Skip to content

Chapter 2

Key opportunity 1. Quality of the manufacturing process.

Aidet by the industrial internet of things.

Quality control is the process that ensures customers receive products that are free from faults, and meet their needs. If this is done wrong, it can put customers at risk. Quality control is important everywhere — especially in the manufacturing industry. But why exactly is this? Why is it a good idea to produce the highest-quality products you can, and why is it essential to have a system in place to ensure this happens?

Problem defenition

Good quality management relies on the ability to constantly monitor and control a host of machine and process parameters that impact product quality. To make sure that product properties are constitently up-to-par, equipment recalibration is constantly performed as process drifts and other changes in the production line crop up. With the increasing complexity of tooling systems and processes, many process variables are left unattended due to the limits of bulky wired networks. A large part of wired-driven industrial systems aren’t intended for data exchange beyond the factory floor, which results to disconnected islands of data. This data couldn’t be used to stimulate production efficiency and throughput.

Quality management and optimization of processes often depend on reactive, manual post-production inspection. Besides human intervention, this introduces significant quality variability and associated costs while making it challenging to trace the root cause of quality issues.

During the process, many production issues can occur. Think for example of not the right quality, long lead times, high on-hand inventory and supply chain interruptions. These all affect the product that you want to produce, which eventually can affect the perception of your brand. We’ve placed the most common problems in four categories:

  1. Quality problems:
    High defect rate, high return rate and poor quality.
  2. Output problem:
    Long lead time, unreasonable production schedule, high
    inventory rate, supply chain interruption.
  3. Cost problem:
    Low efficiency, idle people or machines.
  4. Management problem:
    Bad working conditions.

Industrial internet of things

The pressing quest for improved process visibility speaks to the tremendous potential of IoT. Wireless instrumentation isn’t necessarily new to manufacturing, but most legacy solutions fail to live up to crucial requirements in terms of range, power and ease of integration in industrial operations. A new generation of IoT connectivity delivers not only industry-grade reliability and security for dependable communications, but also a high level of scalability, cost-efficiency, and interoperability needed to overcome the manufacturing inertia.

Wireless IoT networks that can capture vast, granular critical data points along the production line, render manufacturers with unprecedented control over their operations and product outputs. Beyond reactive, end-of-run quality inspection, IoT data empowers a proactive quality assurance approach to diagnose and prevent defects much earlier in the process for peak production throughput and repeatability alongside reduced costs and waste. Concurrently, it provides valuable insights for achieving and maintaining storage best practices.

With 24/7 remote monitoring, quality managers can instantly detect off-spec conditions among running equipment and processes that give rise to potential product defects. A prompt following quality check helps to reaffirm the problem at the source and facilitate troubleshooting to hinder future defects.

Once different quality problem sources have been diagnosed and verified, manufacturers could even develop and implement a quality control model to further optimize product properties. Capitalizing on ongoing sensor inputs, such a model allows machine operations to automatically adapt to unwanted fluctuations in variables like environmental conditions, to achieve the top and consistent product attributes.