This dataset includes a consistent framework of annual, quarterly, and hourly energy demand and operational profiles for 63 U.S. manufacturing subsectors defined by NAICS classification, building on the county-level demand dataset "Updated U.S. Low-Temperature Heating and Cooling Demand by County and Sector" and the methods described in "Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States" (both linked below). The dataset integrates U.S. Energy Information Administration (EIA) Manufacturing Energy Consumption Survey (MECS) data with a quarterly operating schedule reconstruction based on the U.S. Census Bureau Quarterly Plant Capacity Utilization (QPC) dataset. A project-specific methodology (publication under consideration) is used to translate capacity utilization, operating days, and shift structures into consistent hourly operating schedules and end-use energy allocations. The dataset consists of three interconnected components. First, annual total thermal energy demand by end use and fuel type is estimated for each manufacturing subsector, including conventional boiler use, process heating, process cooling and refrigeration, and facility heating and cooling. County-level annual total thermal energy demand data are also included. Second, quarterly operating characteristics are derived from QPC-based utilization data and disaggregated into hours, shifts, and operating states, including full operation, transition, and non-operation, to represent industrial operating schedules. Third, these quarterly operating structures are converted into hourly load allocation profiles that distribute energy demand across the year at hourly resolution, ensuring consistency with both annual energy totals and operational constraints. Together, this framework provides a consistent, multi-scale representation of manufacturing energy demand across subsectors, fuels, end uses, time (annual to hourly), and geography (national to county level) and is designed for integration with power system modeling, industrial energy analysis, and high-resolution demand studies.