Recently, Industry 4.0 facilitates implementing several modular smart factories particularly the Cyber-Physical System. Due to enhanced growth in the Cyber-Physical System, privacy and security issues turned out to be the most significant factor all over the world. This paper demonstrates a complete co-design approach meant for integrating the cyberspace and physical space of a cyber-physical system. Various strategies and models regarding cyber and physical space are established in CPS. Apart from numerous co-design strategies, there are several parameters yet to be resolved and established. It becomes complicated and tricky to examine and explore the extremely best value since these parameters make up a very huge space. Therefore, a metaheuristic algorithm such as improved Fuzzy Harmonic Search Algorithm is proposed to optimize the control parameters so as to obtain a feasible solution. Also, this approach minimizes the cost function using Maximum Allowable Delay Bound (MADB) when subjected to several constraints such as the Sampling period, Horizon length, Routing graph, and scheduling table. Moreover the comparative analyses of various approaches such as Fuzzy Harmony Search (FHS) algorithm, Harmony Search (HS) algorithm, Grey Wolf Optimization Algorithm (GWO), Particle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm as well as Fuzzy Genetic Algorithm (Fuzzy GA) are evaluated to examine the performances of the proposed approach. A testbed is organized for evaluation and exploration in a manufacturing atmosphere. The result reveals that this proposed approach provides enhanced control performance and communication reliability even under very harsh environmental habitat.

最近，工业4.0促进了几个模块化智能工厂的实施，尤其是网络物理系统。由于网络物理系统的增长不断增强，隐私和安全性问题已成为全球范围内最重要的因素。本文演示了一种完整的协同设计方法，旨在集成网络物理系统的网络空间和物理空间。在CPS中建立了有关网络空间和物理空间的各种策略和模型。除了众多的协同设计策略外，还有一些参数尚待解决和建立。由于这些参数构成了非常大的空间，因此检查和探索极佳的价值变得复杂而棘手。所以，提出了一种改进的模糊谐波搜索算法等元启发式算法来优化控制参数，以求得可行的解决方案。同样，当受到一些约束（例如采样周期，水平长度，路由图和调度表）时，此方法使用最大允许延迟绑定（MADB）将成本函数最小化。此外，还对各种方法进行了比较分析，例如模糊和声搜索（FHS）算法，和声搜索（HS）算法，灰狼优化算法（GWO），粒子群优化（PSO）算法，差分演化（DE）算法以及模糊算法。评估了遗传算法（Fuzzy GA），以检查所提出方法的性能。组织了一个测试平台，用于在制造环境中进行评估和探索。