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| import streamlit as st | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import pandas as pd | |
| import math | |
| st.set_page_config( | |
| page_title="Ex-stream-ly Cool App", | |
| page_icon="🧊", | |
| layout="wide", | |
| initial_sidebar_state="expanded" | |
| ) | |
| st.title("Калькулятор Toyota 📦") | |
| st.subheader('Выбор склада. Insource vs Outsource') | |
| Number_of_incoming_pallets = st.number_input('Количество поступаемых паллет, паллет/месяц', value=40) | |
| Number_of_pallets_shipped = st.number_input('Количество отгружаемых паллет, паллет/месяц', value=40) | |
| The_average_cost_of_one_product = st.number_input('Средняя стоимость одного товара, руб.', value=3000) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.write('Характеристики insource склада') | |
| The_cost_of_warehouse_maintenance_services = st.number_input('Стоимость услуг по обеспечению склада, руб./месяц', value=50000) | |
| Average_salary = st.number_input('Средняя зарпала, сотрудник', value=50850) | |
| Equipment_breakdown_rate_in_stock = st.number_input('Коэффициент поломки оборудования на складе, %', value=5) | |
| The_cost_of_equipment_repair_in_the_warehouse = st.number_input('Стоимость ремонта оборудования на складе, руб./шт.', value=20000) | |
| The_cost_of_warehouse_information_support = st.number_input('Стоимость информационной поддержки склада, руб./месяц', value=20000) | |
| Spoilage_coefficient = st.number_input('Коэффициент порчи, %', value=0.1) | |
| Number_of_working_hours_per_month = st.number_input('Количество рабочих часов в месяц, час', value=176) | |
| Average_number_of_goods_per_pallet = st.number_input('Среднее количество товаров в одном паллете, шт./палелт', value=120) | |
| Productivity_of_one_employee = st.number_input('Производительность одного сотрудника, паллетомест/час', value=0.2) | |
| with col2: | |
| st.write('Характеристики outsource склада') | |
| Number_of_storage_days = st.number_input('Количество дней хранения, дни', value=30) | |
| Warehouse_area = st.number_input('Площадь склада, м2', value=150) | |
| Storage_mezzanine = st.number_input('Стоимость хранения мезонина, руб. за м2/сутки', value=22.35) | |
| Unloading_of_pallets_to_the_storage_place = st.number_input('Стоимость выгрузки паллет на место хранения, руб./паллета', value=120) | |
| Acceptance = st.number_input('Стоимость приемки, руб./паллет', value=125.9) | |
| Selection_of_spare_parts = st.number_input('Стоимость подбор запчастей, руб./паллет', value=183) | |
| Shipment_of_spare_parts = st.number_input('Стоимость отгрузки запчастей, руб./паллет', value=120) | |
| Registration_of_documents_entry_or_exit = st.number_input('Стоимость оформление документов вход/выход, руб./комплект', value=130) | |
| Transaction_percentage = st.number_input('Процент транзакции, %', value=1) | |
| def get_average_number_of_damaged_goods(): | |
| return (Number_of_incoming_pallets + Number_of_pallets_shipped) * Spoilage_coefficient * Average_number_of_goods_per_pallet / 100 | |
| def get_cnt_emplyes_and_equipment(): | |
| The_number_of_pallets_processed_by_one_employee = Productivity_of_one_employee * Number_of_working_hours_per_month | |
| Number_of_employees = math.ceil((Number_of_incoming_pallets + Number_of_pallets_shipped) / The_number_of_pallets_processed_by_one_employee) | |
| return Number_of_employees, Number_of_employees | |
| def get_insource_cost(): | |
| Wage_fund = Number_of_employees * Average_salary | |
| The_cost_of_repairing_broken_equipment = Number_of_equipment * The_cost_of_equipment_repair_in_the_warehouse * Equipment_breakdown_rate_in_stock / 100 | |
| Spoilage = Average_number_of_damaged_goods * The_average_cost_of_one_product | |
| return {'Обеспечение склада': The_cost_of_warehouse_maintenance_services, | |
| 'ФОТ': Wage_fund, | |
| 'Информационная поддержка': The_cost_of_warehouse_information_support, | |
| 'Ремонт оборудования': The_cost_of_repairing_broken_equipment, | |
| 'Порча товара': Spoilage, | |
| 'Общие расходы': The_cost_of_warehouse_maintenance_services + Wage_fund + The_cost_of_repairing_broken_equipment + The_cost_of_warehouse_information_support + Spoilage} | |
| def get_outsource_cost(): | |
| Total_cost_of_storage_of_goods = Number_of_storage_days * Warehouse_area * Storage_mezzanine | |
| The_cost_of_unloading_pallets_at_the_storage_location = Unloading_of_pallets_to_the_storage_place * Number_of_incoming_pallets | |
| The_cost_of_shipping_the_goods_from_the_storage_location = Shipment_of_spare_parts * Number_of_pallets_shipped | |
| The_cost_of_acceptance_of_the_goods = Acceptance * Number_of_incoming_pallets | |
| The_cost_of_product_selection = Selection_of_spare_parts * Number_of_pallets_shipped | |
| The_cost_of_registration_of_documents = (Number_of_incoming_pallets + Number_of_pallets_shipped) * Registration_of_documents_entry_or_exit | |
| Costs = Total_cost_of_storage_of_goods + The_cost_of_unloading_pallets_at_the_storage_location \ | |
| + The_cost_of_shipping_the_goods_from_the_storage_location + The_cost_of_acceptance_of_the_goods \ | |
| + The_cost_of_product_selection + The_cost_of_registration_of_documents | |
| Transaction_costs = Costs * Transaction_percentage / 100 | |
| return {'Хранение товара': Total_cost_of_storage_of_goods, | |
| 'Выгрузка паллет': The_cost_of_unloading_pallets_at_the_storage_location, | |
| 'Отгрузка паллет': The_cost_of_shipping_the_goods_from_the_storage_location, | |
| 'Приемка товара': The_cost_of_acceptance_of_the_goods, | |
| 'Подбор товара': The_cost_of_product_selection, | |
| 'Оформление документов': The_cost_of_registration_of_documents, | |
| 'Транзакционные затраты': Transaction_costs, | |
| 'Общие расходы': Transaction_costs + Costs} | |
| if st.button('Расчет эффективности'): | |
| st.subheader('Вывод', anchor=None) | |
| Number_of_employees, Number_of_equipment = get_cnt_emplyes_and_equipment() | |
| Average_number_of_damaged_goods = get_average_number_of_damaged_goods() | |
| insource_cost = get_insource_cost() | |
| outsource_cost = get_outsource_cost() | |
| cost_data = pd.DataFrame({'Insource': insource_cost['Общие расходы'],'Outsource': outsource_cost['Общие расходы']}, index=['Общие расходы']).T | |
| st.write(f'Затраты Insource склад:', insource_cost['Общие расходы']) | |
| st.write(f'Затраты Outsource склад:', outsource_cost['Общие расходы']) | |
| insource_data = pd.DataFrame(insource_cost, index=['Расходы']).T | |
| outsource_data = pd.DataFrame(outsource_cost, index=['Расходы']).T | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.bar_chart(cost_data) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.write('Распределение затрат insource склада') | |
| st.bar_chart(insource_data) | |
| with col2: | |
| st.write('Распределение затрат outsource склада') | |
| st.bar_chart(outsource_data) | |