Neil A. Duffie - Control Theory Applications for Dynamic Production Systems

66 50

67 51

68 52

69 53

70 54

71 55

72 56

73 57

74 58

75 59

76 60

77 61

78 62

79 63

80 64

81 65

82 66

83 67

84 68

85 69

86 70

87 71

88 72

89 73

90 74

91 75

92 76

93 77

94 78

95 79

96 80

97 81

98 82

99 83

100 84

101 85

102 86

103 87

104 88

105 89

106 90

107 91

108 92

109 93

110 94

111 95

112 96

113 97

114 98

115 99

116 100

117 101

118 102

119 103

120 104

121 105

122 106

123 107

124 108

125 109

126 110

127 111

128 112

129 113

130 114

131 115

132 116

133 117

134 118

135 119

136 120

137 121

138 122

139 123

140 124

141 125

142 126

143 127

144 128

145 129

146 130

147 131

148 132

149 133

150 134

151 135

152 136

153 137

154 138

155 139

156 140

157 141

158 142

159 143

160 144

161 145

162 146

163 147

164 148

165 149

166 150

167 151

168 152

169 153

170 154

171 155

172 156

173 157

174 158

175 159

176 160

177 161

178 162

179 163

180 164

181 165

182 166

183 167

184 168

185 169

186 170

187 171

188 172

189 173

190 174

191 175

192 176

193 177

194 178

195 179

196 180

197 181

198 182

199 183

200 184

201 185

202 186

203 187

204 188

205 189

206 190

207 191

208 192

209 193

210 194

211 195

212 196

213 197

214 198

215 199

216 200

217 201

218 202

219 203

220 204

221 205

222 206

223 207

224 208

225 209

226 210

227 211

228 212

229 213

230 214

231 215

232 216

233 217

234 218

235 219

236 220

237 221

238 222

239 223

240 224

241 225

242 226

243 227

244 228

245 229

246 230

247 231

248 232

249 233

250 234

251 235

252 236

253 237

254 238

255 239

256 240

257 241

258 242

259 243

260 244

261 245

262 246

263 247

264 248

265 249

266 250

267 251

268 252

269 253

270 254

271 255

272 256

273 257

274 258

275 259

276 260

277 261

278 262

279 263

280 264

281 265

282 266

283 267

284 268

285 269

286 270

287 271

288 272

289 273

290 274

291 275

292 276

293 277

294 278

295 279

296 280

297 281

298 282

299 283

300 284

301 285

302 286

303 287

304 288

305 289

306 290

307 291

308 292

309 293

310 294

311 295

312 296

313 297

314 298

315 299

316 300

317 301

318 302

319 303

320 304

Production planning, operations, and control are being transformed by digitalization, creating opportunities for automation of decision making, reduction of delays in making and implementing decisions, and significant improvement of production system performance. Meanwhile, to remain competitive, today’s production industries need to adapt to increasingly dynamic and turbulent markets. In this environment, production engineers and managers can benefit from tools of control system engineering that allow them to mathematically model, analyze, and design dynamic, changeable production systems with behavior that is effective and robust in the presence of turbulence. Research has shown that the tools of control system engineering are important additions to the production system engineer’s toolbox, complementing traditional tools such as discrete event simulation; however, many production engineers are unfamiliar with application of control theory in their field. This book is a practical yet thorough introduction to the use of transfer functions and control theoretical methods in the modeling, analysis, and design of the dynamic behavior of production systems. Production engineers and managers will find this book a valuable and fundamental resource for improving their understanding of the dynamic behavior of modern production systems and guiding their design of future production systems.

This book was written for a course entitled Smart Manufacturing at the University of Wisconsin-Madison, taught for graduate students working in industry. It has been heavily influenced by two decades of industry-oriented research, mainly in collaboration with colleagues in Germany, on control theory applications in analysis and design of the dynamic behavior of production systems. Motivated by this experience, the material in this book has been selected to

explain and illustrate how control theoretical methods can be used in a practical manner to understand and design the dynamic behavior of production systems

focus application examples on production systems that can include production processes, machines, work systems, factories, communication, and production networks

present both time-based and frequency-based analytical and design approaches along with illustrative examples to give production engineers important new perspectives and tools as production systems and networks become more complex and dynamic

apply control system engineering software in examples that illustrate how dynamic behavior of production systems can be analyzed and designed in practice

address both open-loop and closed-loop decision-making approaches

present discrete-time and continuous-time theory in an integrated manner, recognizing the discrete-time nature of adjustments that are made in the operation of many production systems and complementing the integrated nature of supporting tools in control system engineering software

recognize that delays are ever-present in production systems and illustrate modeling of delays and the detrimental effects that delays have on dynamic behavior

show in examples how information acquisition, information sharing, and digital technologies can improve the dynamic behavior of production systems

“bridge the gap” between production system engineering and control system engineering, illustrating how control theoretical methods and control system engineering software can be effective tools for production engineers.

This material is organized into the following chapters:

Chapter 1 Introduction . The many reasons why production engineers can benefit from becoming more familiar with the tools of control system engineering are discussed, including the increasingly dynamic and digital environment for which current and future production systems must be designed. Several examples are described that illustrate the opportunities that control theoretical time and frequency perspectives present for understanding and designing the dynamic behavior of production systems and their decision-making components.

Chapter 2 Continuous-Time and Discrete-Time Models of Production Systems . Methods for modeling the dynamic behavior of production systems are introduced, both for continuous-time and discrete-time production systems and components. The result of modeling is differential equations in the continuous-time case or difference equations in the discrete-time case. These describe how the outputs of a production system and its components vary with time as a function of their time-varying inputs. The concepts of linearizing a model around an operating point and linearization using piecewise approximations also are presented.