second task.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "23ec3952",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import plotly.express as px\n",
    "\n",
    "kuka_output = pd.read_excel('KukaOutput-ICNAP.xlsx', engine='openpyxl')\n",
    "kuka_output['EndDate'] = pd.to_datetime(kuka_output['EndDate'])\n",
    "t0 = kuka_output['EndDate'].iloc[0]\n",
    "kuka_output['EndDate min'] = (kuka_output['EndDate'] - t0).astype('timedelta64[m]')\n",
    "programs = pd.read_excel('OvenPrograms-ICNAP.xlsx', engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "67524dde",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Oven:\n",
    "    def __init__(self, index, finish_time=0, temp=0, rotor_list=[]):\n",
    "        self.index = index\n",
    "        self.finish_time = finish_time\n",
    "        self.temp = temp\n",
    "        self.rotor_list = rotor_list\n",
    "    \n",
    "    def get_time_per_product(self, time_available, duration, l):\n",
    "        if time_available > self.finish_time:\n",
    "            return time_available + (duration/l)\n",
    "        return self.finish_time + (duration/l)\n",
    "\n",
    "    def get_enter_time(self, time_available):\n",
    "        if time_available > self.finish_time:\n",
    "            return time_available\n",
    "        return self.finish_time\n",
    "    \n",
    "    def dif_temperature(self, target_temp):\n",
    "        return target_temp-self.temp\n",
    "    \n",
    "    def add_rotor(self, time_available, duration, cold_temp, index):\n",
    "        self.temp = cold_temp\n",
    "        self.rotor_list.append(index)\n",
    "        if time_available > self.finish_time:\n",
    "            self.finish_time = time_available + duration\n",
    "            \n",
    "        else:\n",
    "            self.finish_time += duration\n",
    "        \n",
    "class Node:\n",
    "    def __init__(self, path, remaining_df, ovens, node_dict):\n",
    "        self.path = path\n",
    "        self.remaining_df = remaining_df\n",
    "        self.ovens = ovens\n",
    "        self.node_dict = node_dict\n",
    "        \n",
    "    def get_neighboors(self):\n",
    "        if self.remaining_df.shape[0] > 10:\n",
    "            max_iter = 8\n",
    "        else:\n",
    "            max_iter = self.remaining_df.shape[0]\n",
    "        \n",
    "        ns = [self.get_neighboor(i) for i in range(max_iter)]\n",
    "        return list(filter(lambda n: n['Lambda']<=max_lambda, ns))\n",
    "            \n",
    "    def get_next(self):\n",
    "        neighboors = self.get_neighboors()\n",
    "        best_cost = min([n['MinCost'] for n in neighboors])\n",
    "        next_n_index = [n['MinCost'] for n in neighboors].index(min([n['MinCost'] for n in neighboors]))\n",
    "        return neighboors[next_n_index]\n",
    "    \n",
    "    def get_neighboor(self, index):\n",
    "        n = dict()\n",
    "        n['Product'] = self.remaining_df['Product'].iloc[index]\n",
    "        n['TimeAvailable'] = self.remaining_df['EndDate min'].iloc[index]\n",
    "        n['Duration'] = programs[programs['product type']==n['Product']]['program duration (min)'].values[0] + 60\n",
    "        n['TargetTemp'] = programs[programs['product type']==n['Product']]['target temp (C)'].values[0]\n",
    "        n['CoolTemp'] = programs[programs['product type']==n['Product']]['cooling temp  (C)'].values[0]\n",
    "        df_index = self.remaining_df.iloc[:index+1]\n",
    "        n['Lambda'] = df_index[df_index['Product']==n['Product']].shape[0]\n",
    "        n['ProductIndexes'] = list(df_index[df_index['Product']==n['Product']].index)\n",
    "        n['ProductTimes'] = [oven.get_time_per_product(n['TimeAvailable'], n['Duration'], n['Lambda']) for oven in self.ovens]\n",
    "        n['ProductDifTemps'] = [oven.dif_temperature(n['TargetTemp'])/n['Lambda'] for oven in self.ovens]\n",
    "        n['Costs'] = [self.calculate_cost(n['ProductTimes'][i], n['ProductDifTemps'][i]) for i in range(len(n['ProductTimes']))]\n",
    "        n['MinCost'] = min(n['Costs'])\n",
    "        n['OvenIndex'] = n['Costs'].index(n['MinCost'])\n",
    "        n['EnterTime'] = self.ovens[n['OvenIndex']].get_enter_time(n['TimeAvailable'])\n",
    "        n['DifTemperature'] = self.ovens[n['OvenIndex']].dif_temperature(n['TargetTemp'])\n",
    "        n['TimesAvailables'] = self.remaining_df['EndDate min'].loc[n['ProductIndexes']]\n",
    "        n['WaitingTimes'] = [n['EnterTime']-time for time in n['TimesAvailables']]\n",
    "        n['SumWaitingTime'] = sum(n['WaitingTimes'])\n",
    "        n['MeanWaitingTime'] = sum(n['WaitingTimes'])/len(n['WaitingTimes'])\n",
    "        return n\n",
    "    \n",
    "    def calculate_cost(self, time, temp):\n",
    "        percentage_temp = temp*0.3/291\n",
    "        percentage_time = time*0.7/920\n",
    "        return percentage_temp+percentage_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "fd948f78",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Product</th>\n",
       "      <th>TimeAvailable</th>\n",
       "      <th>Duration</th>\n",
       "      <th>TargetTemp</th>\n",
       "      <th>CoolTemp</th>\n",
       "      <th>Lambda</th>\n",
       "      <th>ProductIndexes</th>\n",
       "      <th>ProductTimes</th>\n",
       "      <th>ProductDifTemps</th>\n",
       "      <th>Costs</th>\n",
       "      <th>...</th>\n",
       "      <th>OvenIndex</th>\n",
       "      <th>EnterTime</th>\n",
       "      <th>DifTemperature</th>\n",
       "      <th>TimesAvailables</th>\n",
       "      <th>WaitingTimes</th>\n",
       "      <th>SumWaitingTime</th>\n",
       "      <th>MeanWaitingTime</th>\n",
       "      <th>JobStart</th>\n",
       "      <th>JobFinish</th>\n",
       "      <th>ProductIndexesText</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Rotor A3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>450</td>\n",
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       "      <td>2022-02-01 01:02:47</td>\n",
       "      <td>2022-02-01 08:32:47</td>\n",
       "      <td>[0, 1]</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rotor A3</td>\n",
       "      <td>338.0</td>\n",
       "      <td>450</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>42.60678</td>\n",
       "      <td>2</td>\n",
       "      <td>[4, 5]</td>\n",
       "      <td>[676.0, 563.0, 563.0, 563.0, 563.0, 563.0]</td>\n",
       "      <td>[138.472035, 159.775425, 159.775425, 159.77542...</td>\n",
       "      <td>[0.6571025013446885, 0.593086498207082, 0.5930...</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>338.0</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>4    199.0\n",
       "5    338.0\n",
       "Name: EndDate min, dtype...</td>\n",
       "      <td>[139.0, 0.0]</td>\n",
       "      <td>139.0</td>\n",
       "      <td>69.500000</td>\n",
       "      <td>2022-02-01 06:39:47</td>\n",
       "      <td>2022-02-01 14:09:47</td>\n",
       "      <td>[4, 5]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rotor B3</td>\n",
       "      <td>532.0</td>\n",
       "      <td>300</td>\n",
       "      <td>326.65198</td>\n",
       "      <td>71.01130</td>\n",
       "      <td>3</td>\n",
       "      <td>[8, 9, 10]</td>\n",
       "      <td>[632.0, 888.0, 632.0, 632.0, 632.0, 632.0]</td>\n",
       "      <td>[94.68173333333333, 94.68173333333333, 108.883...</td>\n",
       "      <td>[0.5784795995816524, 0.7732622082773045, 0.593...</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>532.0</td>\n",
       "      <td>284.04520</td>\n",
       "      <td>8     525.0\n",
       "9     532.0\n",
       "10    532.0\n",
       "Name: EndD...</td>\n",
       "      <td>[7.0, 0.0, 0.0]</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.333333</td>\n",
       "      <td>2022-02-01 09:53:47</td>\n",
       "      <td>2022-02-01 14:53:47</td>\n",
       "      <td>[8, 9, 10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rotor A2</td>\n",
       "      <td>365.0</td>\n",
       "      <td>450</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>42.60678</td>\n",
       "      <td>2</td>\n",
       "      <td>[3, 7]</td>\n",
       "      <td>[1057.0, 1013.0, 590.0, 590.0, 590.0, 590.0]</td>\n",
       "      <td>[124.26977500000001, 138.472035, 159.775425, 1...</td>\n",
       "      <td>[0.9323523005378753, 0.9135155448229493, 0.613...</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>365.0</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>3    136.0\n",
       "7    365.0\n",
       "Name: EndDate min, dtype...</td>\n",
       "      <td>[229.0, 0.0]</td>\n",
       "      <td>229.0</td>\n",
       "      <td>114.500000</td>\n",
       "      <td>2022-02-01 07:06:47</td>\n",
       "      <td>2022-02-01 14:36:47</td>\n",
       "      <td>[3, 7]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rotor A4</td>\n",
       "      <td>127.0</td>\n",
       "      <td>460</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>42.60678</td>\n",
       "      <td>1</td>\n",
       "      <td>[2]</td>\n",
       "      <td>[1292.0, 1248.0, 1275.0, 587.0, 587.0, 587.0]</td>\n",
       "      <td>[248.53955000000002, 276.94407, 276.94407, 319...</td>\n",
       "      <td>[1.2392698184670552, 1.2350745679067683, 1.255...</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>127.0</td>\n",
       "      <td>319.55085</td>\n",
       "      <td>2    127.0\n",
       "Name: EndDate min, dtype: float64</td>\n",
       "      <td>[0.0]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2022-02-01 03:08:47</td>\n",
       "      <td>2022-02-01 10:48:47</td>\n",
       "      <td>[2]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Product  TimeAvailable  Duration  TargetTemp  CoolTemp  Lambda  \\\n",
       "0  Rotor A3            1.0       450   319.55085  42.60678       2   \n",
       "1  Rotor A3          338.0       450   319.55085  42.60678       2   \n",
       "2  Rotor B3          532.0       300   326.65198  71.01130       3   \n",
       "3  Rotor A2          365.0       450   319.55085  42.60678       2   \n",
       "4  Rotor A4          127.0       460   319.55085  42.60678       1   \n",
       "\n",
       "  ProductIndexes                                   ProductTimes  \\\n",
       "0         [0, 1]     [226.0, 226.0, 226.0, 226.0, 226.0, 226.0]   \n",
       "1         [4, 5]     [676.0, 563.0, 563.0, 563.0, 563.0, 563.0]   \n",
       "2     [8, 9, 10]     [632.0, 888.0, 632.0, 632.0, 632.0, 632.0]   \n",
       "3         [3, 7]   [1057.0, 1013.0, 590.0, 590.0, 590.0, 590.0]   \n",
       "4            [2]  [1292.0, 1248.0, 1275.0, 587.0, 587.0, 587.0]   \n",
       "\n",
       "                                     ProductDifTemps  \\\n",
       "0  [159.775425, 159.775425, 159.775425, 159.77542...   \n",
       "1  [138.472035, 159.775425, 159.775425, 159.77542...   \n",
       "2  [94.68173333333333, 94.68173333333333, 108.883...   \n",
       "3  [124.26977500000001, 138.472035, 159.775425, 1...   \n",
       "4  [248.53955000000002, 276.94407, 276.94407, 319...   \n",
       "\n",
       "                                               Costs  ...  OvenIndex  \\\n",
       "0  [0.33667345472882115, 0.33667345472882115, 0.3...  ...          0   \n",
       "1  [0.6571025013446885, 0.593086498207082, 0.5930...  ...          1   \n",
       "2  [0.5784795995816524, 0.7732622082773045, 0.593...  ...          0   \n",
       "3  [0.9323523005378753, 0.9135155448229493, 0.613...  ...          2   \n",
       "4  [1.2392698184670552, 1.2350745679067683, 1.255...  ...          3   \n",
       "\n",
       "   EnterTime  DifTemperature  \\\n",
       "0        1.0       319.55085   \n",
       "1      338.0       319.55085   \n",
       "2      532.0       284.04520   \n",
       "3      365.0       319.55085   \n",
       "4      127.0       319.55085   \n",
       "\n",
       "                                     TimesAvailables     WaitingTimes  \\\n",
       "0  0    0.0\n",
       "1    1.0\n",
       "Name: EndDate min, dtype: fl...       [1.0, 0.0]   \n",
       "1  4    199.0\n",
       "5    338.0\n",
       "Name: EndDate min, dtype...     [139.0, 0.0]   \n",
       "2  8     525.0\n",
       "9     532.0\n",
       "10    532.0\n",
       "Name: EndD...  [7.0, 0.0, 0.0]   \n",
       "3  3    136.0\n",
       "7    365.0\n",
       "Name: EndDate min, dtype...     [229.0, 0.0]   \n",
       "4       2    127.0\n",
       "Name: EndDate min, dtype: float64            [0.0]   \n",
       "\n",
       "  SumWaitingTime  MeanWaitingTime            JobStart           JobFinish  \\\n",
       "0            1.0         0.500000 2022-02-01 01:02:47 2022-02-01 08:32:47   \n",
       "1          139.0        69.500000 2022-02-01 06:39:47 2022-02-01 14:09:47   \n",
       "2            7.0         2.333333 2022-02-01 09:53:47 2022-02-01 14:53:47   \n",
       "3          229.0       114.500000 2022-02-01 07:06:47 2022-02-01 14:36:47   \n",
       "4            0.0         0.000000 2022-02-01 03:08:47 2022-02-01 10:48:47   \n",
       "\n",
       "  ProductIndexesText  \n",
       "0             [0, 1]  \n",
       "1             [4, 5]  \n",
       "2         [8, 9, 10]  \n",
       "3             [3, 7]  \n",
       "4                [2]  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oven_list = [Oven(i, finish_time=0, temp=0, rotor_list=[]) for i in range(6)]\n",
    "path = []\n",
    "df_remaining = kuka_output.copy()\n",
    "current_node = Node(path, df_remaining, oven_list, {})\n",
    "max_lambda = 3\n",
    "\n",
    "while df_remaining.shape[0]>0:\n",
    "    next_node_dict = current_node.get_next()\n",
    "    oven_list[next_node_dict['OvenIndex']].add_rotor(next_node_dict['TimeAvailable'], next_node_dict['Duration'],\n",
    "                                                     next_node_dict['CoolTemp'], next_node_dict['ProductIndexes'])\n",
    "    df_remaining.drop(index=next_node_dict['ProductIndexes'], inplace=True)\n",
    "    path.append(current_node)\n",
    "    current_node = Node(path, df_remaining, oven_list, next_node_dict)\n",
    "    if df_remaining.shape[0] == 0:\n",
    "        path.append(current_node)\n",
    "\n",
    "node_dicts = [i.node_dict for i in path][1:]\n",
    "nodes_df = pd.DataFrame(node_dicts)\n",
    "nodes_df['JobStart'] = t0 + pd.to_timedelta(nodes_df['EnterTime'], unit='m')\n",
    "nodes_df['JobFinish'] = t0 + pd.to_timedelta(nodes_df[['EnterTime', 'Duration']].sum(axis=1), unit='m')\n",
    "nodes_df['ProductIndexesText'] = nodes_df['ProductIndexes'].astype(str)\n",
    "nodes_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "407c536e",
   "metadata": {},
   "outputs": [
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   "execution_count": 18,
   "id": "c081a614",
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     "execution_count": 18,
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   "id": "04fdfbd7",
   "metadata": {},
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   "source": [
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   "cell_type": "code",
   "execution_count": 27,
   "id": "bc4c570b",
   "metadata": {},
   "outputs": [],
   "source": [
    "oven_6_time = nodes_df[nodes_df['OvenIndex']==5]['Duration'].sum()"
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   "cell_type": "code",
   "execution_count": 28,
   "id": "82e1715f",
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   "outputs": [],
   "source": [
    "total_process_time = nodes_df[['EnterTime', 'Duration']].sum(axis=1).max()"
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   "execution_count": 29,
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   "id": "58b953db",
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Histogram with stack\"},\"barmode\":\"relative\"},                        {\"responsive\": true}                    ).then(function(){\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.histogram(x=waiting_list_times, title=\"Idle Histogram with stack\")\n",
    "fig.update_layout(yaxis_range=[0,300],xaxis_range=[0,4500])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "1de5818e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66.41619585687383"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(waiting_list_times)/len(waiting_list_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aab6b005",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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