‘Life planning’ for industrial systems

Making financial decisions by numbers alone is laden with risk, as the numbers are too often one-dimensional. When it comes to planning for a manufacturing plant’s financial future, it pays to take the same approach you would take to your personal financial future. A sound financial strategy can only come from a careful accumulation of several factors. A credible “life plan”—done on your own or with the help of a professional—can provide a competitive edge and serve as a living legacy for the people involved.

When planning for personal retirement, a skilled financial advisor typically asks the potential retiree dozens of questions, including: What assets and income sources would you have access to? What standard of living do you expect? How long do you expect to live after retirement?

The credible advisor compiles responses to such questions into a professionally developed electronic tool set. This utility generates valuable decision-supporting charts, graphs and other resources that create a personalized profile that includes information on how the client’s asset mix impacts his or her risk, how projected inflation may affect savings, and how the situation compares with the client’s peers.

The same careful analysis can and should be used in preparing for the future of an automated industrial process.

More data = better planning

When planning for any investment in automation equipment, engineers and business planners frequently ask one of four questions and use the answers to create their plant’s automation system life plan (See “Planning questions” table.) Only two of these criteria, however, typically are measured. Due to the subjective nature of the other two criteria, they often are considered only as ways to politically reinforce or overturn decisions justified by the others. In the retirement planning analogy, it would be akin to deciding not to invest in a 401(k) because you feel it’s likely that your children will support you indefinitely—not always a sure bet.

The key to creating a successful life plan for an industrial process lies in the ability to collect data and balance considerations from all four criteria. The resulting plan becomes a comprehensive assessment of the current state. Decisions can then be made in a logical, deliberate way and may include:

• Partial or complete equipment, software, or network upgrades over a multi-year schedule,

• Establishment of a preventive maintenance plan,

• Development of a standard training curriculum,

• Modification of electrical safety policies.

The following sample represents a simple model by which to structure an analysis of the future of an automated industrial process. It also provides examples of the data that would help quantify each of the four criteria in simple terms.

Source:Schneider/ Control Engineering

As a process ages market productivity becomes higher than actual process productivity, to the point where incremental gains may not be enough to stay competitive.

Criteria A: process efficiency/resource utilization

In its early stages, an industrial process exhibits tremendous gains in productivity as new equipment is employed, information systems are integrated, startup problems are resolved, and personnel become efficient at their new jobs. Eventually, the rate of productivity will level off as the focus shifts towards incremental cost reduction and process flow improvement.

Initially, the payback against the “market standard” benchmark for productivity is positive, as the modern plant or process is able to offer a return on investment. As the process ages, however, the productivity of the market becomes higher than that of the process, to the point where incremental efficiency gains may not be enough to stay competitive. (See chart, Plant productivity over time.)

A plant’s effort to increase productivity at a market standard rate could be limited by several factors, including equipment capacity, need for manual troubleshooting, inefficient spare parts inventories, and inflexibility of people and processes (resistance to change). Let’s look at each individually and see what information can be collected to measure success.

Machines originally designed for a certain throughput may need to undergo significant redesign or even be replaced to increase their capacity enough to impact efficiency. Information that can be collected to measure capacity increases include the target and actual production rates for the entire facility, and the total operating hours, per year, for first shift and other shifts.

Older production systems need more time to recover from unscheduled downtime than newer plants. Older systems tend to use manual troubleshooting methods, while newer plants may employ self-diagnostic and preventative maintenance technologies. To measure success here, you need to define what process you use to dispatch maintenance personnel and evaluate the effectiveness of this process.

As systems age, the right mix of spare parts inventory becomes critical. Too much inventory drives up costs, while too little creates downtime risk. Data can be collected to measure the efficiency of spare part inventory management. Questions to ask include: How do you manage your spare parts? What is the average inventory turnover, in parts per year, of certain devices, including programmable logic controllers (PLCs), human machine interfaces (HMIs), variable frequency drives (VFDs) and servo drives.

The flexibility of engineering and service personnel—meaning, their ability to adapt to change—can be affected by several factors. For example, incremental expansions and modifications may employ a mixture of various pieces of equipment from several different vendors. This would have a negative impact on the flexibility of maintenance personnel and controls engineers that service the entire operation. Sample of information to be collected for this metric includes: the size (number) of your maintenance and engineering staff, their average years of experience, and how much of this experience is with International Electrical Code (IEC) or related programming and diagnostics.

Criteria B: maintenance costs

Electronic products from any manufacturer that were manufactured in the 1980s and early ’90s are based on components like memory chips and microprocessors that are no longer available on the open market. While spare parts production is maintained with salvage equipment, last-time buys, and discrete redesigns, future indefinite supply of these components cannot be assured. This reduced availability has a direct impact on maintenance costs. Moving to a platform that uses modern electronic technologies can significantly reduce the cost of spare parts and extend the working life of the process or machine. Information to be collected to improve spare parts efficiency includes the cost per hour of downtime, both in terms of maintenance labor as well as cost of lost production.

Criteria C: process modifications

If a process or machine needs to be functionally modified or expanded, doing so with a legacy PLC platform will likely add costs and complexity for a variety of reasons. These include:

Older PLC platforms may not be able to interface with today’s high performance networks without expensive bridges and gateways.

Buying additional racks, I/O cards, CPUs and other accessories for an obsolete product line may be cost-prohibitive.

Adding functionality to a decades-old ladder logic program can require significant engineering time and specialized talent to ensure no negative impact on current performance.

The following data is intended to assess the degree that a plant or process will undergo modifications for reasons other than maintenance costs. These “weighted judgments” on specific motivators are difficult but necessary to quantify:

• Is your industry growing?

• Is your company growing within your industry?

• Is your process sensitive to environmental considerations?

• Do startups and line changes need to be performed more quickly?

Criteria D: safety and security

Today’s business climate demands attention to serious safety and security threats such as terrorism, identity theft, workplace accidents, industrial sabotage, environmental and product liability, public safety, process traceability, and natural disasters. With proper planning and design of safeguards, the risks and recovery costs of these events can be minimized. Collect information on which plant safety standards are you required to comply with, and which listed NFPA-70E requirements you already comply with.

As is the case in retirement planning, an industrial end-user shouldn’t have to do this kind of analysis alone. A reputable electrical automation supplier or industry consultant can streamline this process with tools that are specifically designed to accommodate the needs of their customer base. Regardless of how it’s created, though, a viable, credible life plan for industrial systems can help a facility maintain its competitive edge. It’s imperative to quantify the all-important “soft” criteria to balance the traditional measurements of efficiency and maintenance costs. Only with this balance can confident investments follow.

Criteria	Measurements
A. How can I make my process more efficient or better utilize my resources?
	– Throughput
	– Operational Equipment Efficiency (OEE)
	– Return on Capital Employed (ROCE)
B. How can I reduce maintenance costs?
	– Scheduled and unscheduled downtime
	– Preventative / corrective maintenance hours
C. How can I better prepare for future process modifications and expansions?	Weighted judgments on specific motivators that are difficult to quantify
D. How can I improve the security of my facility and the safety of the employees within?	Checklists of tasks for compliance with specific safety and security standards

Author Information

Robb Dussault is the automation and control services manager for Schneider Electric. He can be reached at robb.dussault@us.schneider-electric.com .

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