Executive summary

A playbook drives a game plan

As a playbook, this resource provides a situational analysis and actions based upon the manufacturing sequence. It describes how the elements of a manufacturing facility interact and which skills, tools and practices support effective cost control. This is presented as a “game” with a sequence of play defined as “Input-Process-Output.” Understanding the sequence provides insight into how efficiency is affected across the sequence. Actions out of sequence embed and even increase variables that that reduce efficiency.

As a guide, this resource describes a journey from manual to mechanical to automated to digitally integrated manufacturing (also known as Industry 4.0). Each leg of this journey is associated with skill sets, practices and technologies. In particular, the pathway is marked by technology — machinery, equipment, software and hardware. Manual and mechanical manufacturing are skills and practices that are relevant building blocks for skills and practices in automated and digitized environments.

Role of technology

The roadmap

The stages of technology that must be adopted (in order) are:

• manual technology
• mechanical technology
• automated technology
• digitized technology

Adoption of manual and mechanical technologies is part of the input stage adoption of automated technology is part of the process stage and adoption of digitized technology is part of the output stage.

Since the 1990s, building equipment, tools and machinery included semiconductors. Since 2010, the digital integration of these components has become cost-effective. What is less well known is that the skills, tools and technology used in Industry 4.0 emerged as a solution to what industry experts call the noise (un-defined costs) and failure modes (where systems or processes fail to perform consistently). While digital traceability, inventory, sales and building operating systems have become commonplace, factory operating systems in food processing establishments have yet to catch up with how to use digital technology to drive efficiency and environmental performance.

The game plan is a priority sequence from inputs to process to outputs. These are the order of implementation for the skills, best practices and technologies that help optimize efficiency along your journey. The machinery and equipment have undergone changes over the past few decades. The mechanics and engineers of the industrial revolution either built their machinery and equipment or had one degree of separation between themselves and the inventors. Today, the trades and engineering staff that work in manufacturing are trained and recruited from groups that are further removed from the professions that build equipment and machinery. That gap has an effect. A trades person with excellent skills for maintaining mechanical equipment may not have the tools and training to maintain automated equipment. The piecemeal introduction of automated equipment in a factory often leaves facility management without the ability to manage productivity as the rules for ensuring equipment reliability and equipment efficiency which govern productivity. New equipment is computerized, and computerized machines require additional skills and tools to ensure their reliability and efficiency. In this document, the additional skills and tools are referred to as foundational technologies. These are tools and skills that enhance (not replace) the skills and tools already in place.

Adopting solutions

Since the 1990s energy, water, waste management, environmental compliance and logistics costs have risen faster than inflation. At the same time, equipment has become increasingly computerized. As businesses grow, costs increase and computerization accelerates; efficiency gets more complex.

For example, an existing technology or process needs replacement. New machinery fitted with semiconductors would improve labour productivity and worker spacing but would also increase utility costs. Doing nothing is a competitive risk. Investing in the new machinery is also a risk that differs from machinery investments in the 1980s and 1990s when mechanical equipment was replaced with automated equipment. Today’s digitized machinery needs power quality conditioning equipment to avoid failure mode-linked power quality events which happen frequently. These events can trigger a range of costs that wipe out expected efficiencies. A power quality event is a micro-interruption in the quality of electricity that occurs regularly. Just like we use power quality conditioning for desktop computers to avoid the blips that can shut down a computer, modern machinery needs the same protection. A more fulsome discussion of power quality issues is described in the playbook for inputs.

The intention or guiding principle of manufacturing is to achieve efficient production. That means the productivity of the facility can meet sales demand and production is efficient and profit is the result of selling what is made. To achieve this the equipment, machinery and labour that are used to make product must meet two criteria:

• Machinery must be efficient. Input and waste management costs are manageable and ensure a margin for profit.
  • The cost of running process equipment and support systems
• The system (equipment, machinery and processing lines) must be reliable. It needs to run when and as expected.

The adoption sequence for foundational technologies and process technologies discussed in this playbook address the pieces that are often missing in today’s manufacturing facilities along with the skills and tools you need to ensure the system reliability and system efficiency that will help you hold your margin.

Beyond a factory’s walls the market (customers and consumers) and government expect industry to be environmentally sustainable. How your productivity improvements translate into environmental performance is also a marketing and environmental performance story. The same digital systems you use to optimize production processes can be used to support these needs, using some of the same data when you have the foundational measurement technologies in place.

There can be as much risk with doing nothing and maintaining a status quo as there is with adopting new solutions, until you understand the roadmap as a methodology.

Plan for performance

The objective of the guide is to also help you understand how to plan for performance and maintain your advantage. It lays out a game plan for special team composition, training, skills, tools and technology to drive scalable financial and environmental performance. Beginning at a common starting point, it utilizes a method that targets variables which escalate between people, machines and processes to avoid detrimental effects.

The sequence of steps in this guide is based upon foundational technologies, skills and best management practices (BMPs). These steps are best practices that are consistent and repeatable on the journey from manual to mechanical to automated and, finally, to digitally integrated manufacturing. At its heart, the guide addresses efficiency like a science experiment. It is based upon the law of causality, where effects never precede their cause (for example, a clean and dry floor reduces accidental slips and falls). Translated into business terms, the methods used to control variables is a consistent process which leads to consistent financial performance.

Across each transformation the first set of steps focus upon input variables. The second set of steps control process variables. The third set deals with output variables. This sequence (or method) is important because it follows how noise affects first the reliability, then the efficiency of equipment in a processing system and finally the noise equipment transfers to linked equipment. A clue to why this approach works is based upon understanding what the ratio of impact is between an individual piece of equipment and the system it works within. It has been suggested that 40% of the operating efficiency of any single piece of equipment is linked to the efficiency of the system to which it is attached. This suggests local noise is 60% of the efficiency equation and continuous noise is 40%. Foundational technologies used to manage local noise also reduce continuous noise going into an individual piece of processing equipment and the continuous noise that might exit that same equipment. Once the local and continuous noise is addressed, system reliability will improve. It is then possible to effectively plan for further process efficiency. Following that, output noise (material wastes and rework) is consistently and measurably reduced in a way that circular, or by-product solutions may change. An input-process-output variable control sequence de-risks the adoption of new processes and technology. This sequence can reduce input costs and environmental outputs (wastes) in parallel.

Several factors should be considered when aligning your business with the end goal of process and environmental efficiency. The scale of a business will determine what is economically possible when the skill set to measure and manage variables exists and is practiced. These factors are examined more closely in six chapters of this guide:

• Understanding behaviour, communication and skills
• Noise: the LLOYD (leaks and losses obscure your data) factor and human error
• Measuring baselines, benchmarks and scale
• Digital integration (DI) and key performance indicators (KPIs)
• Data management
• Circular recovery

These factors, tend to be soft in terms of cost-benefit with a measurement system to connect them. The synergy generated in the input-process-output sequence requires skills, practices and technology to improve performance. With or without the end goal in mind of achieving a successful transformation toward Industry 4.0, the roadmap suggests a data-driven solution. This requires clean data, where the noise (variables) is managed so as not to obscure the analysis and lead to decisions with costly, unintended consequences.

The appendices in this guide include a detailed discussion of various skills, behaviour, tools and technologies. The sequence for reducing variables begins with inputs, then process and lastly outputs to optimize performance.