate Financials Represent the Whole Organization,
Not Just Individual Facilities technology uptake of smart manufacturing, optimize
processes, and see tangible improvements. This lag is
Financial performance of companies embracing Industry brought about by installation processes, testing, training of
4.0 technology is measured at the corporate level rather than employees, and procedural adjustments prior to full
a particular plant or facility. Yearly financial reports indicate realization of benefits from automation as well as digital
revenue expansion, cost reduction, and profit improvement transformation. Financial analyses done within the first few
at the whole organization level instead of confining the
months of implementation may therefore fail to capture the
analysis to the impact of digital transformation on a
full long-term impact, and any cost-benefit analysis must be
particular unit. For instance, Tata Motors' profitability viewed as preliminary until the organization has sufficient
comes from several divisions, such as passenger cars and time to settle into its new systems.
commercial vehicles, as compared to a single manufacturing
facility. Likewise, companies like Vedanta and Hindalco, ● Financial Performance Volatility in the Initial Stage Does
which operate different production units, record Not Reflect Industry 4.0 Success or Failure: During the early
improvements in efficiency across the entire supply stage of Industry 4.0 implementation, companies often
chain—ranging from raw material procurement to witness financial performance fluctuations such as short-
manufacturing and distribution—rather than attributing term cost increases due to capital expenditure, infrastructure
these improvements to a specific location. upgradation, and workforce training. These initial expenses
could lead to short-term drops in profitability prior to when
● The Rapid Pace of Technological Progress: Industry 4.0 is the expected operating efficiencies and cost savings start to
characterized by rapid innovation and evolving manifest. For instance, investments in automation using AI,
technologies, including Artificial Intelligence (AI), the monitoring based on IoT, and cloud computing involve huge
Internet of Things (IoT), robotics, cloud computing, and initial investments but reap dividends over the long term in
data analytics.
terms of lowered downtime, lower production costs, and
Organizations are required to remain current with these enhanced product quality. Accordingly, the financial results
developments to be effective and competitiveness. Endless of the initial few quarters after implementation might not be
new software and tool releases mean endless. technologies representative, and organizations need to measure the

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