Scenario 1: Faster Line Re-Configuration and On-Job Training for Line Managers 

Setup and change-over of production lines are complex time-consuming activities that require trained workers capable of (re)configure machines, align production speeds, and adjust machine settings within a given amount of time. 

Both production line setup and change-over are non-value added operations and so should be minimized as much as possible. The complexity of production line setup and reconfiguration comes from the fact that:

·      each product has a different optimum configuration of the production line that is gradually explored by empirical approaches of product line managers
·      the configuration of a production line can have almost infinite states,
·      the configuration of individual machines within a production line is interdependent (i.e. product line managers need to find the optimal combination of settings), 
·      the optimal production speed is influenced by external factors, such as variation of bottle quality or ambient temperature at the production site,
·      after reconfiguration of the production lines, the first batch productions need to be tested and evaluated and the production line is fine-tuned.

To address these problems, Diversey aims to standardize the reconfiguration process of production lines for individual products by capturing the best practices with the cognitive advisor and by disseminating best practices with the help of a digital intelligent assistant.

Baseline. One production line typically produces 10 tons from product ‘A’ within 20-25 minutes and then it is reconfigured for producing product ‘B’. Reconfiguration takes approximately 20 – 25 minutes in case of a simple change over, while complex changeovers can last up to 2 hours. Change-over time or downtime currently consumes 40-45% of the total production time on average. Diversey aims to tackle the challenge of agile manufacturing by continuously optimizing the process of production line reconfiguration and by training and retraining of production line managers with the help of a digital intelligent assistant.

Using COALA Solution

Diversey expects that the COALA solution will allow production line operators to request advices, explanations, and other information via the digital assistant running on a mobile device during the changeover (T3.4).  Digital assistant will guide workers towards optimum configuration of the production line for each product and formulation (T3.2). The optimal production speed would be also considered by external factors, such as variation of bottle quality or ambient temperature at the production site. The cognitive advisor will help eliminating the fine tuning after reconfiguration of the production lines. Using COALA will reduce the change over time, time pressure caused by downtime, and lessen the cognitive workload of workers in solving unpredictable complex production line management tasks (T5.2). 

Scenario 2: Training of Production Line Managers

Training product line managers is essential for the reliable operation of production facilities at Diversey. This training involves an understanding of the production machines, safety training, standard work instructions, and guidance from experienced operators. When a novice worker starts to operate a production line an experienced production line manager is provided as a supervisor. 

Baseline. Diversey is spending approximately 4000-4500 hours on training its personnel per year only at its Italian site in Bagnolo. Extensive training enables these workers to get a general picture on how production lines need to be operated, what are the safety regulations and what are the typical steps and challenges of production line reconfiguration and operation management. This training, however does not allow enable sharing of tacit knowledge of experts. 

Using COALA Solution

To refine the current training methods applied at Diversey, COALA solution is expected to reduce the time of (re)training of product line managers. To achieve this goal COALA will:

·      Capture, formalize and contextualize tacit knowledge of product line managers about setup, reconfiguration, running, and maintenance of production lines for producing a given product. Experienced workers built up extensive experience with configuration and running of production lines, this knowledge is only partially captured and documented. Digital intelligent assistant will be used to capture the best practices for reconfiguring and running a production line (T3.1). 

·      Transfer tacit knowledge of product line managers to inexperienced co-workers (T3.2). Training of production line managers involves learning on the job activities and training onsite. DIA will be used to provide instructions on the site and in situ (T5.2). 

·      Standardize tacit knowledge of multiple experienced operators of the same production line. A production line is typically managed by multiple operators in different shifts. The best practices of running a production line according to different operators may differ. Diversey aims to standardize the best practices collection during training and during production with the support of DIA (T7.4).