Start with the Problem, Not the Robot: A Smarter Approach to Automation Decisions

Why Successful Manufacturing Automation Starts With the Problem, Not the Technology

A manufacturer recognizes that a production process needs to improve. Throughput is lagging. Labor is insufficient. Product quality varies. Or an aging line presents safety and reliability concerns.

The team quickly identifies what appears to be the answer: a robot, a specific machine or an OEM-supplied system. Soon, an RFP is issued, proposals arrive and the conversation centers on price, delivery and technical specifications.

But one important question may never have been fully answered: What problem are we actually trying to solve?

This omission can turn a seemingly direct path to automation into an expensive detour. Successful manufacturing automation starts by defining the business and production problem before selecting the technology. Robots, OEM equipment and commercially available systems may ultimately be the right solution. The risk comes from prescribing that solution before the process requirements, operating realities and measures of success are understood.

Before investing in automation, manufacturers should define the problem, establish success criteria and evaluate the range of viable solutions. Here’s what that discovery process should include.

What Should Manufacturers Consider Before Investing in Automation?

The right automation solution starts with a clearly defined production problem and measurable business objective. Manufacturers should document process requirements, throughput and quality targets, facility constraints, workforce capabilities, maintainability needs and expected future changes before evaluating technology. Only then should solutions such as robotics, OEM equipment, customized machinery or first-of-a-kind automation be compared.

The discovery process should address the following questions:

Business Requirements

• What business problem are we trying to solve?
• How will success be measured?
• Is speed to market more important than maximum efficiency?

Production and Performance Requirements

• What throughput and cycle time must the system achieve?
• What product characteristics and process variables matter?
• What payload, reach and quality requirements apply?

Facility and Workforce Requirements

• What footprint or facility constraints exist?
• What hazards or physically demanding activities should automation reduce?
• What operator skill, maintenance support and programming capabilities will be available?

Future Requirements

• Is the product, package or process likely to change?
• Does the system need to be expandable or easily duplicated?
• Will the solution be deployed at one site or standardized across multiple facilities?

Answering these questions helps establish the business case and reveals the tradeoffs that should guide the technology decision. Without this upfront work, manufacturers may receive several technically sound proposals for a solution that was never properly validated.

How Do You Identify the Right Manufacturing Automation Solution?

The right automation solution starts with a clearly defined production problem and measurable business objective.

Manufacturers should document process requirements, throughput and quality targets, facility constraints, workforce capabilities, maintainability needs and anticipated future changes before evaluating specific technologies.

Only then should potential solutions be compared.

Depending on the application, the best approach may be:

• A standard OEM system
• An off-the-shelf system customized for the application
• A purchased robotic solution
• Customized mechanical or electrical equipment
• A first-of-a-kind automation system
• A hybrid approach combining proven and custom technologies

Each path carries different implications for capital cost, delivery, flexibility, maintainability, repeatability, throughput, quality and scalability.

The objective is not to choose the most sophisticated technology. It is to select the solution that best supports the manufacturer’s overall business and production requirements.

What Does an Engineering-Led Automation Integrator Do?

A technology supplier typically begins with the capabilities of the equipment it sells. An engineering-led automation integrator begins with the manufacturer’s business objective, product, process and operating environment, then works backward to the appropriate solution.

That distinction allows the technology to follow the application rather than forcing the application to fit predetermined technology.

An engineering-led automation integrator evaluates the manufacturer’s:

• Business case and performance objectives
• Product characteristics
• Production process
• Operating environment
• Technical and facility constraints
• Workforce and maintenance capabilities
• Current and future production needs

As an engineering-led integrator, Foth Serial 1 Automation does not steer every client toward a custom system or dismiss the value of commercially available equipment. Its role is to evaluate the viable options before recommending an approach.

A standard OEM system may provide the best combination of speed, cost and proven performance. In other cases, an existing system may need to be modified for a particular product or facility. Some applications may require custom equipment, a first-of-a-kind system or a combination of proven and custom technologies.

The value of this approach lies in selecting the technology based on each client’s business case, process requirements and ultimate success, not in selling a prepackaged answer.

How Should Manufacturers Define an Automation RFP?

After defining the problem and success criteria, the next step is translating that discovery into a request that invites the appropriate solutions.

A strong automation RFP or project directive should:

• Describe the business and production problem
• Define the desired outcome
• Identify critical performance requirements
• Document product and process characteristics
• Explain facility and operating constraints
• Distinguish firm requirements from areas open to engineering judgment
• Define how proposed solutions will be evaluated
• Avoid prescribing a robot, machine or system type unless that decision has already been validated

This approach gives integrators room to develop and compare viable concepts. It also gives the manufacturer a consistent basis for evaluating performance, technical risk, cost, schedule, maintainability and long-term fit.

Instead of asking, “How much will it cost to install this robot?” the manufacturer can ask a more valuable question: “What solution will best achieve the production outcome we need?”

What Happens When Technology is Selected Too Early?

Predetermined technology is not necessarily bad technology. But problems arise when a manufacturer assumes that one of these options is the answer before confirming that it can deliver the required result. 

A system can work exactly as designed and still fail the business objective if it:

• Cannot achieve the required production rate
• Lacks the reach, precision or flexibility the process requires
• Cannot adapt as products or packaging change
• Requires skills or maintenance capabilities the facility doesn’t have
• Creates unacceptable lifecycle or operating costs

Technical success and business success are not necessarily the same thing.

A machine that runs as designed is not a successful investment if it cannot support production goals, cannot be maintained by the plant, or becomes obsolete when the process changes.

Why Upfront Automation Discovery Saves Time and Money

Discovery, testing and engineering evaluation can initially appear to slow a project or add expense, especially when compared with the apparent ease of collecting proposals from equipment suppliers.

But moving quickly at the beginning does not always produce the fastest path to successful production.

The cost and complexity of correcting a problem generally increase as a project advances from concept through detailed design, fabrication, installation and operation. An issue discovered during early analysis may require only a design adjustment. The same issue discovered after fabrication or installation may result in change orders, redesign, delayed production or lost capital.

Early-stage activities may include:

• Process observation and data collection
• Product testing
• Concept development
• Simulation or modeling
• Proof-of-principle testing
• Prototyping
• Technical and economic feasibility analysis
• Risk assessment

These activities can expose performance gaps before significant capital is committed.

Upfront diligence may prevent:

• Costly change orders
• Equipment redesign
• Delayed startup
• Lost throughput
• Quality problems
• Maintenance difficulties
• Misapplied capital

Spending more during early discovery to avoid a much more expensive failure can be a sound business decision, even when the value of the avoided failure is difficult to see at the outset.

In manufacturing automation, slowing down at the beginning can be the fastest path to successful production.

What Real-World Automation Projects Can Teach Us

The consequences of prescribing technology too early can persist long after installation.

When an Automation Investment Becomes a Stranded Asset

In one situation, a manufacturer’s predetermined solution failed to meet the operation’s needs and ultimately sat unused in a warehouse. Because the asset remained on the company’s depreciation schedule, the manufacturer could not simply discard it.

In another case, equipment was reassigned to a secondary use, not because it was the most effective solution for that process, but because the organization needed to find some way to use its investment.

The lesson: Selecting equipment without first validating its fit can leave a manufacturer with an expensive asset that provides little operational value.

When Equipment Works but the Plant Cannot Support It

A manufacturer invested in a multimillion-dollar packaging solution that performed its intended function but proved too complicated for the plant to operate and maintain effectively. The equipment was ultimately dismantled, and its components were used as spare parts at other facilities.

The lesson: A solution must fit the workforce, maintenance capabilities and operating environment, not just the technical application.

When Early Testing Prevents the Wrong Investment

A commercially available bagging machine appeared to be a suitable solution until testing revealed that it could not meet the required production rate or quality standard.

Proof-of-principle testing exposed the performance gap before the manufacturer committed to full implementation.

The lesson: Early testing can validate critical assumptions while changes are still relatively inexpensive.

When the Performance Objective Drives the Design

In a different application, an intelligently engineered cheese-filling system delivered significantly greater throughput than an available alternative. The design succeeded because the engineering process began with the performance objective rather than an assumed piece of equipment.

The lesson: Starting with the required outcome creates room to identify a solution that may not be evident when technology is prescribed in advance.

Together, these experiences reinforce a critical point: selecting automation equipment is a strategic decision that affects the business case, production process, workforce and system lifecycle.

Start with the Manufacturing Challenge, Not the Technology

Automation investments are too consequential to begin with an assumption that has not been tested.

A robot, OEM machine or custom system may ultimately be the right answer, but that conclusion should follow a clear understanding of the production problem, business case, operating environment and success criteria.

Before selecting the technology:

1. Define the business and production problem.
2. Document the current process.
3. Establish measurable success criteria.
4. Identify performance and operating requirements.
5. Consider workforce, maintenance and facility constraints.
6. Evaluate how the product or process may change.
7. Compare the full range of viable solutions.
8. Validate critical assumptions before committing significant capital.

Foth’s Serial 1 Automation starts with the challenge rather than a predetermined technology. The team evaluates standard equipment, robotics, customized systems and first-of-a-kind solutions against the manufacturer’s actual requirements to identify the approach that provides the best overall fit.

When an available solution does not meet those requirements, Serial 1 can move from concept through custom engineering, integration, installation and startup.

Bring us the production problem. We’ll help you determine what the solution should be.