For continuous improvement and quality managers considering digitalization towards the Factory of the Future and Industry 4.0, our article explores the crucial importance of stakeholder alignment in investment decisions. Managing consensus, overcoming risk aversion, and addressing increasing demands for customization are essential aspects to ensure the success of this evolution through AI. Dive into our advice on balancing innovation and stakeholder satisfaction in this transition towards optimized and connected industrial operations. And if you're wondering what politics has to do with it: you can immediately go to the conclusion. You will find the elements of this article there!

Key Stakeholders

We often find the following interlocutors at Scortex in different stages of innovation and investment projects, from their ideation to their production monitoring. Obviously, some of our clients have more "lean" organizations and have thus concentrated these roles.

1.      Recommend:

·        Continuous improvement manager.

·        Production manager.

·        Quality manager

2.      Approve:

·        CFO.

·        Quality director.

·        Operations or industrial director

3.      Implement:

·        Project manager.

·        Operational or implementation team.

4.      Contribute:

·        Operators in the field.

·        Specialized technicians.

·        Data analysts.

5.      Decide:

·        CEO.

·        Plant manager

·        Management committee.

·        Board of directors.

Investment Objectives

In the complex context of industrial operations, project objectives clarity is the cornerstone of successful alignment among stakeholders responsible for validating and driving the project. It ensures that every quality improvement initiative fits perfectly into the company's long-term objectives, thus promoting optimal use of resources and efforts.

In terms of quality assurance, clear operational objectives are essential to ensure compliance with industrial standards. These quantifiable criteria provide a framework for assessing the effectiveness of quality processes. For example, in some of our clients, a precise definition of key performance indicators (KPIs) and their threshold values (acceptable, drift, non-acceptable) has led to a significant reduction in non-conformity rates in the first year through an automated alert system for consecutive defect detection. This approach is integrated into rigorous project management, including detailed planning, continuous monitoring, and strategic adjustments to ensure the achievement of set objectives.

Similarly, in aspect control, specific objectives are necessary to ensure high standards of finished product quality. For example, at an automotive plastic injection industry client, the implementation of a Spark control system has reduced scrap rates by 3 times. This success is the result of effective project management, integrating close coordination between production and quality control teams, constant monitoring of performance indicators, and flexibility to adapt strategies based on results. Setting quantified objectives within a well-structured project management framework allows for quickly measuring the relevance of investment and validating subsequent phases.

Communication and Transparency

With the proliferation of communication channels such as emails (sometimes with more than 1000 unread emails in certain inboxes), chats, and phone calls, it is imperative to recognize the crucial importance of transparency in communication with all stakeholders. This transparency plays a vital role in project success and in establishing strong relationships, whether internal or external to the organization. Maintaining open dialogue throughout the decision-making process is fundamental to ensure alignment of objectives, foster engagement and collaboration, and minimize risks of misunderstandings or potential conflicts.

Moreover, establishing regular project rituals between clients and suppliers is of paramount importance in effectively managing projects. These periodic meetings offer a valuable opportunity to discuss progress, encountered obstacles, and necessary adjustments. They also help cultivate a common understanding of project objectives and strengthen trust among stakeholders.

In parallel, the introduction of a mid-project "senior review" represents a strategic essential step. This review, involving key stakeholders, including respective management of stakeholders, aims to assess progress, identify potential risks, and adjust strategy accordingly. This approach ensures continuous strategic oversight and high-level support throughout the project.

Risk and Opportunity Analysis

Stakeholders, especially industrial integration and machine retrofit teams, bring essential expertise in identifying and analyzing risks and opportunities related to investment. Their in-depth knowledge of industrial processes and existing equipment allows them to identify potential risks related to the integration of new technologies or machine retrofits.

By integrating the Failure Mode and Effects Analysis (FMEA) methodology, they rigorously assess the risks associated with these changes, identify critical points, and propose suitable solutions to ensure project success. This close collaboration promotes proactive risk management, implementing effective preventive and corrective actions to secure investment and maximize its profitability potential.

For example, in an FMEA concerning the integration of a vision system into a packaging machine, several risks can be identified:

1.      Hardware failure: Components of the vision system (camera, lighting, sensors) could have technical failures, leading to production interruptions.

2.      Software incompatibility: Compatibility issues between the vision system's PLC and the packaging machine's PLC could arise, leading to malfunctions or data processing errors.

3.      Inadequate calibration: Incorrect calibration of the vision system could lead to inaccurate measurements or wrong decisions, affecting packaging quality or operation precision.

4.      Connectivity failure: Connectivity issues between the vision system and other machine components (PLCs, actuators) could occur, resulting in production delays or unexpected stops.

5.      Personnel training and skills: Inadequate training of personnel responsible for using and maintaining the vision system could lead to handling errors or problems diagnosis.

6.      Data reliability: Errors in data acquisition, processing, or interpretation by the vision system could lead to incorrect decisions or product defects.

By identifying and evaluating these various potential risks, FMEA enables the implementation of preventive and corrective actions to reduce their probability of occurrence or their impact on the packaging machine's operation.

Thus, the supplier's expertise and experience in vision system and its support for factory project teams are critical in reducing the levels of risk severity mentioned and therefore in the teams' ability to obtain approval for the automation project launch.

Return on Investment and Value Creation

In the context of an investment in quality control digitalization, measuring return on investment (ROI) should be done according to the total cost of quality axis.

The project team examines potential savings resulting from the reduction of non-quality costs, such as:

·        scrap,

·        product returns,

·        repairs and recalls.

Moreover, they evaluate gains in terms of

·        customer satisfaction,

·        loyalty and brand image,

·        productivity improvements by reducing associated quality control manpower

·        operational efficiency by increasing production capacities and rates

By integrating these elements, they can determine if the investment has generated the expected benefits and contributed to optimizing the company's quality-cost ratio.

Real-time Data: Your Best Asset for Project Success

The use of quality data visualization is crucial for monitoring sorting performance during qualification phases and fostering continuous improvement. By accessing quality data in real-time through a dedicated web platform, teams can access customized dashboards, detailed analytical reports, and even images of inspected parts from anywhere, providing a comprehensive view of sorting performance.

Furthermore, with automatic storage of inspection reports, traceability of inspected parts is ensured, thus offering increased transparency and better quality process management.

This allows proactive monitoring of key performance indicators and rapid identification of emerging trends or issues. This approach facilitates collaboration between internal teams, the supplier, and even the end customer, fostering a culture of continuous improvement and enabling constant optimization of production processes.

Finally, the integration of a visual inspection solution capable of generating detailed images of each part with unique part traceability via a data matrix represents a major advancement in quality and traceability management in industrial environments. By combining these two technologies, manufacturers can benefit from granular quality monitoring throughout the production process. Each part is uniquely identified through a data matrix, and the information associated with this identification is directly linked to the control reports stored in the MES system. This approach provides complete visibility into the quality of each part, facilitating early defect detection, informed decision-making, and continuous process improvement. Moreover, it ensures precise and reliable traceability, thus meeting regulatory requirements and ensuring the quality of the final product.

 Conclusion

In a world where politics seems to intrude into every aspect of our lives, you might wonder if it also has a place in the field of continuous improvement in industrial quality. Well, the answer is rather amusing: no, you don't have to engage in politics to succeed in a continuous improvement project, but you will have to juggle with another type of politics, that of stakeholders!

Indeed, for your industrial quality improvement project to be successful, it is essential to align all stakeholders, from the continuous improvement manager to the CEO to the operators in the field. Managing consensus, overcoming risk aversion, and addressing customization demands are all challenges to ensure a smooth transition to the Factory of the Future and Industry 4.0.

Once key players are aligned, it is crucial to define clear and measurable investment objectives. This ensures that every quality improvement initiative effectively contributes to the company's long-term objectives while maximizing the use of available resources.

Transparent communication also plays a vital role in project success. With the proliferation of communication channels, it is essential to maintain open and constant dialogue with all stakeholders. Regular project rituals between clients and suppliers as well as a mid-project "senior review" can greatly contribute to ensuring continuous alignment of objectives and quickly resolving potential conflicts.

Finally, risk and opportunity management is essential to secure investment and maximize its profitability potential. The use of FMEA helps identify and assess potential risks related to the integration of new technologies, while return on investment analysis should take into account not only cost savings but also intangible benefits such as customer satisfaction and brand image improvement.

So, although politics may sometimes seem inevitable, in the world of continuous improvement in industrial quality, it's rather the art of juggling with stakeholders and navigating between risks and opportunities that leads to victory!

As for Scortex in all of this: we have been navigating between Large Groups and SMEs for 7 years, helping our interlocutors in project teams to always have reliable inspection solutions at hand, generating real-time data and thus visibility. Boardroom control towers have a new asset: real-time quality data!

Here are other articles that might interest you:

·        Our use case: electronic printed circuits

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·        The applications of automated quality control with AI in the cosmetics industry