{"id":1761,"date":"2026-11-05T04:00:13","date_gmt":"2026-11-05T04:00:13","guid":{"rendered":"https:\/\/mestric.com\/planiranje-kapacitet-proizvodnje\/"},"modified":"2026-11-05T04:00:15","modified_gmt":"2026-11-05T04:00:15","slug":"planiranje-kapacitet-proizvodnje","status":"publish","type":"post","link":"https:\/\/mestric.com\/sl\/planiranje-kapacitet-proizvodnje\/","title":{"rendered":"Production Capacity Planning: A Practical Guide for Plant Managers"},"content":{"rendered":"<\/p>\n<p>Production capacity planning means working out how much your plant can realistically produce, comparing that with the demand you expect, and deciding what to change when the two do not match. Done well, it tells you early which machine, shift or product mix will be overloaded, so you act before orders slip. This guide walks through the method step by step, with formulas, a worked example and the data you need to keep the plan accurate.<\/p>\n<div data-blg-cta=\"after_tldr\" data-blg-cta-layout=\"banner\" style=\"margin:28px 0;font-family:-apple-system, BlinkMacSystemFont, &apos;Segoe UI&apos;, Roboto, Helvetica, Arial, sans-serif\">\n<div style=\"border-radius:26px;padding:min(22px,3.2vw);background:radial-gradient(circle at 100% 0%,#e3eeec 0 150px,rgba(255,255,255,0) 151px),radial-gradient(circle at 0% 100%,#e3eeec 0 130px,rgba(255,255,255,0) 131px),linear-gradient(180deg,#edf3f2 0%,#f6f9f9 100%)\">\n<div style=\"background:#ffffff;border-radius:18px;overflow:hidden\">\n<div style=\"padding:34px 30px;text-align:center\">\n<div style=\"margin:0 0 18px\"><span style=\"display:inline-block;max-width:100%;border-radius:999px;padding:6px 13px;font-size:12px;font-weight:800;letter-spacing:0.1em;text-transform:uppercase;line-height:1.3;background:#669f94;color:#ffffff\">Mestric<\/span><\/div>\n<div style=\"font-size:26px;font-weight:800;line-height:1.2;letter-spacing:-0.01em;color:#1f2937;margin:0\">Plan Capacity With Real-Time Data<\/div>\n<div style=\"width:56px;height:6px;border-radius:3px;background:#669f94;margin:12px 0 14px;margin-left:auto;margin-right:auto\"><\/div>\n<div style=\"font-size:15px;line-height:1.55;color:#64748b;margin:0 0 24px;max-width:44em;margin-left:auto;margin-right:auto\">Mestric connects with manufacturing equipment to track performance, downtime and quality, giving plant managers data to support capacity decisions.<\/div>\n<p><a href=\"https:\/\/mestric.com\/sl\/\" style=\"display:inline-flex;align-items:center;gap:9px;border-radius:10px;font-weight:700;font-size:15px;text-decoration:none;padding:13px 22px 13px 26px;background:#669f94;color:#ffffff\">Explore Mestric<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<h2 id=\"tldr\" tabindex=\"-1\">TL;DR<\/h2>\n<ul>\n<li>Capacity planning turns forecast demand into required hours per resource and compares them with the hours truly available.<\/li>\n<li>Use effective capacity, not nameplate capacity: maintenance, changeovers, product mix and quality losses always reduce it.<\/li>\n<li>Divide required by available capacity for each machine or line. A ratio above 100% marks an overload and points to the real constraint.<\/li>\n<li>Fix the constraint itself. Adding people will not solve a machine limit.<\/li>\n<li>A plan is only as good as its data. Measure real cycle times, stops and scrap, and revise the plan as conditions change.<\/li>\n<\/ul>\n<h2 id=\"table-of-contents\" tabindex=\"-1\">Vsebina<\/h2>\n<ul>\n<li><a href=\"#what-production-capacity-planning-is-and-why-it-matters\">What production capacity planning is and why it matters<\/a><\/li>\n<li><a href=\"#step-1-forecast-demand-over-the-right-horizon\">Step 1: Forecast demand over the right horizon<\/a><\/li>\n<li><a href=\"#step-2-calculate-available-capacity\">Step 2: Calculate available capacity<\/a><\/li>\n<li><a href=\"#step-3-compare-required-and-available-capacity\">Step 3: Compare required and available capacity<\/a><\/li>\n<li><a href=\"#step-4-find-the-real-bottleneck\">Step 4: Find the real bottleneck<\/a><\/li>\n<li><a href=\"#step-5-choose-how-to-close-the-gap\">Step 5: Choose how to close the gap<\/a><\/li>\n<li><a href=\"#step-6-validate-on-the-shop-floor-and-keep-the-plan-current\">Step 6: Validate on the shop floor and keep the plan current<\/a><\/li>\n<li><a href=\"#where-manual-planning-breaks-down\">Where manual planning breaks down<\/a><\/li>\n<li><a href=\"#our-perspective\">Our perspective<\/a><\/li>\n<li><a href=\"#see-capacity-planning-data-on-real-machines\">See capacity planning data on real machines<\/a><\/li>\n<li><a href=\"#faq\">Pogosto zastavljena vpra\u0161anja<\/a><\/li>\n<li><a href=\"#sources\">Sources<\/a><\/li>\n<\/ul>\n<h2 id=\"what-production-capacity-planning-is-and-why-it-matters\" tabindex=\"-1\">What production capacity planning is and why it matters<\/h2>\n<p>Capacity planning belongs to the operational stage of planning. According to <a href=\"https:\/\/www.cips.org\/intelligence-hub\/operations-management\/capacity-requirement-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">CIPS<\/a>, it works alongside an MRP system and makes sure resources are available and goods are routed through to the finished line. A detailed plan gives production an operational-level overview of what is needed and when.<\/p>\n<p>For a plant manager, the practical value is simple:<\/p>\n<ul>\n<li>You promise delivery dates you can keep.<\/li>\n<li>You see overloads weeks ahead instead of discovering them on the floor.<\/li>\n<li>You avoid buying materials or releasing orders that the plant cannot process in time.<\/li>\n<li>You can justify investment, extra shifts or outsourcing with numbers.<\/li>\n<\/ul>\n<p>In Slovenia the labour side deserves particular attention. The <a href=\"https:\/\/www.oecd.org\/content\/dam\/oecd\/en\/publications\/reports\/2024\/07\/oecd-economic-surveys-slovenia-2024_37e8dc60\/bc4a107b-en.pdf\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">OECD\u2019s 2024 economic survey of Slovenia<\/a> describes weak manufacturing output alongside acute labour shortages, with over 40% of firms reporting shortages as a factor limiting production. A capacity plan that treats people availability as a real constraint, not an afterthought, matches that reality.<\/p>\n<h2 id=\"step-1-forecast-demand-over-the-right-horizon\" tabindex=\"-1\">Step 1: Forecast demand over the right horizon<\/h2>\n<p>Capacity decisions work on different time scales. CIPS divides capacity management into short- and medium-term capacity review, based on a demand forecast of 2 to 18 months, and an aggregate capacity review across the whole organisation.<\/p>\n<p>A useful way to organise this:<\/p>\n<table>\n<thead>\n<tr>\n<th>Horizon<\/th>\n<th>Question<\/th>\n<th>Typical decision<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Long term<\/td>\n<td>Do we have the right machines and space?<\/td>\n<td>Equipment, facility, outsourcing partners<\/td>\n<\/tr>\n<tr>\n<td>Medium term<\/td>\n<td>Can we cover the coming months?<\/td>\n<td>Hiring, cross-training, shift patterns<\/td>\n<\/tr>\n<tr>\n<td>Short term<\/td>\n<td>Can this week\u2019s schedule be run?<\/td>\n<td>Overtime, reprioritising, resequencing<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Start with your sales forecast and confirmed orders. Convert both into units per week or month, by product family. Do not forecast in money, because capacity is consumed in machine hours and labour hours.<\/p>\n<h2 id=\"step-2-calculate-available-capacity\" tabindex=\"-1\">Step 2: Calculate available capacity<\/h2>\n<p>Theoretical capacity is what a machine could do running non-stop. Effective capacity is what it can deliver in practice. <a href=\"https:\/\/www.scribd.com\/document\/77400188\/CAPACITY-PLANNING-DECISION-THEORY-PROCESS-SELECTION-AND-FACILITY-LAYOUT-and-LINEAR-PROGRAMMING\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Capacity planning literature<\/a> notes that effective capacity is typically lower than design capacity because of product mix, scheduling difficulties, machine maintenance and quality factors.<\/p>\n<h3 id=\"the-inputs-you-need\" tabindex=\"-1\">The inputs you need<\/h3>\n<p>The <a href=\"https:\/\/www.odette.org\/uploads\/resources\/document\/LG11_Production_Capacity_Assessment-Tool.pdf\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Odette Production Capacity Assessment Tool<\/a> shows which figures a serious calculation includes:<\/p>\n<ul>\n<li>the process macro-steps<\/li>\n<li>opening hours per week<\/li>\n<li>target cycle time in seconds per part<\/li>\n<li>planned load rate<\/li>\n<li>customer demand<\/li>\n<li>parts per cycle<\/li>\n<li>number of direct workers<\/li>\n<\/ul>\n<h3 id=\"three-determinants-of-process-capacity\" tabindex=\"-1\">Three determinants of process capacity<\/h3>\n<p>At plant level, <a href=\"https:\/\/www.innovaltec.com\/plant-capacity-modelling-blog\/\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Innoval Technology<\/a> highlights three determinants: process uptime (planned and unplanned downtime and changeovers), product mix, and process efficiency for the products in the mix. Keep these three in your model and you cover most of the gap between nameplate and real output.<\/p>\n<h3 id=\"a-worked-example\" tabindex=\"-1\">A worked example<\/h3>\n<p>Take one CNC machining cell. The figures below are illustrative, not data from a real plant.<\/p>\n<ul>\n<li>Opening hours: 2 shifts \u00d7 8 hours \u00d7 5 days = 80 hours per week<\/li>\n<li>Planned maintenance and breaks: 6 hours<\/li>\n<li>Average changeovers: 4 per week \u00d7 1 hour = 4 hours<\/li>\n<li>Expected unplanned stops: 5 hours<\/li>\n<li>Available productive time: 80 \u2212 6 \u2212 4 \u2212 5 = 65 hours<\/li>\n<li>Cycle time: 90 seconds per part, so 40 parts per hour<\/li>\n<li>Expected good-part rate: 97%<\/li>\n<\/ul>\n<p>Effective weekly capacity = 65 \u00d7 40 \u00d7 0.97 = 2,522 good parts.<\/p>\n<p>If the nameplate calculation had used 80 hours and no losses, it would have promised 3,200 parts. The difference of nearly 700 parts is the gap that causes missed deliveries. For a longer, copyable version of this arithmetic, see our <a href=\"https:\/\/mestric.com\/sl\/izracun-kapacitet-proizvodnje\/\" target=\"_blank\" rel=\"noopener\">capacity calculation with a worked example<\/a>. If your cycle times come from takt time, our <a href=\"https:\/\/mestric.com\/sl\/takt-time-izracun\/\" target=\"_blank\" rel=\"noopener\">takt time calculation guide<\/a> shows how to derive them.<\/p>\n<h2 id=\"step-3-compare-required-and-available-capacity\" tabindex=\"-1\">Step 3: Compare required and available capacity<\/h2>\n<p>Now translate demand into load. A common approach is to compare required and available capacity in hours per week for each resource, or per week for each production line. <a href=\"https:\/\/www.smartsheet.com\/content\/rough-cut-capacity-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Smartsheet\u2019s guide to rough-cut capacity planning<\/a> describes the capacity-load ratio as required capacity divided by available capacity.<\/p>\n<p>Continuing the example, suppose demand for the next four weeks requires 2,900 good parts per week from this cell. Required hours = 2,900 \u00f7 0.97 \u00f7 40 = about 74.7 hours. Available hours are 65.<\/p>\n<p>Capacity-load ratio = 74.7 \u00f7 65 = 115%.<\/p>\n<p>The cell is overloaded by 15%. A ratio below 100% means spare capacity, while above 100% needs action.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/mestric.com\/wp-content\/uploads\/2026\/11\/1793678520978_Required-hours-exceed-available-capacity-by-15-percent.jpeg\" alt=\"Required hours exceed available capacity by 15 percent\"><\/p>\n<h3 id=\"rough-cut-capacity-planning\" tabindex=\"-1\">Rough-cut capacity planning<\/h3>\n<p>Rough-cut capacity planning (RCCP) does this check against the master production schedule. As described by <a href=\"https:\/\/opess.ethz.ch\/course\/section-5-2\/5-2-3c-rough-cut-capacity-planning-rccp\/\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">ETH Zurich\u2019s course material<\/a>, it converts the schedule into required capacity and tests whether key resources can produce the desired output in each period. Smartsheet adds that RCCP is a long-term technique for validating the master production schedule before excess material is purchased or released.<\/p>\n<p>This is also where external limits matter. Dispatch deadlines such as <a href=\"https:\/\/blog.simplyparcel.sg\/blog\/shipping-cut-off-times\" target=\"_blank\" rel=\"noopener\">shipping cut-off times<\/a> mean output finished after a certain hour effectively ships a day later, so your plan should count finished and shippable capacity, not only machine hours.<\/p>\n<h3 id=\"the-100-rule-across-products\" tabindex=\"-1\">The 100% rule across products<\/h3>\n<p>Odette warns that the global load of a production means, across all products and customers, must not exceed 100%. Check each product on its own and then check the sum. A line that looks fine for each customer can still be overbooked in total.<\/p>\n<h2 id=\"step-4-find-the-real-bottleneck\" tabindex=\"-1\">Step 4: Find the real bottleneck<\/h2>\n<p>Quickbase advises that a capacity plan should <a href=\"https:\/\/www.quickbase.com\/blog\/what-is-capacity-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">identify shortages or surpluses and locate the actual constraint<\/a> before you add any resources. In practice, the resource with the highest load ratio sets the pace of the whole flow. Improving a machine that is already below 80% load changes nothing for delivery.<\/p>\n<p>Look for these signs:<\/p>\n<ul>\n<li>Work-in-progress piling up in front of one operation<\/li>\n<li>Downstream machines waiting for parts<\/li>\n<li>One resource with a ratio near or above 100% every week<\/li>\n<li>Frequent expediting for the same operation<\/li>\n<\/ul>\n<p>Our guide on <a href=\"https:\/\/mestric.com\/sl\/kako-ucinkovito-prepoznati-ozka-grla-v-proizvodnji\/\" target=\"_blank\" rel=\"noopener\">how to identify production bottlenecks<\/a> explains the methods in more detail, and <a href=\"https:\/\/mestric.com\/sl\/improve-manufacturing-efficiency-with-process-mapping\/\" target=\"_blank\" rel=\"noopener\">process mapping<\/a> helps you see where flow stops between operations.<\/p>\n<h2 id=\"step-5-choose-how-to-close-the-gap\" tabindex=\"-1\">Step 5: Choose how to close the gap<\/h2>\n<p>When demand exceeds capacity, or falls well below it, you need a plan. CIPS describes the workflow as forecasting aggregate demand, identifying capacity plans, selecting the most suitable plan under constraints, confirming material availability and issuing work orders to production.<\/p>\n<p>Quickbase lists these typical responses to a capacity gap:<\/p>\n<ul>\n<li>adjusting the schedule<\/li>\n<li>redistributing workload between resources<\/li>\n<li>adding shifts or overtime<\/li>\n<li>hiring or cross-training<\/li>\n<li>expanding equipment or facilities<\/li>\n<li>outsourcing<\/li>\n<li>reprioritising orders<\/li>\n<\/ul>\n<p>Match the response to the cause. If the gap is on a machine, extra workers will not fix it, and the same source makes that point directly. If it comes from changeovers, resequencing orders by product family may recover hours at no cost. If it comes from absences or a lack of skilled operators, cross-training gives you flexibility across cells.<\/p>\n<p>In our example, the 15% overload could be addressed by:<\/p>\n<ol>\n<li>Cutting changeovers from four to three per week through better sequencing, recovering one hour.<\/li>\n<li>Reducing unplanned stops by two hours through targeted maintenance.<\/li>\n<li>Adding one Saturday shift for the remaining gap, or moving a low-margin product to another cell.<\/li>\n<\/ol>\n<p>Capacity planning is cross-functional. In CIPS\u2019s description, operations validate feasibility, procurement secures materials, planning confirms the plan and production executes the work order. Agree the plan in one meeting with all four functions, not by email chains.<\/p>\n<h2 id=\"step-6-validate-on-the-shop-floor-and-keep-the-plan-current\" tabindex=\"-1\">Step 6: Validate on the shop floor and keep the plan current<\/h2>\n<p>Target figures alone do not establish what a line really delivers. Odette\u2019s approach is to validate capacity through an observed production run. During the run you measure:<\/p>\n<ul>\n<li>cycle time<\/li>\n<li>good, scrapped and reworked parts<\/li>\n<li>planned and unplanned stops<\/li>\n<li>number of direct workers<\/li>\n<\/ul>\n<p>You then compare the observed capacity with the estimated target capacity and the customer demand, and define improvement actions. Even outside heavy industry, the same logic applies: a shop weighing <a href=\"https:\/\/pulsemerch.com\/in-house-screen-printing-benefits\" target=\"_blank\" rel=\"noopener\">in-house screen printing ROI<\/a> against its monthly order volume needs measured output per run before the comparison means anything.<\/p>\n<p>Quickbase adds that plans must be monitored by comparing actual demand and utilisation with the forecast, then revised when orders, projects, equipment availability or staffing change. A monthly review is a minimum. In volatile order situations, review weekly.<\/p>\n<h3 id=\"common-mistakes-to-avoid\" tabindex=\"-1\">Common mistakes to avoid<\/h3>\n<ul>\n<li>Using nameplate speed instead of measured cycle time.<\/li>\n<li>Ignoring changeovers and product mix.<\/li>\n<li>Planning each product separately and missing the combined load.<\/li>\n<li>Treating the plan as a yearly document instead of a living one.<\/li>\n<li>Adding labour to a machine constraint.<\/li>\n<\/ul>\n<h2 id=\"where-manual-planning-breaks-down\" tabindex=\"-1\">Where manual planning breaks down<\/h2>\n<p>Spreadsheets work for a handful of machines. They struggle when cycle times drift, stops are logged by hand at the end of a shift, and the plan is updated once a week. The data feeding the capacity calculation is then days old and often incomplete.<\/p>\n<p>The fix is to collect it automatically. When machines report their state, counts and stops directly, you get actual availability, performance and quality per resource without retyping. Our articles on <a href=\"https:\/\/mestric.com\/sl\/real-time-production-data\/\" target=\"_blank\" rel=\"noopener\">real-time production data<\/a> and <a href=\"https:\/\/mestric.com\/sl\/zakaj-integracija-strojev-s-programsko-opremo-steje\/\" target=\"_blank\" rel=\"noopener\">machine integration<\/a> explain what this changes in practice. If you want to see how plans react to disruption, our <a href=\"https:\/\/mestric.com\/sl\/dinamicno-replaniranje-proizvodnje\/\" target=\"_blank\" rel=\"noopener\">90 day dynamic replanning pilot<\/a> outlines a KPI-based approach for planners, and our <a href=\"https:\/\/mestric.com\/sl\/planiranje-zmogljivosti-linij\/\" target=\"_blank\" rel=\"noopener\">line capacity playbook<\/a> goes deeper into line-level planning.<\/p>\n<h2 id=\"our-perspective\" tabindex=\"-1\">Our perspective<\/h2>\n<blockquote>\n<p>We see the same pattern in many plants: the capacity plan is sound on paper, but it rests on cycle times and availability figures that nobody has measured recently. The plan then drifts away from reality, and planners spend their week explaining why.<\/p>\n<p>That is why we built Mestric\u2122 around a connection to the equipment itself. Our system is designed to collect production data automatically, show KPIs such as performance, downtime and quality parameters in real time, and give production managers a live picture of where the bottleneck is today, not last month.<\/p>\n<p>Our view is that capacity planning improves most when three things come together: a clear method, like the one in this guide, trustworthy shop floor data, and fast feedback when conditions change. With those in place, the plan becomes a tool you use every day, and AI-powered optimisation can help you find process improvements you would otherwise miss.<\/p>\n<p><em>Andra\u017e<\/em><\/p>\n<\/blockquote>\n<h2 id=\"see-capacity-planning-data-on-real-machines\" tabindex=\"-1\">See capacity planning data on real machines<\/h2>\n<p>Mestric\u2122 is a Manufacturing Execution System that connects directly with your manufacturing equipment and presents KPIs, downtime, quality parameters and cost analysis in one view. It is designed to help you spot bottlenecks, reduce manual errors and base capacity decisions on live figures. You can see it working in a real production environment through an onsite presentation at our demo centre.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/mestric.com\/wp-content\/uploads\/2026\/09\/1771068359718_mestric.jpg\" alt=\"Mestric\"><\/p>\n<p>Learn more about the <a href=\"https:\/\/mestric.com\/sl\/o-resitvi\/\" target=\"_blank\" rel=\"noopener\">Mestric\u2122 MES platform<\/a>, or read how <a href=\"https:\/\/mestric.com\/sl\/mes-vs-traditional-manufacturing-boost-efficiency-2026\/\" target=\"_blank\" rel=\"noopener\">MES compares with traditional manufacturing<\/a>.<\/p>\n<h2 id=\"faq\" tabindex=\"-1\">Pogosto zastavljena vpra\u0161anja<\/h2>\n<h3 id=\"what-is-the-difference-between-capacity-planning-and-production-scheduling\" tabindex=\"-1\">What is the difference between capacity planning and production scheduling?<\/h3>\n<p>Capacity planning checks whether resources can cover expected demand over weeks or months. Scheduling decides which order runs on which machine and when, within the capacity you have. The first sets the limits, the second works inside them. Our guide to <a href=\"https:\/\/mestric.com\/sl\/what-is-production-scheduling-a-guide-for-manufacturers\/\" target=\"_blank\" rel=\"noopener\">production scheduling<\/a> covers the second in detail.<\/p>\n<h3 id=\"how-often-should-i-update-a-capacity-plan\" tabindex=\"-1\">How often should I update a capacity plan?<\/h3>\n<p>Review it at least monthly and whenever orders, equipment availability or staffing change significantly. Quickbase recommends comparing actual demand and utilisation with the forecast and revising the plan when those inputs shift. In unstable demand, weekly reviews are more realistic.<\/p>\n<h3 id=\"which-figures-do-i-need-to-calculate-capacity-for-one-machine\" tabindex=\"-1\">Which figures do I need to calculate capacity for one machine?<\/h3>\n<p>You need opening hours, planned and unplanned downtime, changeover time, cycle time, parts per cycle and the good-part rate. Odette\u2019s assessment tool uses a similar set, including planned load rate and the number of direct workers. Measure them during a real production run, not from the machine\u2019s data sheet.<\/p>\n<h3 id=\"what-should-i-do-if-the-load-ratio-is-above-100\" tabindex=\"-1\">What should I do if the load ratio is above 100%?<\/h3>\n<p>First find which resource is the real constraint. Then choose the response that addresses that constraint: resequencing, reducing stops, an extra shift, cross-training, outsourcing or investment. Adding workers to a machine-limited process will not raise output.<\/p>\n<h2 id=\"sources\" tabindex=\"-1\">Sources<\/h2>\n<ul>\n<li><a href=\"https:\/\/www.cips.org\/intelligence-hub\/operations-management\/capacity-requirement-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Capacity Requirement Planning Guide, CIPS<\/a><\/li>\n<li><a href=\"https:\/\/www.odette.org\/uploads\/resources\/document\/LG11_Production_Capacity_Assessment-Tool.pdf\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Production Capacity Assessment Tool, Odette<\/a><\/li>\n<li><a href=\"https:\/\/www.smartsheet.com\/content\/rough-cut-capacity-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Guide to Rough-Cut Capacity Planning, Smartsheet<\/a><\/li>\n<li><a href=\"https:\/\/opess.ethz.ch\/course\/section-5-2\/5-2-3c-rough-cut-capacity-planning-rccp\/\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Rough-Cut Capacity Planning (RCCP), ETH Zurich<\/a><\/li>\n<li><a href=\"https:\/\/www.quickbase.com\/blog\/what-is-capacity-planning\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Capacity Planning: Strategies, Process, and Best Practices, Quickbase<\/a><\/li>\n<li><a href=\"https:\/\/www.innovaltec.com\/plant-capacity-modelling-blog\/\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Plant capacity modelling considerations, Innoval Technology<\/a><\/li>\n<li><a href=\"https:\/\/www.oecd.org\/content\/dam\/oecd\/en\/publications\/reports\/2024\/07\/oecd-economic-surveys-slovenia-2024_37e8dc60\/bc4a107b-en.pdf\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">OECD Economic Surveys: Slovenia 2024<\/a><\/li>\n<li><a href=\"https:\/\/www.scribd.com\/document\/77400188\/CAPACITY-PLANNING-DECISION-THEORY-PROCESS-SELECTION-AND-FACILITY-LAYOUT-and-LINEAR-PROGRAMMING\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">Capacity planning, decision theory and process selection<\/a><\/li>\n<\/ul>\n<h2 id=\"recommended\" tabindex=\"-1\">Priporo\u010deno<\/h2>\n<ul>\n<li><a href=\"https:\/\/mestric.com\/sl\/planiranje-zmogljivosti-linij\/\" target=\"_blank\" rel=\"noopener\">Planning line capacity: an advanced playbook for production managers<\/a><\/li>\n<li><a href=\"https:\/\/mestric.com\/sl\/izracun-kapacitet-proizvodnje\/\" target=\"_blank\" rel=\"noopener\">Production Planners: Copyable Capacity Calculation with Worked Example<\/a><\/li>\n<li><a href=\"https:\/\/mestric.com\/sl\/dinamicno-replaniranje-proizvodnje\/\" target=\"_blank\" rel=\"noopener\">90 day pilot: dynamic production replanning with KPIs for planners<\/a><\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Learn how to plan production capacity: calculate effective capacity, compare it with demand, find bottlenecks and keep the plan current with live shop floor data.<\/p>","protected":false},"author":1,"featured_media":1762,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1761","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-learn"],"acf":[],"_links":{"self":[{"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/posts\/1761","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/comments?post=1761"}],"version-history":[{"count":1,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/posts\/1761\/revisions"}],"predecessor-version":[{"id":1764,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/posts\/1761\/revisions\/1764"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/media\/1762"}],"wp:attachment":[{"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/media?parent=1761"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/categories?post=1761"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mestric.com\/sl\/wp-json\/wp\/v2\/tags?post=1761"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}