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8 Essential Elements For De-Risking An Automation Project

Risks can enter an automation project at just about any stage. Those risks can result in serious consequences from budget and schedule overruns to unplanned downtime, disrupted supply chains, and more.

Therefore, it’s important to de-risk your automation project at every possible stage. This ensures errors are reduced to a minimum, as well as ensuring the project delivers on expectations.

We have a project delivery process at SL Controls that helps to reduce risks in all project phases. There are also factors relating to your organisation and operations that need to be considered. We’ll start with those.

Minimising Risks In Automation Projects – What You Can Do

There are five crucial areas you should look at to minimise risks in your automation project:

  1. Set clear goals – you should have a clear understanding of why you are embarking on the automation project and what you want to achieve. What are the objectives, what has to happen to meet those objectives, and how will you measure success?
  2. Senior leadership buy-in – getting senior leadership buy-in at the earliest possible stage will make the process smoother, as well as reducing risks.
  3. Resistance to change – are there people in the organisation who will resist the change that automation will bring? This situation is not unusual. The key is to ensure you have a well-thought-through plan of how you will deal with this resistance. Examples of things you can do include communicating effectively, addressing fears head-on, and offering training.
  4. Resources and expertise – what resources and expertise will you need for the successful delivery of the automation project? If you are not completely sure of the expertise that will be required, how will you get that information? What level of resources do you have in-house? What are the key skills and capabilities you will need from a third-party provider?
  5. Stakeholder communication – communication is a potential risk factor in automation projects as communication failures can lead to errors, delays, overruns, and other problems. Therefore, you need to develop an effective communication strategy that includes all stakeholders.

De-Risking Your Automation Project At Every Stage Of Delivery

At SL Controls, our project delivery processes focus on de-risking at every stage, from the pre-automation phase through to final commissioning and testing.

Central to this are eight essential elements to de-risking all automation projects.

1. Proof Of Principle

Proof of Principle (POP) involves proving the feasibility of achieving the desired outcomes for the project based on things like the technologies currently available, budget constraints, timelines, etc.

By going through the POP process, we can avoid pursuing goals or targets that are not feasible or achievable and, instead, make changes to achieve the desired outcome. This prevents wasted expenditure.

2. Design For Manufacturing

Design for manufacturing (DFM) is most commonly used when designing new products. It involves ensuring the design of a product makes it easy to manufacture within the cost target.

In relation to automation projects, we adapt DFM principles to ensure we don’t just create a fancy automation solution. Instead, our goal is to develop an automation solution that is reliable, and that improves several key metrics, i.e., OEE, output rate, quality, productivity, etc.

3. User Requirements Definition

A User Requirements Definition is a document we create that specifies what you, as our client, expect the automation project to deliver. It’s not a technical document but should include, among other things:

  • Required functions and features of the solution
  • Workflow of the solution
  • Integration requirements
  • Data requirements
  • Regulatory requirements
  • Life cycle requirements

In terms of the de-risking process, creating and agreeing on a User Requirements Definition is part of the project’s feasibility analysis. It also ensures everyone is on the same page.

4. Design Review Management

The design review is an essential part of de-risking automation projects. In regulated sectors, it’s also a compulsory part of the process and must be properly documented.

A design review tests and evaluates the design of the automation solution against the User Requirements Definition.

5. Factory Acceptance Testing

The goal of Factory Acceptance Testing (FAT) is to ensure the equipment, platforms, and components of the automation solution can deliver on requirements. It is a process that can highlight issues and errors, so it plays a key role in de-risking automation projects.

6. Logistics Management

Logistics management is often taken for granted in automation projects, despite the fact there are so many things that can go wrong, many of which can have significant consequences. A good example is a piece of equipment getting dropped and damaged. This could set a project back for weeks or months.

To mitigate these risks, we insist on using qualified and approved freight forwarders who take essential steps to ensure the smooth teardown, crating, and transportation of equipment and machinery. This includes:

  • Mapping every aspect of the route
  • Planning the equipment required
  • Deciding on the crate specification
  • Selecting appropriate bracing to secure equipment
  • And more

7. Site Acceptance Testing

While the aim of a de-risking strategy is to eliminate risks at the earliest possible stages of an automation project, the Site Acceptance Testing stage is still important. It’s also an essential GMP requirement.

8. Final Commissioning

De-risking in the final commissioning phase includes IQ (installation qualification), OQ (operational qualification), and PQ (performance qualification).

De-Risking Strategy

By emphasizing de-risking in the earliest stages and then focusing on the elimination of risks through each subsequent stage, we ensure the successful and smooth delivery of automation projects, maximising your ROI.

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Putting Quality First At SL Controls

Like most businesses, there are several values and priorities that are important to us at SL Controls. …

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Transitioning to Smart Manufacturing – A Practical and Cost-Effective Approach

The business case for implementing smart factory technologies is compelling, with tangible improvements in revenue, output, quality, and safety, alongside reduced costs. It is not surprising, therefore, that smart manufacturing technologies are becoming an increasingly important competition driver.

The technologies that are part of the Smart Factory include cloud computing, edge computing, vision systems, robotic process automation, predictive analytics, machine learning, artificial intelligence, big data, and industrial internet of things, as well as augmented, virtual, and mixed reality.

Each one individually has significant potential and creates opportunities for your business. When combined, the benefits increase considerably.

Implementing smart manufacturing solutions is not without risk, however, so where do you start? If you’ve already started, where do you go next? What are the practicalities of making the transition to smart manufacturing?

Transitioning to Smart Manufacturing

 

Important Practicalities to Consider

There are some important practical considerations to think about before embarking on major smart manufacturing projects. Many of these considerations relate to change management and include ensuring there is senior leadership buy-in, sufficient skills available for the initiative, and support for those involved.

Other considerations include the divide that sometimes exists in many manufacturing organisations between IT and OT. The success of smart manufacturing initiatives often hinges on these critical business functions working together.

Two other important considerations are worth mentioning:

  1. Integration – you will have different machines, equipment, devices, sensors, platforms, and systems that make up your manufacturing operations and supply chain management processes. The integration of these various technologies and machines is an important step.
  2. Connectivity – connectivity and the transfer of data are crucial to the implementation of smart manufacturing solutions, so it is essential to have a robust IT infrastructure to provide the required level of connectivity.

Finally, it is important to focus on business value when deciding on strategies and implementing smart manufacturing solutions. Without a proper focus on business value, improvements can be made in specific areas, but the benefits won’t extend much further. The best approach is to look at the overall objectives of the business to decide on the smart manufacturing technologies that offer the most value.

15 Technologies Transforming Manufacturing

 

Progressing Towards a Smart Manufacturing Approach

You need to move to the next stage of your smart manufacturing journey, but what should you do first? How do you ensure you don’t take missteps? How do you progress without diverting significant resources? Can you get a short-term and medium-term return on investment as well as a long-term return?

Let’s look at three key strategies:

  1. Trial projects
  2. Structured incremental implementation
  3. Simulation tools

A combination of the three, depending on the status of your existing operations, is often the best approach to keep costs under control, maximise return on investment, and ensure the transition is as smooth as possible, particularly in relation to product output and customer impact.

Trial Projects

Trial projects can be a useful approach in a wide range of situations, not just at the start of your Smart Manufacturing journey. With a trial project, you can ringfence costs and structure the work parameters as tightly as you want.

This will let you identify risks and areas for improvement, and it will demonstrate where you may encounter resistance, bottlenecks, or barriers when you start to scale up.

In addition, a trial project will give you a better indication of the real return on investment you can achieve from transitioning to Smart Manufacturing.

Structured Incremental Approach

Whether you go with the trial project option or not, adopting a structured, incremental approach is almost always the best option.

How far you go and how quickly depends on your current circumstances and immediate plans. For example, it might save you in the long run if you increase the scale of a project if it requires a considerable investment in new equipment.

It’s important you don’t go too far too fast, however. Upgrading all your legacy systems in a short period of time is rarely the best option, for example. Rather than a big bang investment, the more successful approach is usually a carefully planned evolution.

The most obvious reason for this is the fact it might not be practical, for financial or other business reasons, to upgrade all legacy systems in a short space of time. Furthermore, it might not even be necessary, i.e., you might not need to upgrade all your legacy systems to achieve your Smart Manufacturing goals.

Simulation Tools

It is also possible to explore and analyse the implementation of Smart Manufacturing processes and technologies in your facility using simulation tools. One of the most effective is using digital twins.

By creating digital twins of your current equipment and processes, you can model various options and scenarios to identify the best approach, helping you decide on the next Smart Factory steps to take.

Starting and Continuing the Transition

Smart Manufacturing may be a buzzword, but the technologies involved are driving transformational change in manufacturing companies in all sectors, including the life sciences sector. Companies that take a strategic approach and continuously improve their operations with new smart factory initiatives will be best placed to respond to the needs of the market today and in the future.

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The Business Case for Smart Manufacturing

Advances in Smart Manufacturing technologies are changing the manufacturing sector forever. However, those technologies don’t change your core priorities and goals.

New technologies or not, you still need to deliver high-quality products that your customers need and want, plus you must maximise competitiveness, productivity, and profitability.

Marrying up a transition to Smart Manufacturing with your goals and priorities is not always easy.

We have looked at specific, practical, and cost-effective approaches to implementing Smart Manufacturing solutions and moving your production lines forward in other blog posts. A good starting point, though, is to consider the business case for doing so.

Of course, you will probably need to develop a specific business case for your facility. However, buying into the high-level pitch for Smart Manufacturing is an important first step.

Smart Manufacturing – The Business Case

The Business Case for Smart Manufacturing

 

As a component of Industry 4.0, Smart Manufacturing centres on digitalising manufacturing businesses and improving the ability of people and connected devices to work together.

The reality is the technologies that make smart manufacturing possible will have an impact on your business. This impact applies however quickly you proceed and how far down the Smart Manufacturing route you go in the near term.

Even if you do nothing regarding the implementation of Smart Manufacturing technologies in your facility over the next 12-24 months, by not moving forward, you risk falling behind or missing opportunities that could be beneficial to your business.

Why? Many of the challenges and opportunities that are becoming more important to the manufacturing sector are being driven by market trends, advances made by your competitors, regulatory requirements, and changing consumer behaviour and expectations.

Here are two examples by way of illustration:

Mass Customisation

Smart manufacturing technologies make it possible for manufacturers to move towards the mass customisation of products. This mass customisation trend will change the offering that is available to the consumers and users of the products you produce. In fact, marketplace expectations are already changing.

While industries like pharmaceutical and medical device manufacturing are not as far advanced as other industries, the direction of travel is firmly towards mass customisation. Manufacturing flexibility is increasingly important too.

New Product Introductions

The practical and regulatory requirements for introducing a new product on the market are as complex today as they have ever been. However, Smart Manufacturing technologies throw an important consideration into the mix.

Specifically, Smart Manufacturing technologies streamline and automate many NPI processes. Therefore, organisations that embrace Smart Manufacturing solutions will introduce new products faster while maintaining compliance and quality standards. This reduced NPI timescale greatly enhances competitiveness.

The Sooner the Better

The above are just two examples of the many ways that Smart Manufacturing can (and is) impacting your business. So, the summary is the sooner you get started with implementing Smart Manufacturing solutions, the better.

How you do that will depend on your business. The process requires a detailed assessment of the readiness of your organisation, as well as an analysis of where first to target Smart Manufacturing solutions with a focus on maximising improvements, delivering a healthy return on investment, and ensuring scalability for the future.

Benefits of Smart Manufacturing

  • Improvements in OEE – overall equipment effectiveness.
  • Increased efficiency, but not just in the operation of machines and equipment. Smart Manufacturing technologies also enable the more efficient use of resources, as well as delivering material efficiency benefits and helping make your operations more energy efficient.
  • Reducing both planned and unplanned downtime through digital twin technologies, machine learning, and predictive analytics.
  • Improved quality control.
  • Opening up the potential of new business opportunities with the introduction of new product lines, mass customisation strategies, and more.
  • More effective and efficient regulatory compliance processes.
  • Increased output that will improve revenues and profits while also delivering capital expenditure avoidance.
  • Improved customer satisfaction by consistently and reliably delivering high-quality products, in addition to responding quickly to queries and complaints.
  • Building a closer direct connection with your customers.
  • Increasing the variety of products that you can produce on a single production line.
  • Overall improvements in productivity.
  • Enhanced insight at all levels of the business, from supply chain management to how customers use products to predicting future market demands.

Drivers for Transitioning to a Smart Factory

When making a business case for Smart Manufacturing, it also helps to understand the drivers of change. Some of the most important of these drivers include:

  • Customer demand and expectations – these constantly evolve, with one major current trend being mass customisation. Market factors that increase or decrease demand unexpectedly and/or in short periods of time are also factors.
  • Agility and flexibility – i.e., ensuring your business is in a position to take advantage of the new opportunities that Industry 4.0 and Smart Manufacturing technologies present.
  • Productivity and improving OEE – the constant push to improve performance and efficiency, particularly in the face of increasing demands.
  • Availability of skills and resources – many businesses in a range of industries struggle to recruit and retain the operatives and technicians they need, so they are looking to technology as the solution.
  • Compliance – additional compliance requirements on manufacturers, particularly in highly regulated sectors like pharmaceuticals and medical device manufacturing, results in a push for innovative solutions. Some of this comes from regulators, but manufacturers striving to keep compliance costs under control are also a factor.
  • Business opportunities – Smart Manufacturing technologies have the potential to transform businesses, creating opportunities in new markets, product development opportunities, business model innovation, and more.
  • Sustainability – sustainability is increasingly important in all businesses. Smart Manufacturing technologies can increase energy efficiency and reduce waste across the entire product lifecycle.

Drivers for Transitioning to a Smart Factory

 

Getting Started with Smart Manufacturing

The business case for Smart Manufacturing is strong, although the way it is presented and tailored will differ depending on your organisation. To move to the next stage, find out more about the practical and cost-effective ways to transition your current facility using Smart Manufacturing processes, methods, and technologies.

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Infographic: Computer System Validation Vs. Computer Software Assurance

The FDA (US Food and Drug Administration) is due to release guidance on Computer Software Assurance. That guidance aims to put critical thinking at the centre of Computer System Validation (CSV) processes.

In our latest infographic, we highlight the main differences between traditional CSV and the new Computer Software Assurace (CSA) approach.

Infographic Computer System Validation Vs. Computer Software Assurance

 

Traditional CSV

  • Perceived as a barrier to automated solutions and innovation
  • All software validated as if it’s product software
  • The primary focus is securing evidence for auditors
  • Duplication of vendor documentation and effort
  • High occurrence of deviations due to tester error

New Computer Software Assurance

  • A more flexible, less burdensome, and faster risk-based approach
  • Various assurance approaches depending on the system/feature risk
  • Apply critical thinking to ensure the software is safe and meet its intended use
  • Reduced testing activities resulting from better supplier qualification and collaboration
  • Reduced number of deviations due to tester error
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Is Your Company Ready for the FDA’s Upcoming Guidance on Computer Software Assurance?

Technology and computerised systems have evolved greatly over the past 20 years. In that time, cloud computing has become mainstream, and big data is here. When you also add the fourth industrial revolution (Industry 4.0), it’s clear that new manufacturing and business technologies will be truly transformative in the coming years.

Yet, in the Life Sciences industry, the uptake of new automated solutions and technologies has been slow relative to other manufacturing industries. It is a trend that regulators have been seeking to fix.

The FDA’s Case for Quality initiative was set up to promote industry collaboration and encourage innovation, automation, and digital technologies. By working with those in the industry, the FDA was able to identify best practices and learn the barriers that exist for manufacturers.

It quickly became apparent that CSV, as it is applied today, is perceived as a barrier to technology implementation, where companies produce excessive, non-value-adding documentation that is driving longer validation cycles and increasing expenses.

Manufacturers are reluctant to invest in highly automated technologies as the validation cost is so high. It has become clear that the approach to validating such computer systems has not kept pace with technology advancements.

Enter Computer Software Assurance (CSA), the FDA’s upcoming guidance that aims to place critical thinking at the centre of the CSV process.

Is your company ready for the FDA’s upcoming guidance on Computer Software Assurance

 

What is CSA?

Computer Software Assurance is a risk-based approach to computerised systems that is product quality-focused and patient-centric. It encourages critical thinking based on product knowledge.

The FDA, recognising that CSV has become a barrier to technology, is releasing the new guidance to tackle the issues faced by manufacturers, while also offering greater flexibility in achieving software assurance.

The guidance highlights new ways of approaching non-product software, i.e., QMS, ERP, PLM, MES, LIMS, etc. It states that assurance activities should be value-driven, patient-focused, and streamlined using existing technologies such as automated testing tools.

Here are some areas that the new guideline seeks to address.

Risk-Based Approach

A risk-based approach to validation is not a new concept. However, regulated companies have struggled with balancing the overall validation effort based on the software risks identified. As a result, companies fall into the trap of applying a one-size-fits-all CSV approach, where lower-risk systems are evaluated to the same scrutiny as high-risk systems. This approach produces a burdensome level of documentation, drives longer validation cycles, and increases expenditure.

The new guidance advocates a risk-based validation approach and also switches the focus from validation to assurance.

How will this affect you? One of the main areas is that there will be a significantly reduced validation requirement for software applications that have no direct impact on product quality or safety. In this situation, the recommendation from the FDA is to use current processes like the qualification of suppliers, as well as risk-mitigating process controls.

Vendor Qualification

Even with an audited or trusted vendor, regulated companies still tend to reproduce documentation and test out-of-the-box software functionality that has already been tested by the vendor. Under the new guidance, if a vendor’s documentation is deemed to be of good quality, efforts should focus on ensuring the software meets its intended use rather than reproducing documentation for the sake of audit readiness.

Testing

With traditional CSV, regulated industries have adopted a conservative approach to testing, where too much focus is on documentation, manual testing, and evidence gathering. It is common to see this robust and scripted test approach applied to every system and function, regardless of its associated risk classification.

There is more flexibility with the assurance approach that CSA facilitates, as well as flexibility with acceptable records of results. There is also the introduction of the terms Scripted, Unscripted, and Ad Hoc Testing.

Scripted Testing

Scripted testing is widely used today in traditional CSV. It contains test objectives, step-by-step test procedures, expected results, independent review, and approval. CSA guides companies to continue using Scripted testing but only for high-risk features of a system that directly impact the product or patient safety.

Unscripted testing

An Unscripted test is testing without detailed instructions but with a clear objective and pass/fail criteria. Unscripted testing is to be used to test lower risk features of a system. Importantly, Unscripted testing still means you have to test, and details of test failures should be recorded as normal.

Ad Hoc Testing

Ad Hoc testing is similar to Unscripted Testing but does not require pre-approved protocols. This assurance approach may be in the form of exploratory testing, and it is considered the least-burdensome assurance option. It should be used for low-risk systems.

Efficiency Savings that Will Increase Innovation

By applying critical thinking and a risk-based approach, these assurance processes can be easily implemented on a feature-by-feature basis, as shown by the simple example illustrated below.

Risk-Based Assurance Process

 

Unscripted and Ad-Hoc testing are seen as the right level of documentation for medium to low-risk features. CSA will consider these approaches to be an acceptable record or results. It is expected this new approach will result in a 30 – 50% reduction in time and costs, so it will therefore increase and accelerate innovation.

Preparing for CSA

The new CSA guidance is expected to be released in the coming months. The FDA has stated that companies can (and should) proactively take these principles into consideration. The recommendation is to create a transition plan and to pilot new methodologies on a subgroup of systems before rolling out to your entire organisation.

For some companies, moving to CSA will be a cultural shift compared to the current way of doing things. It is therefore critical the quality leadership team embrace CSA to enable its adoption throughout the organisation.

Now is also the perfect time to leverage automated testing and continuous data monitoring tools to streamline assurance activities that the new guidance supports.

Conclusion

Digital transformation is gathering pace in the life sciences industry due to Industry 4.0. The COVID-19 crisis is also spurring on innovation.

Traditional CSV practices are no longer compatible with emerging automation and digital technology solutions. It is time to implement a streamlined validation approach based on critical thinking that will support Industry 4.0 and will ultimately drive better patient outcomes and faster time to market.

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How Industry 4.0 Supports Flexibility and Mass Customisation

“Any customer can have a car painted any colour that he wants so long as it is black.”

That’s a quote from Henry Ford, the founder of the Ford Motor Company. It’s a famous quote, but what does it have to do with flexible manufacturing and mass customisation? Does it have any relevance in the era of Industry 4.0 as we look towards the next industrial revolution, Industry 5.0? Is there anything we can learn from an idea that appears so outdated?

According to his autobiography, Ford made the famous comment in a meeting with his team in 1909. The comment was part of an announcement that the Ford Motor Company would, from then on, only be making one model of car – the Model T.

Ford’s thinking at the time was clear. In another part of his autobiography, Ford writes:

“No business can improve unless it pays the closest possible attention to complaints and suggestions. If there is any defect in service then that must be instantly and rigorously investigated, but when the suggestion is only as to style, one has to make sure whether it is not merely a personal whim that is being voiced.”

So, Ford’s approach was to get the design of the product right and then manufacture that product and that product alone at a massive scale.

It was a successful approach, too. When he made the famous “any colour so long as it’s black” quote, Ford was producing just over 10,000 cars a year. Ten years later, the company had produced half-a-million Model T Fords, and five years after that, it was producing two million.

100+ Years On

Industry 4.0 technologies are changing the reality from Ford’s era unlike any other technologies that have come before. Today, for example, it is now possible to meet the demands of customers for product customisation while also getting the design right.

In the life sciences sector, that means customised medicines, therapies, and medical devices that meet quality standards and regulatory requirements, while also being economical to produce.

It’s also possible to have a flexible production process where different products with different tools and moulds can be produced on the same production line.

For example, dynamically programmed robots with interchangeable tooling enable manufacturers to quickly and effectively switch between models manufactured with negligible efficiency loss.

Industry 4.0 technologies, processes, and ways of thinking make this possible.

Crucially, it’s also possible to do all the above while maintaining productivity and operational efficiency. As a result, new profit-making opportunities become a reality.

What is Mass Customisation?

Mass Customisation - the ability to manufacture what the customer wants profitably and with no loss of productivity

 

Mass customisation is the ability to manufacture what the customer wants profitably and with no loss of productivity. The aim is to make the manufacturing process more customer oriented.

What is Flexible Manufacturing?

Flexible Manufacturing - production lines that can quickly and easily change the type of product being manufactured

 

Flexible manufacturing is a manufacturing strategy involving production lines that can quickly and easily change the type of product being produced. The process of switching between product types is automated.

The Technologies Driving Change

Back in Ford’s day, designers designed products with minimal input from consumers. Engineers then worked on refining the design and getting the production processes right, in addition to making sure the production process was as effective and efficient as possible.

The product then left the production line and entered the distribution chain, with little connection between it and the factory floor.

In other words, the connection between the customer, the manufacturing process, and the design process, was minimal. The supply chain was also disconnected and disjointed.

Industry 4.0 turns this completely on its head. Sensors and communication technologies mean machines in the production line can interact, collect data, and issue instructions autonomously. These processes can be integrated with the supply and distribution chains, connecting other business units, and driving efficiency savings even further. Supply chain collaboration and oversight, product traceability, OEE optimisation, and more happen in real-time.

However, the real gamechanger when it comes to flexibility and mass customisation is the use of sensors in end products. With this technology, manufacturers can create digital twins of products that are being used by customers in the real world, with the digital twin receiving real-time updates from sensors on the physical products.

Digital Twin - a digital replica of a product or process updated in real-time with real-world data

 

Non-Linear Product Lifecycle

Digital twin and simulation technologies offer a number of benefits to manufacturers, including predictive maintenance and making faults easier and faster to repair.

One of the biggest benefits, however, is how the use of sensors and digital twin technologies can influence the design process. Product designers no longer have to rely on gut instinct, limited research, or outdated usage data.

With Industry 4.0 technologies like digital twins, designers can use real-time data to produce products that customers really want.

In other words, the product lifecycle becomes non-linear.

A non-linear product lifecycle makes it possible to customise products for different customer segments, improving customer relations and the customer experience. Even single-unit production runs are possible, i.e., true product personalisation.

Mass Customisation Gets You Closer to Your Customers

Remaining competitive and relevant to your customers is essential, as is improving the customer experience, from the service they receive to shipping lead times to product quality.

Arguably, however, the most eye-catching benefit of mass customisation and manufacturing flexibility has to do with the relationship you have with customers. Industry 4.0 technologies, as well as mass customisation and flexible manufacturing strategies, get you closer to customers.

As a result, you can establish a more robust direct link with customers, strengthening your brand, building customer loyalty, improving customer and marketplace knowledge, and ensuring you stay out in front of emerging trends, changing values, and evolving expectations.

What Can We Learn from Ford’s Famous Quote?

There is a connection between Ford’s approach in the early 1900s and the opportunities presented by Industry 4.0 today. Specifically, two of the biggest things that Ford got right back in 1909 was to:

  • Focus on the customer – he understood that the vast majority of his customers preferred to have a reliable car they could afford rather than one where they could specify a particular colour.
  • Focus on profitability – Ford also understood he had to deliver on the above expectations of his customers in a way that was profitable for his company.

Hence, the get-it-right-and-then-make-them-all-the-same approach.

Manufacturers need to follow Ford’s lead, albeit with a 21st-century twist.

  • Focus on the customer – customers still want products that work, and they want those products to be affordable, but they also want products tailored to their needs, i.e., they want customised products.
  • Focus on profitability – manufacturers need to offer flexibility and customisation to remain competitive, but they must do so profitably.

Industry 4.0 technologies make both the above possible: sensors, automation, robotics, machine learning, data analysis (particularly anomaly detection), digital twins, equipment integration, and more.

It is manufacturing’s next evolutionary step, as Industry 4.0 technologies, processes, and systems become the norm, and we start moving towards Industry 5.0.

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