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Digital Transformation In Life Sciences

How to prepare your shop floor for a digital transformation

The opportunity to transform life sciences operations with Industry 4.0 is here, yet traditional digitization approaches fail to help companies get started, adjust with changes, and continually improve. As a result, these approaches have not lived up to their promises of supporting initiatives around agility, compliance, quality, competitiveness, and volume.

In this guide, we’ll discuss the current downfall of traditional solutions and highlight new approaches organizations in life sciences have taken to tackle digital transformation. We’ll look at the paradigm shift from top-down to bottom-up and how the democratization of digital technologies has helped companies adopt this transformation with ease.

First off, let’s compare what the production schedule looks like in a non-digital setting vs a digital one.

Chapter One: Production Planning Problems

Let’s use a typical office problem as an example. Here is a challenge for a typical office of about 80, where there are only 2 bathrooms. The disappointment of walking to the bathrooms to find out they are both occupied is a common occurrence, and as a result, multiple trips and queues lead to inefficiencies. What makes matters worse is that the bathrooms are tucked away in a corridor, which makes it difficult to tell if they are open.

So as a part of a hackathon, two engineers came up with the idea of putting two IIoT sensors by the doors and tracking their availability with an I/O gateway. The engineers then connected this gateway to a Tulip app (named Toilep) and relayed information to Slack, where people could ask a bot to get the most real-time, accurate information on the availability of bathrooms right from their desks.

So why this example?

You might think that this is just another trivial office problem, but in fact, it is very similar to the kind of problems manufacturers face when planning and scheduling production.

If we consider going to the bathroom as work and the bathroom itself as the piece of equipment where work is done, you would think that the most efficient way of planning trips to the bathroom would be to create an Excel sheet that assigns each person to a time slot. Right?

Well…not quite. What this system assumes is a very static world in which there is no variability and no unexpected events or any type of waste. And that is simply not the case in manufacturing. Production processes are full of frequent variations and changes.

In a typical production process, team members can push, cancel, or backlog scheduled work, meaning that the unused equipment (or in this example, the vacant bathroom) can be made available for someone else to use. Therefore, increasing the flexibility and visibility of production planning and scheduling is vital to running an agile operation.

So how is this shift in digital transformation achieved? To understand what cultural and technological changes are required of this transformation, let’s first observe this paradigm shift from a bottom-up perspective.

Chapter Two: New Paradigm Shift - From Top-Down to Bottom-Up

Using the example above, a top-down approach would be using excel sheets to allot bathroom times, whereas the bottom-up approach would be using the Toilep app. When planning is initiated by those carrying out the action, it is considered a bottom-up approach.

Here are the differences between the two control systems (hierarchical control vs emergent control).

Traditional Top-down Approach

Traditional planning systems and production logistics adopt a top-down (hierarchical) approach. It breaks the production process down into applications, control, and devices. For example, the commonly used ISA 95 is a process-centric approach that focuses on top-down control. It feeds master data into production systems to define what the process does, such as business processes and factory processes. It does not have the human perspective in mind.

In the top-down approach, there is an underlying assumption that the way the work is designed stays that way. Because the system is very rigid, the decision on a system is rarely overturned.

Bottom-up Approach in the Industry 4.0 Era

In the Industry 4.0 environment, work is seen from a bottom-up perspective, a concept of emergent control. The emergence of IoT (Internet of Things) has equipped people and machines to interact at the lower level, allowing shop floors to operate with a more agile system.

This model drops the traditional hierarchies and moves away from the ISA 95. Instead of imposing how production should be processed from the top, data collected through IoT devices and shop floor workers get to determine how production should be planned and adjusted.


We know that this is a strong statement. However, the ISA 95 is not a valid model in this new era of manufacturing.

With a more human-centric approach, we can move away from processes and focus more on what humans do in the shop floor environment. The Industry 4.0 era is about enabling shop floor workers and operators to use digital technologies, which will be the source of productivity. It is the only way to stay agile in increasingly turbulent and competitive manufacturing environments.

Chapter Three: Why is Industry 4.0 Interesting?
Productivity exponentially increases as digital transformation journey moves along

Industry 4.0 and Pharma 4.0 promise an order of magnitude in productivity increase. It helps manufacturers work faster, quicker, and better at a higher quality with an order of magnitude. With the help of connected systems, Industry 4.0 catalyzes exponential growth in production efficiency in a short period.

While there is risk in adopting Industry 4.0, the benefits of a successful digital transformation journey offer the ability for your system to move faster than ever. Therefore, it is important to evaluate what digital capabilities would make the biggest impact on the business, and start with low-risk, high-growth opportunities.

As seen in the graph, the further along the digital transformation journey, the more exponential the productivity growth gets.

Chapter Four: Maximizing Productivity and Minimizing Risk in Industry 4.0

To maximize the output of the risk being taken, businesses need to first identify what digital capabilities would bring them the highest return. And in doing so, they must first identify where they are on the current production lifecycle.

What Digital Capabilities do you need?

Before we can be certain which digital capabilities will catalyze productivity growth, we must evaluate the type of manufacturing we currently have. This way, we can properly judge how digital technologies can be applied to support the business model, and strive towards a low-risk, high-growth model.

One way of doing this is by using the lifecycle approach. For example, if your plant brings on new technology — such as getting the new Covid-19 vaccine into the production cell — you are most likely at the stage of agility. You need to have an adaptable process model that can help you incorporate new technologies into the existing framework.

The chart above outlines 5 different digital capabilities by production lifecycle.

Following agility (adaptable process model), the cycle progresses in the order of:

  • getting compliance to obtain a license (consistent documentation quality)
  • quality check (repeatable product quality)
  • scaling up and increasing production volume (fulfill market demand)
  • staying competitive to produce more (optimal COGS)

Depending on the current lifecycle stage of your business, you can determine which digital capabilities you need at the moment to maximize your productivity.

Chapter Five: Addressing the Unique Challenges in your Facilities

When we talk to various plant leaders about the current state of their shop floors, it always comes down to several small challenges that amount to increasing the plant’s overall productivity. For example, the second shift might not be as productive as the first one, there might be some material variability, and a critical machine might not be set up properly because of missing parts.

A combination of small challenges that have a seemingly low impact on the overall production process are often rooted in several, critical issues that need to be diagnosed from the bottom up.

Following the identification of these small problems, manufacturers can prioritize which challenges they want to address first based on their business objectives. And based on that list of priorities, a manufacturing app can be configured to address specific needs and root causes of problems.

The key thing to note in this paradigm shift is that the digital transformation does not require the changing or replacement of existing machines, tools, and systems. Manufacturers can slowly ease into the plan, start looking at where the problems lie, and start applying digital technologies in a way that supports the operators and gives them the data they need to realize that order of magnitude in productivity.

Chapter Six: Another Step Towards a Human-Centric Approach

Apart from the bottoms-up approach, another key enabler in Industry 4.0 is this notion of democratization of digital technologies. This means that digital technologies are accessible to everyone on the shop floor, in more ways than just being available. It is easy for everyone to learn and use.

With the democratization of digital technologies, operators can manage activities and processes with an intuitive interface that is connected to the physical world around them. This is different from the traditional manufacturing systems where only those with advanced skills could operate and manage.

Let’s use a common, everyday item for comparison. Democratizing digital technology in manufacturing is the same concept as using a cell phone. You do not have to be a software expert or a mobile technician to use one. A modern mobile phone may be highly complex and advanced in the way that it is built, but practically anyone can learn how to use it within a couple of minutes. With most recent capabilities, phones have become democratized enough for everyday users to program their phones to trigger actions such as turning on lights when the sunsets. Even 10 years ago, a custom trigger like this would have required a very high level of skill and experience in automation.

Digital Manufacturing is Human Centric

In traditional Industry 3.0, the approach was to put humans aside and focus on automating processes and machines. Shop floor workers were forced to use technology as is, hence the name top-down approach. This forced many shop floors to adapt their processes to fit the systems defined at a higher level.

In Industry 4.0, this is unthinkable. The transition in technology has given way to manufacturing software that adapts to people and processes. It is no longer about looking at the process first and determining which tool can be used to support the different parts of the process.

In this new era, problems are seen from the perspective of shop floor workers and where they operate. It is about understanding the individual use cases and the daily challenges and helping the operators and workers build app solutions that interconnect with other devices. Data in the hands of operators and workers allow for a more flexible, agile production process.

If you’re interested in how Tulip can help your shopfloor take on a more human-centric approach to manufacturing, get in touch today.

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