This paper presents simple analytic rules for model reduction and PID controller tuning. The aim is to provide tuning rules that are easy to use and result in good closed-loop performance. The rules are based on the IMC-PID tuning method, which has been widely accepted in industry. The integral term of the PID controller is modified to improve disturbance rejection for integrating processes. A single tuning rule is provided for first- or second-order time delay models, avoiding the need for separate rules for each transfer function. Simple analytic rules for model reduction are also presented, including the "half rule" for estimating effective time delay. The paper first describes the problem of PID controller tuning, noting that despite having only three parameters, finding good settings is not straightforward. The proposed two-step procedure involves obtaining a first- or second-order time delay model and then deriving model-based controller settings. The first step involves approximating the process model, while the second step involves deriving the controller settings based on the model. The paper discusses the use of the half rule for estimating effective time delay, which is a key part of the model reduction process. The half rule is used to distribute the largest neglected time constant evenly between the effective delay and the smallest retained time constant. This approach helps maintain the robustness of the controller settings. The paper also presents the derivation of PID tuning rules using direct synthesis (IMC tuning) for setpoints. The controller settings are derived based on the desired closed-loop response, and the integral time is modified to improve disturbance rejection. The paper also discusses the use of the SIMC-PID tuning rules, which are based on the half rule and provide good performance for both integrating and pure time delay processes. The paper evaluates the proposed tuning rules on various processes, showing that they provide good performance and robustness. The results show that the SIMC-PID settings are effective for a wide range of processes, including integrating processes, pure time delay processes, and second-order processes with dominant dynamics. The paper also compares the proposed rules with other tuning methods, showing that they provide better performance and robustness in many cases. The paper concludes that the simple analytic rules for model reduction and PID tuning are effective and practical for a wide range of industrial processes.This paper presents simple analytic rules for model reduction and PID controller tuning. The aim is to provide tuning rules that are easy to use and result in good closed-loop performance. The rules are based on the IMC-PID tuning method, which has been widely accepted in industry. The integral term of the PID controller is modified to improve disturbance rejection for integrating processes. A single tuning rule is provided for first- or second-order time delay models, avoiding the need for separate rules for each transfer function. Simple analytic rules for model reduction are also presented, including the "half rule" for estimating effective time delay. The paper first describes the problem of PID controller tuning, noting that despite having only three parameters, finding good settings is not straightforward. The proposed two-step procedure involves obtaining a first- or second-order time delay model and then deriving model-based controller settings. The first step involves approximating the process model, while the second step involves deriving the controller settings based on the model. The paper discusses the use of the half rule for estimating effective time delay, which is a key part of the model reduction process. The half rule is used to distribute the largest neglected time constant evenly between the effective delay and the smallest retained time constant. This approach helps maintain the robustness of the controller settings. The paper also presents the derivation of PID tuning rules using direct synthesis (IMC tuning) for setpoints. The controller settings are derived based on the desired closed-loop response, and the integral time is modified to improve disturbance rejection. The paper also discusses the use of the SIMC-PID tuning rules, which are based on the half rule and provide good performance for both integrating and pure time delay processes. The paper evaluates the proposed tuning rules on various processes, showing that they provide good performance and robustness. The results show that the SIMC-PID settings are effective for a wide range of processes, including integrating processes, pure time delay processes, and second-order processes with dominant dynamics. The paper also compares the proposed rules with other tuning methods, showing that they provide better performance and robustness in many cases. The paper concludes that the simple analytic rules for model reduction and PID tuning are effective and practical for a wide range of industrial processes.