Bahan Ajar Mata Kuliah Pengendalian Kualitas

Statistical process control (SPC) is the application of statistical methods to the monitoring and control of a process to ensure that it operates at its full potential to produce conforming product. Under SPC, a process behaves predictably to produce as much conforming product as possible with the least possible waste. While SPC has been applied most frequently to controlling manufacturing lines, it applies equally well to any process with a measurable output.

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Statistical Process Control may be broadly broken down into three sets of activities: understanding the process; understanding the causes of variation; and elimination of the sources of special cause variation.

In understanding a process, the process is typically mapped out and the process is monitored using control charts. Control charts are used to identify variation that may be be due to special causes, and to free the user from concern over variation due to common causes. By the nature of the control chart, "understanding the process" is a continuous activity. With a stable process that does not trigger any of the detection rules for a control chart, a process capability analysis is also performed to evaluate the ability of the current process to produce conforming (i.e. within specification) product.

When, through the control charts, variation that is due to special causes is identified, or the process capability is found lacking, additional effort is exerted to determine causes of that variance and eliminate it. The tools used include Ishikawa diagrams, designed experiments and Pareto charts. Designed experiments are critical to this phase of SPC, as they are the only means of objectively quantifying the relative importance of the many potential causes of variation.

Once the causes of variation have been quantified, effort is spent in eliminating those causes that are both statistically and practically significant (i.e. a cause that has a only small but statistically significant effect may not be considered cost-effective to fix; conversely, a cause that is not statistically significant cannot be considered practically significant). Generally, this includes development of standard work, error-proofing and training. Additional measures may be required, especially if there is a problem with process capability.
Dalam rekayasa dan manufaktur, pengendalian mutu atau pengendalian kualitas melibatkan pengembangan sistem untuk memastikan bahwa produk dan jasa dirancang dan diproduksi untuk memenuhi atau melampaui persyaratan dari pelanggan. Sistem-sistem ini sering dikembangkan bersama dengan disiplin bisnis atau rekayasa lainnya dengan menggunakan pendekatan lintas fungsional. ISO 9000 dan TQM (Total Quality Management) adalah contoh standar dan pendekatan yang digunakan untuk pengendalian mutu.

Berikut ini adalah bahan ajar mata kuliah Pengendalian Kualitas Statistik, yang dirancang selama 16 kali pertemuan, dengan rincian sebagai berikut :
Materi 1 : Konsep dasar pengendalian kualitas
Materi 2 : Peta Kendali Variabel I
Materi 3 : Peta Kendali Variabel II
Materi 4 : Peta Kendali Atribut I
Materi 5 : Peta Kendali Atribut II
Materi 6 : Diagram Sebab Akibat
Materi 7 : Tujuh Alat Bantu Lainnya
Materi 8 : Ujian Tengah Semester