Signalling Game, Multiple Signals
From the perspective of the buyer, he is receiving 1 two-dimensional signal. After observing a combination of the wholesale price and limit order, the buyer can update their beliefs about the supplier's capacity using Bayes rule. Let me show it:

Let $c\in [0,1]$ be the supplier's capacity (just for simplicity of notation I assumed it is in the interval from 0 to 1) and assume $c$ is distributed according to $\mu_0(c)$, thus $\mu_0$ is prior belief of the buyer that the capacity is $c$. 
Then each type of supplier will optimally choose a signal $(p_w(c), \bar o(c))$ of the wholesale price and the limit on buyer's order. These are functions from the production capacity $c$ (or more generally, the  suppler's private information) into $\mathbb{R}^2$ (if some types of suppliers use mixed strategies, then $(p_w(c), \bar o(c))$ are functions that return distributions supported in  $\mathbb{R}^2$.

After receiving a signal say $(p_w, \bar o)$ the buyer's posterior belief, denoted  $\mu_1(c)$, is given by:

$$\mu_1(c|(p_w, \bar o))=\frac{Prob((p_w(c), \bar o(c))=(p_w, \bar o))\mu_0(c)}{\int_{[0,1]} Prob((p_w(t), \bar o(t))=(p_w, \bar o))\mu_0(t)dt}$$

That is the ratio of the probability of receiving signal $(p_w, \bar o)$ from a supplier with capacity $c$ over the total probability of receiving the same signal; from any type of supplier. Note that if the supplier with capacity $c$ is using a pure strategy, then $Prob((p_w(c), \bar o(c))=(p_w, \bar o)$ is either $0$ or $1$.

Given the 2 dimensional signal, I would  suspect that one of the following 3 scenarios will occur:


The buyer learns the capacity form the signal (for example if the function $f(c)=(p_w(c), \bar o(c))$ is injective from $\mathbb{R}$ into $\mathbb{R}^2$. (notice that this can occur even if one or both of the functions $p_w(c), \bar o(c)$ are not injective).
The function $\bar o(c)$ is constant, so you revert back to the case with a 1-D signal since the buyer learns nothing from $\bar o(c)$.
Suppliers choose mixed strategies. In that case, finding $(p_w(c), \bar o(c))$ will be a challenge because the set of distributions supported in $\mathbb{R}^2$ is quite large.


Good luck!