Digital Transformation Strategies for the Machinery Manufacturing Sector

Introduction

Manufacturing companies are embracing digital transformation.  They are reinventing business processes and relationships, and remaking legacy IT systems – for business, engineering, supply chain, and manufacturing operations – based on modern software systems, artificial intelligence, and connected things.  They are pursuing modular automation and other Industrie 4.0 (I4.0) strategies.  And they are developing creative new ways to collaborate with and support customers. 

Machinery OEMs had a good 2017.  However, many are in a transition phase and worried that they may miss out on talent, digitization, modularization, or new control technology.  Long-run trends, such as rising wages in China, demands for increased quality of consumer products, and flexibility of production also drive adoption of machinery across all main end user industries.

In 2009, many machinery OEMs experienced a sharp drop in revenues, as most business models still relied primarily on selling machinery and on capital expenditures of end users.  Now, many OEMs are working on new business models to smooth out revenue streams.

Machinery manufacturing revenues and capital expenditures increased strongly in 2017 at around 10 percent.  Strong growth is expected in machinery in 2018, driven by increased expenditures in the automotive, electronics, mining, construction, and agriculture industries. 

Machine makers are creating tailored, digitally-enabled, intelligent connected products.  Increasingly, they are doing so using innovative processes like connected manufacturing, predictive maintenance, and pioneering service models. Digitization allows them to differentiate themselves and grow the business, while reducing the risk of becoming irrelevant as the market-place evolves.  One potential area of growth is in service.  Today, many OEM machine builders lose much of the potential service business to third parties that often take 40 percent or more of the service business.  But with intelligent machines, the OEMs could capture more of this business with innovative business models. 

Table of Contents

• Introduction
• Critical Digital Transformation Initiatives
  • IT Systems:  Business Systems and Cloud Infrastructure
  • ET Systems:  Product Design, Simulation, Engineering
  • OT Systems:  Drive Performance throughout Production Operations
  • ST (Service Technology) Systems:  Services for Connected Products
  • Additive Manufacturing
  • Artificial Intelligence and Machine Learning
  • Cybersecurity
  • Workforce Considerations
• Recommendations

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