What You Might Not Know About Industry 4.0
Brian Hoey - March 08, 2018
At a recent event, renowned consulting firm Deloitte revealed the results of a survey showing that only 14% of C-level executives were highly confident in their readiness to utilize Industry 4.0 principles to their maximum advantage. While other surveys have shown similar anxieties to exist throughout many different spheres of global manufacturing, we at the flexis blog believe that the new changes surrounding so-called smart factories, though significant, become less daunting as one learns more about them. After all, this new technology is explicitly meant to make life easier for businesses. In the spirit of demystifying the new global technological landscape, here are a few things you might not know about Industry 4.0:
It's Designed to Help Humans Make Decisions
The technological aspects of Industry 4.0 are touted as its primary value-added propositions, but what many people don’t realize is that the purpose of Industry 4.0’s promotion of visibility and interoperability is, in fact, to help humans in their jobs. More than a revolution in specific production processes, the Industry 4.0 supply chain is a paradigm shift in how planners and managers access the information they need in order to make informed decisions about their operations. Real-time data from internet-of-things (IoT) devices and other sensors ensures that planners are making their decisions based on the most complete and up-to-date information about their production processes, transport routing, and inventory usage.
The added value from these types of insights can be significant. More than that, cyber-physical systems that connect disparate points on the supply stream can eventually be trained to make small decisions on their own, freeing up human time and resources for longer term development and execution of production plans. And this is not to mention the improvements in forecasting and “what-if” scenarios that Industry 4.0 can bring about in manufacturing businesses, helping to create ever-more responsive supply chain management.
It Makes Sales & Operations Execution (S&OE) Possible
Not only does the added intra-operational visibility of Industry 4.0 workflows help to drive more informed operational planning, it also makes possible a new business function that helps to bridge the gap between long- and mid-term planning and day-to-day supply chain operations: S&OE. S&OE relies on real-time demand and supply data to make small, daily and weekly adjustments across a number of touchpoints on the value stream:
- Short-term inventory management
- Transport routing and other transportation planning tasks
- Daily ordering and restocking
Each of these tasks ensures that a given organization’s strategic and operational plans aren’t derailed by minor disruptions—a crucial value proposition, certainly, but impossible without access to the real-time demand data via a convenient interface that only Industry 4.0 systems can provide. This emerging practice obviously represents another manner in which Industry 4.0 aids human decision-making, but it also signals the kind of organizational changes that become possible when a company works toward an integrated supply chain. Looking beyond S&OE, businesses can expect to see other processes emerging in the era of Industry 4.0 that simply would not have been possible without boosts in interoperability and transparency.
It Drives Big Data Analytics
We’ve spoken a bit about Industry 4.0’s advances in data visibility and transparency, but what many people don’t realize is that these advances, in addition to promoting better planning and production scheduling, also pave the way for a symbiotic relationship between various touchpoints on the value chain and advanced analytics software. In earlier eras, big data analytics in manufacturing rarely had enough data to sustain meaningful business insights, but with real-time data collection and IoT sensors it is increasingly possible to integrate Industry 4.0 processes with intelligent planning and analytics software. Generally speaking, analytics can be divided into two categories:
- Predictive analytics, which help to create forecasts for demand and generate “what-if” scenarios for planning purposes;
- Prescriptive analytics, which examine existing workflows in order to uncover areas that can be made to function more efficiently or with increased synergy.
Both types can serve as crucial value-added propositions for manufacturers seeking a competitive edge, either by helping to promote the visibility necessary for a leaner supply chain or by improving existing supply chain processes. This not only results in a more responsive supply chain overall, but higher production quality, reduced maintenance downtime, and improved customer satisfaction.