Tips for Assembling Automation Systems

Designing and using a Building Automation System (BAS) in an existing facility to create well-balanced, efficient, and healthy buildings requires both a strategic retrofit plan and careful operational use once installed. Here’s a structured approach: 1. Assessment and Benchmarking Existing Systems Review: Gather drawings, control sequences, and recent testing/air balance (TAB) reports. Map which equipment is automated, semi-manual, or outdated. Occupant Comfort & Health Data: Collect thermal comfort complaints, indoor air quality readings (CO₂, VOCs, humidity), and hot/cold zone reports. Energy Baseline: Benchmark energy use (kWh, therms, kBTU/sq.ft) before changes to measure impact later. 2. System Design for Retrofit Open Protocols: Use BACnet/IP, Modbus, or MQTT gateways to integrate legacy HVAC, lighting, and power monitoring systems into a common BAS platform. Zoning & Control Strategies: Add VAV box controllers, airflow measuring stations, and smart dampers where feasible. Layer demand-controlled ventilation (using CO₂ sensors) to balance health with energy efficiency. Sensor Deployment: Temperature, humidity, CO₂, and occupancy sensors distributed per ASHRAE/Well Building standards. Thermal imaging or wireless sensor networks to identify air balance and comfort issues in real time. Healthy Building Features: Integrate MERV-13+ filtration monitoring and filter life sensors. Add UV-C or bipolar ionization controls (where appropriate). Tie in IAQ dashboards for occupant transparency. 3. Control Sequences & Optimization Air Balance & Comfort: Program supply/return fan tracking and static pressure reset to reduce drafts and ensure balanced airflow. Zone-level setpoint adjustment with occupant feedback loops (via apps or kiosks). Energy Efficiency: Implement chilled/hot water reset schedules. Optimize economizer use for free cooling. Integrate with lighting controls and occupancy sensors for holistic energy management. Safety & Resilience: Alarms for high CO₂, humidity excursions, filter pressure drop, or equipment failures. Cellular failover routers for visibility during network outages (cyber-secure). 4. Operational Use Analytics Layer: Add FDD (Fault Detection & Diagnostics) to identify stuck dampers, simultaneous heating/cooling, or drifting sensors. Continuous Commissioning: Periodic re-balancing aided by real-time BAS data and thermal imaging surveys. Dashboards: Tailor interfaces for facilities, executives, and occupants (different levels of detail). Training: Facility staff must be trained in both BAS operation and comfort/IAQ troubleshooting. 5. Measurable Outcomes Balanced Comfort: More consistent temperatures across spaces, reduced hot/cold complaints. Efficiency Gains: Typically 15–30% energy savings post-retrofit. Health Improvements: CO₂ maintained below 800–1000 ppm, humidity controlled within 40–60%, reduced absenteeism and improved occupant satisfaction.

Here’s my step-by-step action plan whenever I work with a client to help them get a new automation project started. Maybe it’s useful to you, too. 0. Write a single, meaningful, efficient test. I don’t care if it’s a unit test, an integration test, an E2E test or whatever, as long as it is reliable, quick and produces information that is valuable. 1. Run that test a few times locally so you can reasonably assume that the test is reliable and repeatable. 2. Bring the test under version control. 3. Add the test to an existing pipeline or build a pipeline specifically for the execution of the test. Have it run on every commit or PR, or (not preferred) every night, depending on your collaboration strategy. 4. Trigger the pipeline a few times to make sure your test runs as reliably on the build agent as it does locally. 5. Improve the test code if and where needed. Run the test locally AND through the pipeline after every change you make to get feedback on the impact of your code change. This feedback loop should still be VERY short, as we’re still working with a single test (or a very small group of tests, at the most). 6. Consider adding a linter for your test code. This is an optional step, but one I do recommend. At some point, you’ll probably want to enforce a common coding style anyway, and introducing a linter early on is way less painful. Consider being pretty strict. Warnings are nice and gentle, but easy to ignore. Errors, not so much. 7. Only after you’ve completed all the previous steps you can start adding more tests. All these new tests will now be linted, put under version control and be run locally and on a build agent, because you made that part of the process early on, thereby setting yourself up for success in the long term. 8. Make refactoring and optimizing your test code part of the process. Practices like (A)TDD have this step built in for a reason. 9. Once you’ve added a few more tests, start running them in parallel. Again, you want to start doing this early on, because it’s much harder to introduce parallelisation after you’ve already written hundreds of tests. 10 - ∞ Rinse and repeat. Forget about ‘building a test automation framework’. That ‘framework’ will emerge pretty much by itself as long as you stick to the process I outlined here and don’t skip the continuous refactoring.

This cabinet was engineered with Eplan Electric P8, and the result speaks for itself: clean wiring, clear structure, fast commissioning, and zero ambiguity for technicians. If you design control panels and want fewer errors, faster builds, and smoother handover to production, these practical EPLAN tips make a real difference: 1. Use proper device macros, not symbols Macros with mounting, connection points, and accessories ensure your design matches reality. This alone reduces wiring mistakes dramatically. 2. Keep structure identifiers consistent from day one Define your IEC structure (Function / Location / Installation) early. Changing it later costs hours and breaks reports. 3. Let EPLAN generate terminal strips and wiring lists Manual terminal planning is one of the biggest time-wasters. Auto-generated terminal diagrams speed up panel wiring and troubleshooting. 4. Standardize parts via Parts Management Link every symbol to a real manufacturer part number. This improves BOM accuracy and avoids procurement surprises. 5. Think like the panel builder, not only the designer Cable routing, spacing, and accessibility matter. A schematic that ignores physical reality always fails on the shop floor. 6. Use reports as engineering tools, not paperwork Connection lists, wire lengths, and PLC I/O reports are not “extras”—they are how you validate design quality. This is why modern electrical engineering is no longer just about drawing schematics. It is about data consistency, automation, and lifecycle efficiency. If you work with: • EPLAN • Industrial automation • Control panels • PLC systems • Electrical design standards this topic directly impacts your daily work. What is the one EPLAN feature that saved you the most time on a real project? #EPLAN #ElectricalEngineering #ControlPanel #IndustrialAutomation #PLC #PanelBuilding #ElectricalDesign #AutomationEngineering #DigitalEngineering #SmartManufacturing #Industry40

AI isn’t the hard part. Designing the workflows around the AI is what separates beginners from real builders. If you're trying to get into automation, AI agents, or workflow engineering, this cheat sheet is one of the best starting points I’ve seen. Here’s your roadmap to think like an automation engineer👇 1. Understand Workflow Automation → Triggers, actions, conditions → Why automation saves time, reduces errors, and scales operations → Real examples across marketing, sales, support, and ops 2. Master n8n Fundamentals → Visual node-based builder → Trigger nodes, core nodes, action nodes → Cloud vs self-hosting, environment setup, and templates library → How n8n compares to Zapier and Make (flexibility, cost, control) 3. Learn Core Nodes & Data Handling → Set Node, Code Node, HTTP Node, Merge Node → Expressions, data structures, referencing, transformations → Handling nested JSON, loops, branching, and error paths → Debugging with execution logs and error workflows 4. Add AI into Your Workflows → AI Agent node, LLM chains, summarizers, Q&A chains → Integrating OpenAI, Google AI, IBM Watson → Building content engines, research agents, inbox managers → Designing repeatable and safe agent workflows 5. Build Real Systems → Automations for support, reporting, content, operations → Apply prompting, memory, and tool use → Case studies: human-in-loop pipelines, storytelling agents, research bots 👉 If you're serious about automation or AI agents, start here. 👉 This kit teaches you the engineering thinking, not just the tool clicks. ♻️ Repost to help others build safer systems. ➕ Follow Naresh Edagotti for more AI engineering breakdowns that go beyond the surface.

Just read #OpenAI’s latest guide on building AI Agents. No fluff. No hype. Just clear, field-tested advice. Here are the 10 takeaways that really stayed with me — not just as a technologist, but as someone helping enterprises build agentic systems that last. 1. Start simple — with one #agent. It’s tempting to jump into multi-agent orchestration, but most use cases don’t need it upfront. In fact, multiple agents often introduce more chaos than value, especially when the basic workflow isn’t stable yet. 2. Choose your problems wisely. Agents shine where there's ambiguity — decision-making, exception handling, and unstructured data. If your task is predictable and rule-based, traditional automation will always be more efficient. 3. Start with the most powerful model. Establish your baseline with #GPT-4 or an equivalent. You need to prove the value first. Once it works, then fine-tune for speed and cost. 4. Your #SOPs are agent instructions waiting to happen. This one hit home. So much enterprise knowledge sits in playbooks and wikis — often ignored. Break them down into steps. Let the agent learn your process as it is, before redesigning it. 5. Tools need boundaries. Don’t make tools up as you go. Define clean interfaces — retrieval, execution, orchestration — and document them well. Reusable tools aren’t just efficient; they reduce technical debt. 6. Guardrails aren't optional. They're layered. There’s no single safety net. Combine prompt checks, rules, APIs, human feedback — whatever it takes to protect privacy, security, and intent. In high-trust environments, this matters more than anything. 7. Don’t over-engineer prompts. Use templates with variables. One solid base prompt that accepts policy or context inputs can scale across workflows. It’s easier to manage and debug. 8. Design for escalation from day one. What happens when an agent hits a blind spot? Or a high-risk situation? There must be a graceful, traceable way to hand off to a human — without friction. 9. Match orchestration to complexity. Some systems need a central ‘manager’ agent. Others are better off with distributed, peer-to-peer tasking. There’s no universal pattern — it’s about choosing what fits your use case. 10. Don’t wait for perfection — deploy early. Real users will always surprise you. The edge cases, the weird inputs, the unexpected outcomes — they show up only after you ship. Your best guardrails will be born from actual failures, not hypothetical ones. This isn’t theory. These are the kinds of lessons we apply every week as we build intelligent systems — where agents augment humans, not replace them. If you’re building in this space: 📌 Start small. 📌 Stay human-centric. 📌 Let trust scale with capability. Because building an agent is easy. Building a system you can trust — at scale, under pressure, and in the wild — is the real challenge. #AIagents #AgenticAI #LLMOps #EnterpriseAI #GauravWrites #BuildingWithTrust

Did you know that 70% of control panel failures trace back to improper earthing and wiring practices - not faulty components? When it comes to industrial automation, panel reliability isn’t just about selecting premium devices - it’s built on the invisible foundation of how you wire, segregate, and ground your system. 1. Wiring Segregation – IS vs Non-IS Circuits Follow IEC 60079-14 & ISA RP12.6: Intrinsically Safe (IS) and Non-IS circuits must be segregated physically or by metallic barriers to avoid energy coupling. Maintain ≥50 mm spacing or use earthed metal partitions in marshalling panels. Always separate analog, digital, and power wiring to reduce electromagnetic interference (EMI) and signal noise. Common pitfall: Routing IS and Non-IS in the same conduit — a direct violation that can invalidate IECEx/ATEX certification. 2. Earthing – The Heartbeat of Reliability Follow IEC 60364, IEC 61000, and Shell DEP 33.46.00.31-Gen for control panel grounding. Maintain < 1 Ω earth resistance for control systems and equipotential bonding between instrument earth and main earth bar. Use star-point earthing to prevent ground loops in sensitive analog systems. Ensure individual clean earth for signal reference separate from dirty earth (power/EMI sources). 🧠 Remember: Even a few millivolts of ground potential difference can cause analog drift or false trip signals. 3. Cable Selection & Labeling Select cables per IEC 60228 (conductor sizing) and IEC 60332 (flame retardancy). Voltage drop should stay below 2% for control circuits and below 5% for power feeders. Use tinned copper shields and 100% coverage foil + braid for analog signal cables. Implement IEC 81346-1 / ISA 5.1 for consistent tagging and labeling across panels. Labels must be heat-resistant, UV-stable, and machine-printed for long-term traceability. 4. Common Mistakes & Their Impact Shared earth bars between power & signal → ground loops and EMI noise. Mixed IS/Non-IS wiring → safety certification failure. Undersized neutral or earth conductor → voltage imbalance or equipment damage. Missing ferrules or poor cable termination → intermittent faults and difficult troubleshooting. ✅ Takeaway Panel reliability is not built in the factory — it’s wired into every detail. Good wiring and earthing practices ensure safety, signal integrity, and long-term system stability. 🔍 What’s your approach to ensuring proper segregation and grounding in your panels? Share your experience or key lessons from the field 👇 #IndustrialAutomation #ControlSystems #ElectricalEngineering #PanelDesign #Instrumentation #IECStandards #AutomationEngineering #Earthing #WiringPractices #ProcessSafety #ReliabilityEngineering #EngineeringDesign

One of the most underrated foundations of automation? Process mapping. Not flashy. Not technical. But essential. --- Before you even think of Make, n8n, Zapier or GPT — map the process. It’s like trying to build a skyscraper with no blueprint. You’re not automating tasks — you’re automating decisions, flows, and outcomes. And without a shared map, it all collapses. --- Before we touch a single tool, we start with process mapping. It’s not just a flowchart. It’s your operational source of truth: 1️⃣ Inputs — Where is the data coming from? 2️⃣ Logic — What are the decision branches? 3️⃣ People — Who’s involved (AI or human)? 4️⃣ Output — What does success look like? When this is clear, the system builds itself. --- We’ve rebuilt dozens of broken systems that skipped this step: → Teams not aligned on what “onboarding” even means   → Random triggers glued together with no structure   → Approval loops forgotten, human actors missing Three weeks later? Everything breaks & no one knows why. --- A good process map avoids all of that. It acts as: → Shared language across sales, ops, leadership → Insurance policy before any build → Blueprint for every transformation that happens in the business Every successful system we’ve built — from content engines to lead follow-ups to full-scale ops infra — started with this. --- And don’t overthink the tool to represent it: → Miro, Lucid, Whimsical, Figma… even pen and paper. The best tool is the one you’ll stick to. What matters is clarity. Not color palettes. --- So if your automations are breaking down, slow down. Start with the map. Then build the system. That’s how you build for outcomes — not aesthetics.

If your PLC program looks like a tornado of rungs and tags… it’s time to talk code organization. One of the most overlooked (but most important) skills in automation is how you structure your logic. A good program isn’t just functional, it’s readable, maintainable, and scalable. Here’s how I like to structure mine: READ INPUTS FIRST At the top of the scan, I read and preprocess all inputs. That means: - Scaling analog values - Bit summing statuses - Conditioning values that come in externally to the respectivecomponent This makes sure everything below is based on reliable, real-time, and clean data. CONTROL LOGIC IN THE MIDDLE This is where the brain lives, sequences, states, fault conditions, timers, and logic that drives the system. I group this by function or subsystem (motors, valves, conveyors, etc.), often with clearly labeled rungs or section headers. OUTPUTS LAST At the bottom, I drive outputs based on the control decisions made above. No logic calculations down here, just clean writes like: MotorStart := Motor1.RunCommand; Minimize the logic out of the output section. It should be transparent. BIT GROUPING = SANITY SAVER If you’ve got the same 6 conditions checked 20 times across the program, wrap them into a single BOOL like SystemReady. Then everywhere else, you just check: IF SystemReady AND AutoMode THEN This avoids copy-paste errors, simplifies debugging, and makes logic more readable. REUSABILITY & NAMING - Use descriptive tag names. - Use UDTs and AOIs to encapsulate data/logic for repeated devices. - Group tags in structured ways: Motor1.b Running, Motor1.Fault, etc. Make it easy to search, comment, and troubleshoot. WHY IT MATTERS: - Faster startup & commissioning - Easier troubleshooting in the field - Smoother handoffs to other engineers - Less chance of “spaghetti logic” biting you later Clean logic doesn’t just help the machine run better. It helps the people who work on it. What’s your go-to structure when building out PLC code? #PLCProgramming #StructuredText #LadderLogic #ControlsEngineer #CodeOrganization #AutomationEngineering #IndustrialAutomation #FunctionBlocks #SmartManufacturing #SystemDesign #EngineeringBestPractices #innovation #technology #futurism #engineering

You're automating your business all wrong...let's fix that. Here's the 5 step approach I would take: 1. Live within the workflow itself, performing the manual tasks for 1 week to 1 month...too many will skip this step. But you need to fully understand if the process you have is efficient or not. Otherwise you'll end up building an automation for something that isn't very useful, or contains too much waste. 2. Figure out where the slowest & most inefficient parts are. This usually involves button-clicks, copying & pasting, duplication, and boring / mindless tasks. 3. Map out the flow: - What happens first? - Where does the data come from? - Where does it need to go to? - Where does it end up at? - When does a human perform any quality checks or approvals? - What tools are part of this process? - Are there any areas that can be eliminated altogether? - Who needs to know about it? 4. Open up n8n, Make, or Zapier...and start diagramming the modules. Sometimes it might take 1-2 automations that are chained together, with a human sitting in the middle of the process for approvals or quality checks. This step is where you'll begin to find out the limitations of AI & Automation tools, and visualize how the workflow will be built. 5. Test the flows with dummy data before turning anything on live...especially if this is a workflow that communicates with clients! (I've screwed this one up many times before LOL) If you're interested in some of the tools I use to run my newsletter business, check out this post here: https://lnkd.in/e9sHn6MQ

How to prepare an automation project in your warehouse? It warehouse involves several key steps to ensure its success. Here's a general outline of how to approach it: 1- Assessment and Planning: Evaluate your current warehouse operations to identify areas that can benefit from automation. This could include tasks such as inventory management, order picking, packing, and shipping. Determine your goals for automation, such as increasing efficiency, reducing errors, improving safety, or scaling operations. 2- Research and Selection: Research automation technologies and solutions that align with your goals and budget. This could include automated guided vehicles (AGVs), robotic arms, conveyor systems, warehouse management software (WMS), and sensors. Consider factors such as scalability, compatibility with existing systems, ease of integration, and return on investment (ROI). 3- Design and Implementation: Work with vendors or internal teams to design a detailed plan for implementing automation in your warehouse. This should include timelines, resource allocation, and milestones. Develop a layout for your automated warehouse, considering factors such as workflow optimization, space utilization, and safety regulations. Install and configure the chosen automation technologies, integrating them with your existing systems as needed. 4- Testing and Optimization: Conduct thorough testing of the automated systems to ensure they function as intended and meet your performance metrics. Gather feedback from warehouse staff and make any necessary adjustments to optimize the automation process. 5- Deployment and Maintenance: Once the automation project is fully operational, monitor its performance closely to ensure it continues to meet your goals. Develop a maintenance schedule to keep the automated systems running smoothly, including regular inspections, repairs, and software updates. 6- Change Management and Communication: Communicate clearly with warehouse staff about the goals and benefits of the automation project, addressing any concerns or resistance to change. Provide training and support to help employees transition to the new automated processes. By following these steps and carefully planning and implementing your automation project, you can streamline your warehouse operations, improve efficiency, and position your business for future growth.