21 Aug
2018

Continuous Improvement Analysis to Reduce Rejects

Measuring Rejects and Non-Quality is essential to both lean manufacturing and continuous improvement initiatives. Learn about continuous improvement analysis methods here.

Continuous Improvement
Lean Manufacturing
Analyse de l'amélioration continue pour réduire les rejets

A fundamental tenet of Continuous Improvement eliminating waste, including reducing the costs of non-quality rejects. While the capacity to produce large amounts of product in efficiently is very important in manufacturing, the quantity of rejects occurring in that time is even more important, as it affects profitability, wastes time, and is extremely costly.

Reducing the amount, or percentage of rejects throughout the production process will improve efficiency, cut down costs, and increase output.

Below are three ways that you can look at production in order implement continuous improvement and reduce rejects:

Past of rejects reduction

Considering what happened to cause the reject in the first place may give insight into a potential solution. There is no way to fix a problem without first understanding what the caused the problem in the first place. Through this kind of analysis, understanding what happened in the past will help to prevent future rejects.

 

Present of rejects reduction

Another important analysis is to look at the production line in the present. Analyzing where there are bottlenecks and problems within the line will not only help improve efficiency, but will reduce the amount of risk for rejects.

Future of rejects reduction

Finally, it is very important to consider the future. Preventive action, whether it be keeping machines clean and maintained, training workers so that they have a comprehensive understanding of the task and are willing to ask questions, or even using the present condition of the production line to plan on making improvements down the line, is potentially the most important to consider.

Future planning for cutting down on rejects can take on many forms, each which will in some way or another help to cut down on the amount of rejects.

Worximity is deeply committed to the philosophies of Continuous Improvement and Lean Manufacturing in food manufacturing. Using our IoT technology we provide company wide visibility into the statistics that matter to manufacturers and accelerate TTV (Time to Value) of investments in company culture and training to achieve outstanding productivity.

Get started by downloading our free Lean Manufacturing Ebook.

 

 

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
21
Août 2018

Five Pillars of a Successful AI-based Transformation

English
18
septembre 2019

Événement Réseau PDG

French
11
Déc 2019

Évaluez votre logiciel de lean manufacturing

French

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
28
Juin 2023

Investir dans l'industrie 4.0 : c'est désormais plus important que jamais pour les manufacturiers d’agroalimentaire et boissons de toutes tailles

La clé est d'adopter l'innovation pour naviguer dans des conditions en constante évolution et rester à l'écoute des demandes des consommateurs, tout en maximisant la rentabilité.

French
28
Juin 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

Faced with challenges that include labor and raw material shortages, tightened regulations ,and skyrocketing costs, companies like you are struggling to produce and price products to meet the demands of increasingly cost-conscious consumers and anxious stakeholders alike.

English
27
Juin 2023

Au-delà des chiffres : maximiser le retour sur investissement dans le secteur manufacturier grâce à l'analyse de données

L'intelligence des données provient de chiffres bruts. Ces informations doivent être analysées et traduites en actions ayant un impact sur l'entreprise. Mais avec des données qui s'accumulent plus vite qu'elles ne peuvent être transformées en analyses de données manufacturières, les entreprises ratent des opportunités.

French